id stringlengths 20 52 | title stringlengths 3 459 | abstract stringlengths 0 12.3k | classification_labels list | numerical_classification_labels list |
|---|---|---|---|---|
http://arxiv.org/abs/2104.01791v2 | A Heuristic-driven Uncertainty based Ensemble Framework for Fake News Detection in Tweets and News Articles | The significance of social media has increased manifold in the past few decades as it helps people from even the most remote corners of the world to stay connected. With the advent of technology, digital media has become more relevant and widely used than ever before and along with this, there has been a resurgence in ... | [
"Reasoning",
"Fact & Claim Verification",
"Ethical NLP",
"Responsible & Trustworthy NLP"
] | [
8,
46,
17,
4
] |
http://arxiv.org/abs/1512.03950v1 | A Hidden Markov Model Based System for Entity Extraction from Social Media English Text at FIRE 2015 | This paper presents the experiments carried out by us at Jadavpur University as part of the participation in FIRE 2015 task: Entity Extraction from Social Media Text - Indian Languages (ESM-IL). The tool that we have developed for the task is based on Trigram Hidden Markov Model that utilizes information like gazetteer... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
SCOPUS_ID:38149032434 | A Hidden Markov Model based named entity recognition system: Bengali and Hindi as case studies | Named Entity Recognition (NER) has an important role in almost all Natural Language Processing (NLP) application areas including information retrieval, machine translation, question-answering system, automatic summarization etc. This paper reports about the development of a statistical Hidden Markov Model (HMM) based N... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
http://arxiv.org/abs/1611.06607v2 | A Hierarchical Approach for Generating Descriptive Image Paragraphs | Recent progress on image captioning has made it possible to generate novel sentences describing images in natural language, but compressing an image into a single sentence can describe visual content in only coarse detail. While one new captioning approach, dense captioning, can potentially describe images in finer lev... | [
"Visual Data in NLP",
"Captioning",
"Text Generation",
"Multimodality"
] | [
20,
39,
47,
74
] |
SCOPUS_ID:85107364152 | A Hierarchical Approach for Joint Extraction of Entities and Relations | Most existing approaches for the extraction of entities and relations face two main challenges: extracting overlapping relations and capturing the interactions between entity and relation extractions. In this paper, we present a novel sequence-to-sequence model with a hierarchical decoder to solve both issues elegantly... | [
"Language Models",
"Relation Extraction",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
52,
75,
72,
3
] |
http://arxiv.org/abs/1909.12401v1 | A Hierarchical Approach for Visual Storytelling Using Image Description | One of the primary challenges of visual storytelling is developing techniques that can maintain the context of the story over long event sequences to generate human-like stories. In this paper, we propose a hierarchical deep learning architecture based on encoder-decoder networks to address this problem. To better help... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:85135753167 | A Hierarchical Approach to Interpretability of TS Rule-Based Models | Interpretability of fuzzy rule-based models has always been of significant interest to the research community and the research in this area led to a number of far-reaching results. In this study, we briefly revisit the methodology and concepts of interpretability of Takagi-Sugeno (T-S) rule-based models and develop a c... | [
"Explainability & Interpretability in NLP",
"Summarization",
"Text Generation",
"Responsible & Trustworthy NLP",
"Information Extraction & Text Mining"
] | [
81,
30,
47,
4,
3
] |
SCOPUS_ID:85115289880 | A Hierarchical Category Embedding Based Approach for Fault Classification of Power ICT System | To solve the low classification accuracy oreven misclassification issue in fault diagnosis, a text classification method based on hierarchical category embedding is proposed in information and communication technology (ICT) customer service systems. First, a hierarchical label system is constructed for the failure data... | [
"Semantic Text Processing",
"Text Classification",
"Representation Learning",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
72,
36,
12,
24,
3
] |
SCOPUS_ID:85081665146 | A Hierarchical Classification Framework for Phonemes and Broad Phonetic Groups (BPGs): a Discriminative Template-Based Approach | In this paper, a novel framework to phone or phoneme classification is presented. The framework combines discriminative classification approach to the traditional HMM framework. Unlike the traditional HMM approach to phoneme recognition, here all phones are modeled by one HMM. However, instead of using generative model... | [
"Text Classification",
"Syntactic Text Processing",
"Phonetics",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
15,
64,
24,
3
] |
SCOPUS_ID:85084761659 | A Hierarchical Clustering Approach to Fuzzy Semantic Representation of Rare Words in Neural Machine Translation | Rare words are usually replaced with a single < unk> token in the current encoder-decoder style of neural machine translation, challenging the translation modeling by an obscured context. In this article, we propose to build a fuzzy semantic representation (FSR) method for rare words through a hierarchical clustering m... | [
"Language Models",
"Machine Translation",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Representation Learning",
"Text Generation",
"Text Clustering",
"Multilinguality"
] | [
52,
51,
72,
3,
12,
47,
29,
0
] |
SCOPUS_ID:85065666811 | A Hierarchical Clustering Based Relation Extraction Method for Domain Ontology | At present, the focus of ontology learning is on the extraction of concepts and relations. The relation extraction is divided into hierarchical relation extraction and non-hierarchical relation extraction, and hierarchical relation extraction is the basis of non-hierarchical relation extraction. In this paper, the meth... | [
"Semantic Text Processing",
"Relation Extraction",
"Knowledge Representation",
"Text Clustering",
"Information Extraction & Text Mining"
] | [
72,
75,
18,
29,
3
] |
SCOPUS_ID:85072198536 | A Hierarchical Deep Correlative Fusion Network for Sentiment Classification in Social Media | Most existing research of sentiment analysis are based on either textual or visual data and can not achieve satisfied results. As multi-modal data can provide richer information, multi-modal sentiment analysis is attracting more and more attentions and has become a hot research topic. Due to the strong semantic correla... | [
"Visual Data in NLP",
"Information Extraction & Text Mining",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
"Multimodality"
] | [
20,
3,
36,
78,
24,
74
] |
SCOPUS_ID:84974288913 | A Hierarchical Dirichlet Language Model | We discuss a hierarchical probabilistic model whose predictions are similar to those of the popular language modelling procedure known as ‘smoothing’. A number of interesting differences from smoothing emerge. The insights gained from a probabilistic view of this problem point towards new directions for language modell... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
http://arxiv.org/abs/1504.05929v2 | A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution | We present a novel hierarchical distance-dependent Bayesian model for event coreference resolution. While existing generative models for event coreference resolution are completely unsupervised, our model allows for the incorporation of pairwise distances between event mentions -- information that is widely used in sup... | [
"Coreference Resolution",
"Information Extraction & Text Mining",
"Text Clustering"
] | [
13,
3,
29
] |
http://arxiv.org/abs/1805.01089v2 | A Hierarchical End-to-End Model for Jointly Improving Text Summarization and Sentiment Classification | Text summarization and sentiment classification both aim to capture the main ideas of the text but at different levels. Text summarization is to describe the text within a few sentences, while sentiment classification can be regarded as a special type of summarization which "summarizes" the text into a even more abstra... | [
"Information Retrieval",
"Summarization",
"Text Generation",
"Sentiment Analysis",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
30,
47,
78,
36,
3
] |
http://arxiv.org/abs/2108.09505v1 | A Hierarchical Entity Graph Convolutional Network for Relation Extraction across Documents | Distantly supervised datasets for relation extraction mostly focus on sentence-level extraction, and they cover very few relations. In this work, we propose cross-document relation extraction, where the two entities of a relation tuple appear in two different documents that are connected via a chain of common entities.... | [
"Multimodality",
"Relation Extraction",
"Structured Data in NLP",
"Information Extraction & Text Mining"
] | [
74,
75,
50,
3
] |
SCOPUS_ID:85094149152 | A Hierarchical Fine-Tuning Approach Based on Joint Embedding of Words and Parent Categories for Hierarchical Multi-label Text Classification | Many important classification problems in real world consist of a large number of categories. Hierarchical multi-label text classification (HMTC) with higher accuracy over large sets of closely related categories organized in a hierarchical structure or taxonomy has become a challenging problem. In this paper, we prese... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Representation Learning",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
12,
24,
3
] |
SCOPUS_ID:85085727446 | A Hierarchical Fine-Tuning Based Approach for Multi-label Text Classification | Hierarchical Text classification has recently become increasingly challenging with the growing number of classification labels. In this paper, we propose a hierarchical fine-tuning based approach for hierarchical text classification. We use the ordered neurons LSTM (ONLSTM) model by combining the embedding of text and ... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Representation Learning",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
12,
24,
3
] |
http://arxiv.org/abs/1811.03925v1 | A Hierarchical Framework for Relation Extraction with Reinforcement Learning | Most existing methods determine relation types only after all the entities have been recognized, thus the interaction between relation types and entity mentions is not fully modeled. This paper presents a novel paradigm to deal with relation extraction by regarding the related entities as the arguments of a relation. W... | [
"Relation Extraction",
"Information Extraction & Text Mining"
] | [
75,
3
] |
http://arxiv.org/abs/2208.11283v1 | A Hierarchical Interactive Network for Joint Span-based Aspect-Sentiment Analysis | Recently, some span-based methods have achieved encouraging performances for joint aspect-sentiment analysis, which first extract aspects (aspect extraction) by detecting aspect boundaries and then classify the span-level sentiments (sentiment classification). However, most existing approaches either sequentially extra... | [
"Text Classification",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
23,
78,
24,
3
] |
SCOPUS_ID:85072868301 | A Hierarchical Label Network for Multi-label EuroVoc Classification of Legislative Contents | EuroVoc is a thesaurus maintained by the European Union Publication Office, used to describe and index legislative documents. The Eurovoc concepts are organized following a hierarchical structure, with 21 domains, 127 micro-thesauri terms, and more than 6,700 detailed descriptors. The large number of concepts in the Eu... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:85128391147 | A Hierarchical Language Model for CSR | We present a new language model that includes some of the most promising techniques for overcoming linguistic inadequacy, - including POS tagging [3] and refining [4], hierarchical, locally conditioned grammars [5], parallel modelling of acoustic and linguistic domains [6] - and some of our own: language modelling as l... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:85146198285 | A Hierarchical Long Short-Term Memory Encoder-Decoder Model for Abstractive Summarization | Abstractive summarization is the task of generating concise summary of a source text, which is a challenging problem in Natural Language Processing (NLP). Many recent studies have relied on encoder-decoder sequence-to-sequence deep neural networks to solve this problem. However, most of these models treat the input as ... | [
"Language Models",
"Semantic Text Processing",
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
52,
72,
30,
47,
3
] |
SCOPUS_ID:84880793927 | A Hierarchical Method for Clustering Binary Text Image | Image clustering is a crucial task in image retrieving, filtering and organizing. Most of recent work focuses on dealing with color images or gray scale images with features extracted from text content, annotation or image content. This paper aims at binary text images and proposes a novel clustering method that can be... | [
"Visual Data in NLP",
"Multimodality",
"Information Extraction & Text Mining",
"Text Clustering"
] | [
20,
74,
3,
29
] |
SCOPUS_ID:85083979747 | A Hierarchical Model for Data-to-Text Generation | Transcribing structured data into natural language descriptions has emerged as a challenging task, referred to as “data-to-text”. These structures generally regroup multiple elements, as well as their attributes. Most attempts rely on translation encoder-decoder methods which linearize elements into a sequence. This ho... | [
"Data-to-Text Generation",
"Text Generation"
] | [
16,
47
] |
http://arxiv.org/abs/1609.02745v1 | A Hierarchical Model of Reviews for Aspect-based Sentiment Analysis | Opinion mining from customer reviews has become pervasive in recent years. Sentences in reviews, however, are usually classified independently, even though they form part of a review's argumentative structure. Intuitively, sentences in a review build and elaborate upon each other; knowledge of the review structure and ... | [
"Aspect-based Sentiment Analysis",
"Sentiment Analysis"
] | [
23,
78
] |
SCOPUS_ID:85075825614 | A Hierarchical Model with Recurrent Convolutional Neural Networks for Sequential Sentence Classification | Hierarchical neural networks approaches have achieved outstanding results in the latest sequential sentence classification research work. However, it is challenging for the model to consider both the local invariant features and word dependent information of the sentence. In this work, we concentrate on the sentence re... | [
"Semantic Text Processing",
"Text Classification",
"Representation Learning",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
72,
36,
12,
24,
3
] |
http://arxiv.org/abs/2011.09046v2 | A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus | Identifying a short segment in a long video that semantically matches a text query is a challenging task that has important application potentials in language-based video search, browsing, and navigation. Typical retrieval systems respond to a query with either a whole video or a pre-defined video segment, but it is ch... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Multimodality"
] | [
20,
52,
72,
24,
74
] |
http://arxiv.org/abs/1811.06031v2 | A Hierarchical Multi-task Approach for Learning Embeddings from Semantic Tasks | Much effort has been devoted to evaluate whether multi-task learning can be leveraged to learn rich representations that can be used in various Natural Language Processing (NLP) down-stream applications. However, there is still a lack of understanding of the settings in which multi-task learning has a significant effec... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Representation Learning",
"Responsible & Trustworthy NLP"
] | [
52,
80,
72,
12,
4
] |
http://arxiv.org/abs/2004.02016v4 | A Hierarchical Network for Abstractive Meeting Summarization with Cross-Domain Pretraining | With the abundance of automatic meeting transcripts, meeting summarization is of great interest to both participants and other parties. Traditional methods of summarizing meetings depend on complex multi-step pipelines that make joint optimization intractable. Meanwhile, there are a handful of deep neural models for te... | [
"Language Models",
"Semantic Text Processing",
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
52,
72,
30,
47,
3
] |
https://aclanthology.org//W16-4403/ | A Hierarchical Neural Network for Information Extraction of Product Attribute and Condition Sentences | This paper describes a hierarchical neural network we propose for sentence classification to extract product information from product documents. The network classifies each sentence in a document into attribute and condition classes on the basis of word sequences and sentence sequences in the document. Experimental res... | [
"Semantic Text Processing",
"Question Answering",
"Natural Language Interfaces",
"Knowledge Representation",
"Information Extraction & Text Mining"
] | [
72,
27,
11,
18,
3
] |
SCOPUS_ID:85069485473 | A Hierarchical Neural Summarization Framework for Spoken Documents | Extractive text or speech summarization seeks to select indicative sentences from a source document and assemble them together to form a succinct summary, so as to help people to browse and understand the main theme of the document efficiently. A more recent trend is towards developing supervised deep learning based me... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85066316807 | A Hierarchical Quasi-Recurrent approach to Video Captioning | Video captioning has picked up a considerable attention thanks to the ability of Recurrent Neural Networks to extrapolate an encoded representation of the input video, and then use it to generate a description. We propose a recurrent encoding approach able to find and exploit the layered design of the video. Differentl... | [
"Visual Data in NLP",
"Captioning",
"Text Generation",
"Multimodality"
] | [
20,
39,
47,
74
] |
http://arxiv.org/abs/2012.11960v1 | A Hierarchical Reasoning Graph Neural Network for The Automatic Scoring of Answer Transcriptions in Video Job Interviews | We address the task of automatically scoring the competency of candidates based on textual features, from the automatic speech recognition (ASR) transcriptions in the asynchronous video job interview (AVI). The key challenge is how to construct the dependency relation between questions and answers, and conduct the sema... | [
"Visual Data in NLP",
"Structured Data in NLP",
"Question Answering",
"Natural Language Interfaces",
"Reasoning",
"Multimodality"
] | [
20,
50,
27,
11,
8,
74
] |
http://arxiv.org/abs/1906.01833v1 | A Hierarchical Reinforced Sequence Operation Method for Unsupervised Text Style Transfer | Unsupervised text style transfer aims to alter text styles while preserving the content, without aligned data for supervision. Existing seq2seq methods face three challenges: 1) the transfer is weakly interpretable, 2) generated outputs struggle in content preservation, and 3) the trade-off between content and style is... | [
"Low-Resource NLP",
"Responsible & Trustworthy NLP",
"Text Generation",
"Text Style Transfer"
] | [
80,
4,
47,
35
] |
SCOPUS_ID:85130792473 | A Hierarchical Representation Model Based on Longformer and Transformer for Extractive Summarization | Automatic text summarization is a method used to compress documents while preserving the main idea of the original text, including extractive summarization and abstractive summarization. Extractive text summarization extracts important sentences from the original document to serve as the summary. The document represent... | [
"Language Models",
"Semantic Text Processing",
"Representation Learning",
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
52,
72,
12,
30,
47,
3
] |
SCOPUS_ID:85105727255 | A Hierarchical Sequence-To-Sequence Model for Korean POS Tagging | Part-of-speech (POS) tagging is a fundamental task in natural language processing. Korean POS tagging consists of two subtasks: morphological analysis and POS tagging. In recent years, scholars have tended to use the seq2seq model to solve this problem. The full context of a sentence is considered in these seq2seq-base... | [
"Language Models",
"Semantic Text Processing",
"Morphology",
"Syntactic Text Processing",
"Tagging"
] | [
52,
72,
73,
15,
63
] |
SCOPUS_ID:85045733609 | A Hierarchical Structured Self-Attentive Model for Extractive Document Summarization (HSSAS) | The recent advance in neural network architecture and training algorithms has shown the effectiveness of representation learning. The neural-network-based models generate better representation than the traditional ones. They have the ability to automatically learn the distributed representation for sentences and docume... | [
"Semantic Text Processing",
"Representation Learning",
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
72,
12,
30,
47,
3
] |
http://arxiv.org/abs/2003.13841v1 | A Hierarchical Transformer for Unsupervised Parsing | The underlying structure of natural language is hierarchical; words combine into phrases, which in turn form clauses. An awareness of this hierarchical structure can aid machine learning models in performing many linguistic tasks. However, most such models just process text sequentially and there is no bias towards lea... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Responsible & Trustworthy NLP"
] | [
52,
80,
72,
4
] |
http://arxiv.org/abs/2012.14781v1 | A Hierarchical Transformer with Speaker Modeling for Emotion Recognition in Conversation | Emotion Recognition in Conversation (ERC) is a more challenging task than conventional text emotion recognition. It can be regarded as a personalized and interactive emotion recognition task, which is supposed to consider not only the semantic information of text but also the influences from speakers. The current metho... | [
"Language Models",
"Semantic Text Processing",
"Natural Language Interfaces",
"Sentiment Analysis",
"Emotion Analysis",
"Dialogue Systems & Conversational Agents"
] | [
52,
72,
11,
78,
61,
38
] |
SCOPUS_ID:78049527922 | A Hierarchical visual model for video object summarization | We propose a novel method for removing irrelevant frames from a video given user-provided frame-level labeling for a very small number of frames. We first hypothesize a number of windows which possibly contain the object of interest, and then determine which window(s) truly contain the object of interest. Our method en... | [
"Visual Data in NLP",
"Information Extraction & Text Mining",
"Summarization",
"Text Generation",
"Multimodality"
] | [
20,
3,
30,
47,
74
] |
SCOPUS_ID:84994092411 | A Hierarchical word sequence language model | Most language models used for natural language processing are continuous. However, the assumption of such kind of models is too simple to cope with data sparsity problem. Although many useful smoothing techniques are developed to estimate these unseen sequences, it is still important to make full use of contextual info... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
https://aclanthology.org//W19-3510/ | A Hierarchically-Labeled Portuguese Hate Speech Dataset | Over the past years, the amount of online offensive speech has been growing steadily. To successfully cope with it, machine learning are applied. However, ML-based techniques require sufficiently large annotated datasets. In the last years, different datasets were published, mainly for English. In this paper, we presen... | [
"Ethical NLP",
"Responsible & Trustworthy NLP"
] | [
17,
4
] |
SCOPUS_ID:85112111487 | A Hierarchy of Interests: Discursive Practices on the Value of Particle and High-Energy Physics | Current science policy emphasizes practical outcomes. In this article, I explore how a fundamental research community addresses the value of research, an area that has received a little attention. In the wake of the discovery of the Higgs boson, I analyse how particle physicists interpret the values of their research i... | [
"Discourse & Pragmatics",
"Semantic Text Processing"
] | [
71,
72
] |
SCOPUS_ID:85040053208 | A Hierarchy-to-Sequence Attentional Neural Machine Translation Model | Although sequence-to-sequence attentional neural machine translation (NMT) has achieved great progress recently, it is confronted with two challenges: learning optimal model parameters for long parallel sentences and well exploiting different scopes of contexts. In this paper, partially inspired by the idea of segmenti... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
SCOPUS_ID:85135075440 | A High-Efficiency Knowledge Distillation Image Caption Technology | Image caption is wildly considered in the application of machine learning. Its purpose is describing one given picture into text accurately. Currently, it uses the Encoder-Decoder architecture from deep learning. To further increase the semantic transmitted after distillation by feature representation, this paper propo... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Green & Sustainable NLP",
"Captioning",
"Text Generation",
"Responsible & Trustworthy NLP",
"Multimodality"
] | [
20,
52,
72,
68,
39,
47,
4,
74
] |
SCOPUS_ID:85126812721 | A High-Precision Method for Segmentation and Recognition of Shopping Mall Plans | Most studies on map segmentation and recognition are focused on architectural floor plans, while there are very few analyses of shopping mall plans. The objective of the work is to accurately segment and recognize the shopping mall plan, obtaining location and semantic information for each room via segmentation and rec... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
https://aclanthology.org//W19-5212/ | A High-Quality Multilingual Dataset for Structured Documentation Translation | This paper presents a high-quality multilingual dataset for the documentation domain to advance research on localization of structured text. Unlike widely-used datasets for translation of plain text, we collect XML-structured parallel text segments from the online documentation for an enterprise software platform. Thes... | [
"Language Models",
"Machine Translation",
"Semantic Text Processing",
"Text Generation",
"Multilinguality"
] | [
52,
51,
72,
47,
0
] |
http://arxiv.org/abs/2208.04243v1 | A High-Quality and Large-Scale Dataset for English-Vietnamese Speech Translation | In this paper, we introduce a high-quality and large-scale benchmark dataset for English-Vietnamese speech translation with 508 audio hours, consisting of 331K triplets of (sentence-lengthed audio, English source transcript sentence, Vietnamese target subtitle sentence). We also conduct empirical experiments using stro... | [
"Machine Translation",
"Speech & Audio in NLP",
"Multimodality",
"Text Generation",
"Multilinguality"
] | [
51,
70,
74,
47,
0
] |
SCOPUS_ID:70349733195 | A High-speed word level finite field multiplier in F<inf>2m</inf> using redundant representation | In this paper, a high-speed word level finite field multiplier in FF 2m using redundant representation is proposed. For the class of fields that there exists a type I optimal normal basis, the new architecture has significantly higher speed compared to previously proposed architectures using either normal basis or redu... | [
"Semantic Text Processing",
"Representation Learning"
] | [
72,
12
] |
SCOPUS_ID:85105719699 | A Hindi Image Caption Generation Framework Using Deep Learning | Image captioning is the process of generating a textual description of an image that aims to describe the salient parts of the given image. It is an important problem, as it involves computer vision and natural language processing, where computer vision is used for understanding images, and natural language processing ... | [
"Visual Data in NLP",
"Captioning",
"Text Generation",
"Multimodality"
] | [
20,
39,
47,
74
] |
SCOPUS_ID:84980383359 | A Hindi Question Answering System using Machine Learning approach | A Question Answering (QA) System is fairly an Information Retrieval(IR) system in which a query is stated to the system and it relocates the correct or closest results to the specific question asked in natural language. It is one of the consequences of Natural Language Interface to Database (NLIDB). The paper discusses... | [
"Text Classification",
"Question Answering",
"Natural Language Interfaces",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
27,
11,
24,
3
] |
http://arxiv.org/abs/1211.2741v1 | A Hindi Speech Actuated Computer Interface for Web Search | Aiming at increasing system simplicity and flexibility, an audio evoked based system was developed by integrating simplified headphone and user-friendly software design. This paper describes a Hindi Speech Actuated Computer Interface for Web search (HSACIWS), which accepts spoken queries in Hindi language and provides ... | [
"Speech & Audio in NLP",
"Information Retrieval",
"Multimodality"
] | [
70,
24,
74
] |
SCOPUS_ID:79952061440 | A Hindi question answering system for E-learning documents | To empower the general mass through access to information and knowledge, organized efforts are being made to develop relevant content in local languages and provide local language capabilities to utility software. We have developed a Question Answering (QA) System for Hindi documents that would be relevant for masses u... | [
"Passage Retrieval",
"Natural Language Interfaces",
"Question Answering",
"Information Retrieval"
] | [
66,
11,
27,
24
] |
SCOPUS_ID:84920873456 | A History of English: From Proto-Indo-European to Proto-Germanic | This volume traces the prehistory of English from Proto-Indo-European, its earliest reconstructable ancestor, to Proto-Germanic, the latest ancestor shared by all the Germanic languages. It begins with a grammatical sketch of Proto-Indo-European, then discusses in detail the linguistic changes - especially in phonology... | [
"Phonology",
"Syntactic Text Processing",
"Morphology"
] | [
6,
15,
73
] |
SCOPUS_ID:84922269198 | A History of Psycholinguistics: The Pre-Chomskyan Era | How do we manage to speak and understand language? How do children acquire these skills and how does the brain support them? These psycholinguistic issues have been studied for more than two centuries. Though many Psycholinguists tend to consider their history as beginning with the Chomskyan 'cognitive revolution' of t... | [
"Psycholinguistics",
"Linguistics & Cognitive NLP"
] | [
77,
48
] |
SCOPUS_ID:85049331038 | A Holistic Approach for Recognition of Complete Urdu Ligatures Using Hidden Markov Models | Optical Character Recognition (OCR) is one of the continuously explored problems. Presently, commercial character recognizers are available reporting near to 100% recognition rates on text in a number of scripts. Despite these advancements, OCR systems however, have yet to mature for cursive scripts like Urdu. This stu... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
https://aclanthology.org//2022.bigscience-1.8/ | A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language Model | As ever larger language models grow more ubiquitous, it is crucial to consider their environmental impact. Characterised by extreme size and resource use, recent generations of models have been criticised for their voracious appetite for compute, and thus significant carbon footprint. Although reporting of carbon impac... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
http://arxiv.org/abs/2301.10606v1 | A Holistic Cascade System, benchmark, and Human Evaluation Protocol for Expressive Speech-to-Speech Translation | Expressive speech-to-speech translation (S2ST) aims to transfer prosodic attributes of source speech to target speech while maintaining translation accuracy. Existing research in expressive S2ST is limited, typically focusing on a single expressivity aspect at a time. Likewise, this research area lacks standard evaluat... | [
"Machine Translation",
"Speech & Audio in NLP",
"Multimodality",
"Text Generation",
"Multilinguality"
] | [
51,
70,
74,
47,
0
] |
http://arxiv.org/abs/1911.01248v1 | A Holistic Natural Language Generation Framework for the Semantic Web | With the ever-growing generation of data for the Semantic Web comes an increasing demand for this data to be made available to non-semantic Web experts. One way of achieving this goal is to translate the languages of the Semantic Web into natural language. We present LD2NL, a framework for verbalizing the three key lan... | [
"Text Generation"
] | [
47
] |
SCOPUS_ID:85062890603 | A Holistic Ranking Scheme for Apps | App stores or application distribution platforms allow users to present their sentiments about apps in the forms of ratings and reviews. However, selecting the "best one" from available apps that offer similar functionality is difficult task - especially, if the selection process only uses the average star rating of th... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85062916097 | A Home Service-Oriented Question Answering System with High Accuracy and Stability | With the development of deep learning, neural network-based (NN-based) methods have been applied in question answering (QA) widely and achieved significant progress. Although an NN-based QA system can obtain better performance and save manual efforts, the system is likely to suffer attacks from the external perturbatio... | [
"Natural Language Interfaces",
"Question Answering"
] | [
11,
27
] |
SCOPUS_ID:85056634887 | A Homomorphic Property of the Cryptosystems Based on Word Problem | There are many cryptosystems in the literature based on formal language theory. Some of them are public key cryptosystems and others are symmetric key cryptosystems. Homomorphic encryption is a form of encryption that allows computations to be carried out on ciphertext, thus generating an encrypted result which, when d... | [
"Linguistics & Cognitive NLP",
"Linguistic Theories"
] | [
48,
57
] |
SCOPUS_ID:85065761157 | A Hotel Review Corpus for Argument Mining | With the development of the network, the research of user reviews has become more important in academia and industry, because user reviews gradually influence the reputation of products and services. Argument mining has recently become a hot topic, and it is currently in the center of attention of the text mining resea... | [
"Argument Mining",
"Reasoning"
] | [
60,
8
] |
SCOPUS_ID:85129742944 | A Human Quality Text to Speech System for Sinhala | This paper proposes an approach on implementing a Text to Speech system for Sinhala language using MaryTTS framework. In this project, a set of rules for mapping text to sound were identified and proceeded with Unit selection mechanism. The datasets used for this study were gathered from newspaper articles and the corr... | [
"Syntactic Text Processing",
"Phonology",
"Speech & Audio in NLP",
"Multimodality"
] | [
15,
6,
70,
74
] |
http://arxiv.org/abs/2303.06944v1 | A Human Subject Study of Named Entity Recognition (NER) in Conversational Music Recommendation Queries | We conducted a human subject study of named entity recognition on a noisy corpus of conversational music recommendation queries, with many irregular and novel named entities. We evaluated the human NER linguistic behaviour in these challenging conditions and compared it with the most common NER systems nowadays, fine-t... | [
"Information Extraction & Text Mining",
"Speech & Audio in NLP",
"Natural Language Interfaces",
"Named Entity Recognition",
"Dialogue Systems & Conversational Agents",
"Multimodality"
] | [
3,
70,
11,
34,
38,
74
] |
http://arxiv.org/abs/1912.00667v1 | A Human-AI Loop Approach for Joint Keyword Discovery and Expectation Estimation in Micropost Event Detection | Microblogging platforms such as Twitter are increasingly being used in event detection. Existing approaches mainly use machine learning models and rely on event-related keywords to collect the data for model training. These approaches make strong assumptions on the distribution of the relevant micro-posts containing th... | [
"Event Extraction",
"Information Extraction & Text Mining"
] | [
31,
3
] |
SCOPUS_ID:85115649390 | A Human-Human Interaction-Driven Framework to Address Societal Issues | The scientific contribution of this paper is a multilayered Human-Human Interaction driven framework that aims to connect the needs of different sectors of the society to provide a long-term, viable, robust, and implementable solution for addressing multiple societal, economic, and humanitarian issues related to the in... | [
"Information Retrieval"
] | [
24
] |
SCOPUS_ID:85099575695 | A Human-Machine Interaction Scheme Based on Background Knowledge in 6G-Enabled IoT Environment | 6G-Enabled Internet of Things (IoT) is about to open a new era of Internet of Everything (IoE). It creates favorable conditions for new application services. The human-machine dialogue system, one of the most important forms of human-machine interaction, is expected to replace mobile applications in the future. This ar... | [
"Language Models",
"Semantic Text Processing",
"Dialogue Response Generation",
"Natural Language Interfaces",
"Text Generation",
"Dialogue Systems & Conversational Agents"
] | [
52,
72,
14,
11,
47,
38
] |
SCOPUS_ID:85147330123 | A Human-like Interactive Chatbot Framework for Vietnamese Banking Domain | In recent years, the application of chatbots evolved rapidly in numerous fields and received increasing attention in the academic and industrial communities. In this paper, we present a novel chatbot framework based on machine learning and deep learning approaches. Our framework not only answers the domain questions bu... | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
11,
38
] |
SCOPUS_ID:85123603731 | A Human-machine Cooperation Protocol for Machine Translation Output Edit Annotation | We report on a study exploring automatic edit annotation in a post-editing corpus with a new method for computing edit types. We examine edit type association with quality scores assigned to the machine translation output and the postedited texts. Finally, we account for shortcomings in our method and point out edit ty... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
SCOPUS_ID:85037085460 | A Hungarian sentiment corpus manually annotated at aspect level | In this paper we present a Hungarian sentiment corpus manually annotated at aspect level. Our corpus consists of Hungarian opinion texts written about different types of products. The main aim of creating the corpus was to produce an appropriate database providing possibilities for developing text mining software tools... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85137262944 | A Hybrid AI Model for Improving COVID-19 Sentiment Analysis in Social Networks | The recent COVID-19 (novel coronavirus disease) pandemic induced a deep polarization among regional as well as global communities. The sentiments regarding the pandemic and its impact on lifestyle and economy, often expressed via social networks, are regarded as critical metrics for capturing such polarization and form... | [
"Language Models",
"Semantic Text Processing",
"Sentiment Analysis"
] | [
52,
72,
78
] |
SCOPUS_ID:85062785864 | A Hybrid Algorithm for Text Classification Based on CNN-BLSTM with Attention | We propose an effective text classification framework, which is the hybrid of different weights of character-level and word-level features through concatenation based on Convolutional Neural Network-bidirectional long short-term memory with attention (BACNN). The first step is word segmentation or character segmentatio... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Syntactic Text Processing",
"Text Segmentation",
"Text Classification",
"Information Extraction & Text Mining"
] | [
52,
72,
24,
15,
21,
36,
3
] |
http://arxiv.org/abs/1702.01587v1 | A Hybrid Approach For Hindi-English Machine Translation | In this paper, an extended combined approach of phrase based statistical machine translation (SMT), example based MT (EBMT) and rule based MT (RBMT) is proposed to develop a novel hybrid data driven MT system capable of outperforming the baseline SMT, EBMT and RBMT systems from which it is derived. In short, the propos... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
SCOPUS_ID:85077954382 | A Hybrid Approach Handwritten Character Recognition for Mizo using Artificial Neural Network | In the past decade we have seen a rapid advancement in object recognition, however Mizo Handwritten Character Recognition (MHCR) remains an untapped field. In this study a handwritten is collected from 20 different writers each consisting of 456 Mizo characters. In total 20 X 456= 9120 characters are used for testing t... | [
"Text Segmentation",
"Syntactic Text Processing",
"Information Extraction & Text Mining"
] | [
21,
15,
3
] |
SCOPUS_ID:85135012138 | A Hybrid Approach Towards Machine Translation System for English–Hindi and Vice Versa | With the rapid progress in the technology and data in the public domain, the machine translation and data science have made remarkable progress. In this paper, we discuss our specific use case of developing machine translation system for English to Hindi and Hindi to English language translation. For this system, we ha... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
http://arxiv.org/abs/1912.00127v3 | A Hybrid Approach Towards Two Stage Bengali Question Classification Utilizing Smart Data Balancing Technique | Question classification (QC) is the primary step of the Question Answering (QA) system. Question Classification (QC) system classifies the questions in particular classes so that Question Answering (QA) System can provide correct answers for the questions. Our system categorizes the factoid type questions asked in natu... | [
"Text Classification",
"Question Answering",
"Natural Language Interfaces",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
27,
11,
24,
3
] |
SCOPUS_ID:85056478283 | A Hybrid Approach Using Topic Modeling and Class-Association Rule Mining for Text Classification: The Case of Malware Detection | We propose a novel general-purpose hybrid method comprising topic modeling and Class Association Rule Mining (CARM) for text classification in tandem. While topic modeling performs dimension reduction, association rule mining aspect is taken care by Apriori and Frequent Pattern(FP)- growth algorithms, separately. In or... | [
"Topic Modeling",
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
9,
24,
36,
3
] |
SCOPUS_ID:85044342793 | A Hybrid Approach for Arabic Text Summarization Using Domain Knowledge and Genetic Algorithms | Text summarization is the process of producing a shorter version of a specific text. Automatic summarization techniques have been applied to various domains such as medical, political, news, and legal domains proving that adapting domain-relevant features could improve the summarization performance. Despite the existen... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
http://arxiv.org/abs/2004.08673v1 | A Hybrid Approach for Aspect-Based Sentiment Analysis Using Deep Contextual Word Embeddings and Hierarchical Attention | The Web has become the main platform where people express their opinions about entities of interest and their associated aspects. Aspect-Based Sentiment Analysis (ABSA) aims to automatically compute the sentiment towards these aspects from opinionated text. In this paper we extend the state-of-the-art Hybrid Approach f... | [
"Representation Learning",
"Semantic Text Processing",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis"
] | [
12,
72,
23,
78
] |
SCOPUS_ID:85149636440 | A Hybrid Approach for Aspect-based Sentiment Analysis: A Case Study of Hotel Reviews | This study presents a method of aspect-based sentiment analysis for customer reviews related to hotels. The considered hotel aspects are staff attentiveness, room cleanliness, value for money and convenience of location. The proposed method consists of two main components. The first component is used to assemble releva... | [
"Text Classification",
"Text Clustering",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
29,
23,
78,
24,
3
] |
SCOPUS_ID:85146939481 | A Hybrid Approach for Auto-Correcting Grammatical Errors Generated by Non-Native Arabic Speakers | Spelling correction is among the most substantial Natural Language Processing (NLP) tasks, which is used as a pre-or post-processing step in many other tasks such as Optical Character Recognition (OCR). Many challenges may face while attempting to implement correctors, including correcting the real-word errors in which... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:85104673439 | A Hybrid Approach for Automatic Extractive Summarization | In recent times, there have been many works in automatic text summarization as it has become a very intriguing topic of natural language processing. A summary should be concise, delivering all the important facts of a document. State-of-The-Art extractive text summarizers use sentence ranking in various ways to extract... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85142201011 | A Hybrid Approach for Creating Knowledge Graphs: Recognizing Emerging Technologies in Dutch Companies | [
"Knowledge Representation",
"Structured Data in NLP",
"Semantic Text Processing",
"Multimodality"
] | [
18,
50,
72,
74
] | |
SCOPUS_ID:84988890405 | A Hybrid Approach for Drug Abuse Events Extraction from Twitter | Since their emergence, social media have become a reliable source of social events which attracted the interest of research community to extract them for many business requirements. However, unlike formal sources like news articles, social data exploitation for events extraction is much harder regarding the complex cha... | [
"Event Extraction",
"Information Extraction & Text Mining"
] | [
31,
3
] |
SCOPUS_ID:85139786764 | A Hybrid Approach for Extractive Summarization of Medical Documents | Text summarization helps us to obtain the most significant content from any document saving time and resources. Many researches of automatic summarization have been done with documents of general domain. In recent years, artificial intelligence and machine learning are being more and more integrated with medical field.... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85063135772 | A Hybrid Approach for French Medical Entity Recognition and Normalization | Medical document written in natural language is available in electronic form, and it constitutes an invaluable source for medical research. This paper describes our system based on hybrid approach for the task of Named Entity Recognition and Normalization of French medical documents using QUAERO corpus [1]. To evaluate... | [
"Named Entity Recognition",
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
34,
24,
36,
3
] |
http://arxiv.org/abs/2011.07403v3 | A Hybrid Approach for Improved Low Resource Neural Machine Translation using Monolingual Data | Many language pairs are low resource, meaning the amount and/or quality of available parallel data is not sufficient to train a neural machine translation (NMT) model which can reach an acceptable standard of accuracy. Many works have explored using the readily available monolingual data in either or both of the langua... | [
"Low-Resource NLP",
"Machine Translation",
"Text Generation",
"Responsible & Trustworthy NLP",
"Multilinguality"
] | [
80,
51,
47,
4,
0
] |
SCOPUS_ID:85146930883 | A Hybrid Approach for Inference between Behavioral Exception API Documentation and Implementations, and Its Applications | Automatically producing behavioral exception (BE) API documentation helps developers correctly use the libraries. The state-of-the-art approaches are either rule-based, which is too restrictive in its applicability, or deep learning (DL)-based, which requires large training dataset. To address that, we propose StatGen,... | [
"Programming Languages in NLP",
"Machine Translation",
"Multimodality",
"Text Generation",
"Multilinguality"
] | [
55,
51,
74,
47,
0
] |
SCOPUS_ID:85100513948 | A Hybrid Approach for Linguistic Summarization of Time Series | Linguistic summarization is an important step to extract information from a time series in an efficient and effective manner that simulates the human perspective. Before performing this process, scientists suggested using time series representations to identify the trends, then summarize the characteristics associated ... | [
"Information Extraction & Text Mining",
"Green & Sustainable NLP",
"Summarization",
"Text Generation",
"Responsible & Trustworthy NLP"
] | [
3,
68,
30,
47,
4
] |
SCOPUS_ID:85102141770 | A Hybrid Approach for Question Retrieval in Community Question Answerin | Community Question Answering (CQA) services, such as Yahoo! Answers and WikiAnswers, have become popular with users as one of the central paradigms for satisfying users' information needs. The task of question retrieval aims to answer one's query directly by finding the most relevant questions (together with their answ... | [
"Language Models",
"Topic Modeling",
"Semantic Text Processing",
"Intent Recognition",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
9,
72,
79,
78,
24,
3
] |
SCOPUS_ID:85115821720 | A Hybrid Approach for Stock Market Prediction Using Financial News and Stocktwits | Stock market prediction is a difficult problem that has always attracted researchers from different domains. Recently, different studies using text mining and machine learning methods were proposed. However, the efficiency of these methods is still highly dependant on the retrieval of relevant information. In this pape... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85142807561 | A Hybrid Approach for Text Summarization Using Social Mimic Optimization Algorithm | Every day, millions of Internet users share a lot of information on the web. In this digital era, the exponential growth of data on the web causes difficulties in getting the needed information quickly. Text summarization plays a crucial role in getting the needed information quickly. This work introduces a new extract... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85145699769 | A Hybrid Approach for Web Pages Classification | Currently, the internet is growing at an exponential rate and can cover just some required data. However, the immense amount of web pages makes the discovery of the target data more difficult for the user. Therefore, an efficient method to classify this huge amount of data is essential where web pages can be exploited ... | [
"Information Retrieval",
"Term Extraction",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
1,
36,
3
] |
https://aclanthology.org//W06-2207/ | A Hybrid Approach for the Acquisition of Information Extraction Patterns | [
"Information Extraction & Text Mining"
] | [
3
] | |
SCOPUS_ID:85083455867 | A Hybrid Approach for the Sentiment Analysis of Turkish Twitter Data | Social media is now playing an important role in influencing people’s sentiments. It also helps analyze how people, particularly consumers, feel about a particular topic, product or an idea. One of the recent social media platforms that people use to express their thoughts is Twitter. Due to the fact that Turkish is an... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Text Classification",
"Sentiment Analysis"
] | [
3,
24,
36,
78
] |
SCOPUS_ID:85060021028 | A Hybrid Approach of Text Summarization Using Latent Semantic Analysis and Deep Learning | In the current scenario of Information Technology, excessive and vast information is available on online resources but it is not always easy to find relevant and useful information. Along this issue, the paper is presented a method on extractive single document text summarization using Deep Learning method - Self-Organ... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85129231516 | A Hybrid Approach to Analyze Cybersecurity News Articles by Utilizing Information Extraction & Sentiment Analysis Methods | Cybersecurity is becoming indispensable for everyone and everything in the times of the Internet of Things (IoT) revolution. Every aspect of human society - be it political, financial, technological, or cultural - is affected by cyber-attacks or incidents in one way or another. Newspapers are an excellent source that p... | [
"Information Extraction & Text Mining",
"Sentiment Analysis"
] | [
3,
78
] |
SCOPUS_ID:85044006536 | A Hybrid Approach to Answer Selection in Question Answering Systems | In this paper, we present a hybrid model for answer selection in question answering systems by representing multiple kinds of features, i.e., lexical-based, word-alignment, and word-embedding. The model employs convolutional neural network, multilayer perceptron, and support vector machines to train the classifiers. We... | [
"Natural Language Interfaces",
"Question Answering"
] | [
11,
27
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.