id stringlengths 20 52 | title stringlengths 3 459 | abstract stringlengths 0 12.3k | classification_labels list | numerical_classification_labels list |
|---|---|---|---|---|
SCOPUS_ID:85068267709 | A Distributed Ensemble of Deep Convolutional Neural Networks with Random Forest for Big Data Sentiment Analysis | Big data has become an important issue for a large number of research areas. With the advent of social networks, users can express their feelings about the products they bought or the services they used every day. Also, they can share their ideas and interests, discuss current issues. Therefore, Big Data sentiment anal... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85056312030 | A Distributed Representation Model for Short Text Analysis | The distributed representation of short texts has become an important task in text mining. However, the direct application of the traditional Paragraph Vector may not be suitable, and the fundamental reason is that it does not make use of the information of corpus in training process, so it can not effectively improve ... | [
"Topic Modeling",
"Semantic Text Processing",
"Representation Learning",
"Text Clustering",
"Information Extraction & Text Mining"
] | [
9,
72,
12,
29,
3
] |
SCOPUS_ID:85055421962 | A Distributed Text Clustering Model Based on Multi-Agent | As the Internet big data grow rapidly, it urgently needs us to design new clustering approaches that can handle large-scale semi-structured and unstructured text data. The existing methods have the following disadvantages: the commonly used text datasets are very monotonous, the accuracy of text clustering on semi-stru... | [
"Responsible & Trustworthy NLP",
"Text Clustering",
"Information Extraction & Text Mining",
"Green & Sustainable NLP"
] | [
4,
29,
3,
68
] |
SCOPUS_ID:85077131787 | A Distributed Topic Model for Large-Scale Streaming Text | Learning topic information from large-scale unstructured text has attracted extensive attention from both the academia and industry. Topic models, such as LDA and its variants, are a popular machine learning technique to discover such latent structure. Among them, online variational hierarchical Dirichlet process (onli... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
http://arxiv.org/abs/2012.11635v2 | A Distributional Approach to Controlled Text Generation | We propose a Distributional Approach for addressing Controlled Text Generation from pre-trained Language Models (LMs). This approach permits to specify, in a single formal framework, both "pointwise" and "distributional" constraints over the target LM -- to our knowledge, the first model with such generality -- while m... | [
"Language Models",
"Semantic Text Processing",
"Text Generation"
] | [
52,
72,
47
] |
http://arxiv.org/abs/2210.02889v2 | A Distributional Lens for Multi-Aspect Controllable Text Generation | Multi-aspect controllable text generation is a more challenging and practical task than single-aspect control. Existing methods achieve complex multi-aspect control by fusing multiple controllers learned from single-aspect, but suffer from attribute degeneration caused by the mutual interference of these controllers. T... | [
"Text Generation"
] | [
47
] |
http://arxiv.org/abs/2106.15772v1 | A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers | We present ASDiv (Academia Sinica Diverse MWP Dataset), a diverse (in terms of both language patterns and problem types) English math word problem (MWP) corpus for evaluating the capability of various MWP solvers. Existing MWP corpora for studying AI progress remain limited either in language usage patterns or in probl... | [
"Reasoning",
"Numerical Reasoning"
] | [
8,
5
] |
http://arxiv.org/abs/2109.11834v1 | A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification | Data augmentation (DA) aims to generate constrained and diversified data to improve classifiers in Low-Resource Classification (LRC). Previous studies mostly use a fine-tuned Language Model (LM) to strengthen the constraints but ignore the fact that the potential of diversity could improve the effectiveness of generate... | [
"Low-Resource NLP",
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Information Extraction & Text Mining",
"Text Classification",
"Responsible & Trustworthy NLP"
] | [
80,
52,
72,
24,
3,
36,
4
] |
SCOPUS_ID:85097335169 | A Divide-and-Conquer Approach to the Summarization of Long Documents | We present a novel divide-and-conquer method for the neural summarization of long documents. Our method exploits the discourse structure of the document and uses sentence similarity to split the problem into an ensemble of smaller summarization problems. In particular, we break a long document and its summary into mult... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85101969114 | A Document Clustering Approach Using Shared Nearest Neighbour Affinity, TF-IDF and Angular Similarity | Quantum of data is increasing in an exponential order. Clustering is a major task in many text mining applications. Organizing text documents automatically, extracting topics from documents, retrieval of information and information filtering are considered as the applications of clustering. This task reveals identical ... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Text Classification",
"Text Clustering"
] | [
3,
24,
36,
29
] |
SCOPUS_ID:85075765279 | A Document Driven Dialogue Generation Model | Most of the current man-machine dialogues are at the two end-points of a spectrum of dialogues, i.e. goal-driven dialogues and non goal-driven chit-chats. Document-driven dialogues provide a bridge between them with the change of documents from structured data to unstructured free texts. This paper proposes a Document ... | [
"Dialogue Response Generation",
"Natural Language Interfaces",
"Text Generation",
"Dialogue Systems & Conversational Agents"
] | [
14,
11,
47,
38
] |
SCOPUS_ID:85147841547 | A Document Image Quality Assessment Algorithm Based on Information Entropy in Text Region | The quality of the image is critical to Optical Character Recognition (OCR), poor quality images will lead OCR to generate unreliable results. There are relative high ratio of low quality images in practical OCR-based application scenarios, how to evaluate quality of image and filter out unqualified images by document ... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:0016049546 | A Document Storage Method Based on Polarized Distance | Some elementary mathematical properties of term matching document retrieval systems are developed. These properties are used as a basis for a new file organization technique. Some of the advantages of this new method are (1) the key-to-address transformation is easily determined; (2) the documentary information is stor... | [
"Document Retrieval",
"Information Retrieval"
] | [
56,
24
] |
SCOPUS_ID:85119320867 | A Document-Level Machine Translation Quality Estimation Model Based on Centering Theory | Machine translation Quality Estimation (QE) aims to estimate the quality of machine translations without relying on golden references. Current QE researches mainly focus on sentence-level QE models, which could not capture discourse-related translation errors. To tackle this problem, this paper presents a novel documen... | [
"Machine Translation",
"Linguistic Theories",
"Text Generation",
"Linguistics & Cognitive NLP",
"Multilinguality"
] | [
51,
57,
47,
48,
0
] |
http://arxiv.org/abs/1906.04362v1 | A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots | We present a document-grounded matching network (DGMN) for response selection that can power a knowledge-aware retrieval-based chatbot system. The challenges of building such a model lie in how to ground conversation contexts with background documents and how to recognize important information in the documents for matc... | [
"Natural Language Interfaces",
"Information Retrieval",
"Dialogue Systems & Conversational Agents"
] | [
11,
24,
38
] |
SCOPUS_ID:85137353354 | A Dog Is Passing over the Jet? A Text-Generation Dataset for Korean Commonsense Reasoning and Evaluation | Recent natural language understanding (NLU) research on the Korean language has been vigorously maturing with the advancements of pretrained language models and datasets. However, Korean pretrained language models still struggle to generate a short sentence with a given condition based on compositionality and commonsen... | [
"Commonsense Reasoning",
"Language Models",
"Reasoning",
"Semantic Text Processing"
] | [
62,
52,
8,
72
] |
https://aclanthology.org//W15-4703/ | A Domain Agnostic Approach to Verbalizing n-ary Events without Parallel Corpora | [
"Text Generation"
] | [
47
] | |
SCOPUS_ID:85146913076 | A Domain Specific Parallel Corpus and Enhanced English-Assamese Neural Machine Translation | Machine translation deals with automatic translation from one natural language to another. Neural machine translation is a widely accepted technique of the corpus-based machine translation approach. However, an adequate amount of training data is required, and there is a need for the domain-wise parallel corpus to impr... | [
"Multilinguality",
"Language Models",
"Low-Resource NLP",
"Machine Translation",
"Semantic Text Processing",
"Text Generation",
"Responsible & Trustworthy NLP"
] | [
0,
52,
80,
51,
72,
47,
4
] |
SCOPUS_ID:84902377604 | A Domain independent double layered approach to keyphrase generation | The annotation of documents and web pages with semantic metatdata is an activity that can greatly increase the accuracy of Information Retrieval and Personalization systems, but the growing amount of text data available is too large for an extensive manual process. On the other hand, automatic keyphrase generation, a c... | [
"Term Extraction",
"Text Generation",
"Information Extraction & Text Mining"
] | [
1,
47,
3
] |
SCOPUS_ID:85105253092 | A Double Channel CNN-LSTM Model for Text Classification | The CNN-LSTM model has the advantages of combining Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM). It can perform timing analysis while extracting abstract features. It is widely used in Computer Vision and Natural Language Processing (NLP) fields and has achieved satisfactory results. However, fo... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
24,
3
] |
SCOPUS_ID:85143495464 | A Double Meta<sup>n</sup>-Semantic Search Model Based on Ontology and Semantic Similarity: Asthma Disease | With the exponential and rapid growth of online resources in recent years, there has been a huge increase in the use of search engines; these are also one of the most common ways to navigate the Web content without taking into account, in general, the request meaning by which was successfully added the user's webpage p... | [
"Semantic Text Processing",
"Semantic Similarity",
"Knowledge Representation",
"Semantic Search",
"Information Retrieval"
] | [
72,
53,
18,
41,
24
] |
SCOPUS_ID:33847333264 | A Double Metaphone encoding for Bangla and its application in spelling checker | We present a Double Metaphone encoding for Bangla that can be used by spelling checkers to improve the quality of suggestions for misspelled words. The complex rules of Bangla spelling present a significant challenge in producing suggestions for a misspelled word when employing the traditional edit-distance methods; on... | [
"Phonetics",
"Syntactic Text Processing"
] | [
64,
15
] |
http://arxiv.org/abs/2206.09158v1 | A Double-Graph Based Framework for Frame Semantic Parsing | Frame semantic parsing is a fundamental NLP task, which consists of three subtasks: frame identification, argument identification and role classification. Most previous studies tend to neglect relations between different subtasks and arguments and pay little attention to ontological frame knowledge defined in FrameNet.... | [
"Semantic Parsing",
"Structured Data in NLP",
"Semantic Text Processing",
"Multimodality"
] | [
40,
50,
72,
74
] |
SCOPUS_ID:85127519559 | A Drift-Sensitive Distributed LSTM Method for Short Text Stream Classification | Real-world applications especially in the fields of social media have produced massive short text streams. Unlike traditional normal texts, these data present the characteristics of short length, high-volume, high-velocity and variable data distribution etc, which lead to the issues of data sparsity and concept drift. ... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Representation Learning",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
12,
24,
3
] |
SCOPUS_ID:85141898622 | A Dual Attention Encoder-Decoder Text Summarization Model | A worthy text summarization should represent the fundamental content of the document. Recent studies on computerized text summarization tried to present solutions to this challenging problem. Attention models are employed extensively in text summarization process. Classical attention techniques are utilized to acquire ... | [
"Language Models",
"Semantic Text Processing",
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
52,
72,
30,
47,
3
] |
SCOPUS_ID:85135396708 | A Dual Knowledge Aggregation Network for Cross-Domain Sentiment Analysis | Cross-domain sentiment analysis (CDSA) is an essential subtask of sentiment analysis. It aims to utilize rich source domain data to conquer the data-hungry problem on target domain. Most existing approaches depending on deep learning mainly concentrate on common features or pivots. However, few of them consider the eff... | [
"Semantic Text Processing",
"Structured Data in NLP",
"Knowledge Representation",
"Sentiment Analysis",
"Multimodality"
] | [
72,
50,
18,
78,
74
] |
SCOPUS_ID:85061447293 | A Dual Prediction Network for Image Captioning | General captioning practice involves a single forward prediction, with the aim of predicting the word in the next timestep given the word in the current timestep. In this paper, we present a novel captioning framework, namely Dual Prediction Network (DPN), which is end-to-end trainable and addresses the captioning prob... | [
"Visual Data in NLP",
"Captioning",
"Text Generation",
"Multimodality"
] | [
20,
39,
47,
74
] |
http://arxiv.org/abs/2201.05780v3 | A Dual Prompt Learning Framework for Few-Shot Dialogue State Tracking | Dialogue state tracking (DST) module is an important component for task-oriented dialog systems to understand users' goals and needs. Collecting dialogue state labels including slots and values can be costly, especially with the wide application of dialogue systems in more and more new-rising domains. In this paper, we... | [
"Low-Resource NLP",
"Language Models",
"Semantic Text Processing",
"Green & Sustainable NLP",
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents",
"Responsible & Trustworthy NLP"
] | [
80,
52,
72,
68,
11,
38,
4
] |
http://arxiv.org/abs/1905.10060v1 | A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer | Unsupervised text style transfer aims to transfer the underlying style of text but keep its main content unchanged without parallel data. Most existing methods typically follow two steps: first separating the content from the original style, and then fusing the content with the desired style. However, the separation in... | [
"Low-Resource NLP",
"Responsible & Trustworthy NLP",
"Text Generation",
"Text Style Transfer"
] | [
80,
4,
47,
35
] |
SCOPUS_ID:85121902110 | A Dual Reinforcement Network for Classical and Modern Chinese Text Style Transfer | Text style transfer aims to change the stylistic features of a sentence while preserving its content. Although remarkable progress have been achieved in English style transfer, Chinese style transfer, such as classical and modern Chinese style transfer, still relies heavily on manual process. In this paper, we first co... | [
"Text Style Transfer",
"Text Generation"
] | [
35,
47
] |
SCOPUS_ID:85125186811 | A Dual Self-Attention based Network for Image Captioning | Image captioning technology has become an important solution for intelligent robots to understand image content. How to extract image information effectively is the key to generate accurate and reliable captions. In this paper, we propose a dual self-attention based network (DSAN) for image captioning. Specifically, we... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Captioning",
"Text Generation",
"Multimodality"
] | [
20,
52,
72,
39,
47,
74
] |
SCOPUS_ID:85106058010 | A Dual Simple Recurrent Network Model for Chunking and Abstract Processes in Sequence Learning | Although many studies have provided evidence that abstract knowledge can be acquired in artificial grammar learning, it remains unclear how abstract knowledge can be attained in sequence learning. To address this issue, we proposed a dual simple recurrent network (DSRN) model that includes a surface SRN encoding and pr... | [
"Syntactic Text Processing",
"Chunking"
] | [
15,
43
] |
http://arxiv.org/abs/1810.09154v3 | A Dual-Attention Hierarchical Recurrent Neural Network for Dialogue Act Classification | Recognising dialogue acts (DA) is important for many natural language processing tasks such as dialogue generation and intention recognition. In this paper, we propose a dual-attention hierarchical recurrent neural network for DA classification. Our model is partially inspired by the observation that conversational utt... | [
"Text Classification",
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
11,
38,
24,
3
] |
SCOPUS_ID:85118193883 | A Dual-Attention Neural Network for Pun Location and Using Pun-Gloss Pairs for Interpretation | Pun location is to identify the punning word (usually a word or a phrase that makes the text ambiguous) in a given short text, and pun interpretation is to find out two different meanings of the punning word. Most previous studies adopt limited word senses obtained by WSD(Word Sense Disambiguation) technique or pronunc... | [
"Explainability & Interpretability in NLP",
"Semantic Text Processing",
"Word Sense Disambiguation",
"Responsible & Trustworthy NLP"
] | [
81,
72,
65,
4
] |
http://arxiv.org/abs/2109.03587v2 | A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict | Sarcasm employs ambivalence, where one says something positive but actually means negative, and vice versa. The essence of sarcasm, which is also a sufficient and necessary condition, is the conflict between literal and implied sentiments expressed in one sentence. However, it is difficult to recognize such sentiment c... | [
"Stylistic Analysis",
"Sentiment Analysis"
] | [
67,
78
] |
http://arxiv.org/abs/2204.00796v1 | A Dual-Contrastive Framework for Low-Resource Cross-Lingual Named Entity Recognition | Cross-lingual Named Entity Recognition (NER) has recently become a research hotspot because it can alleviate the data-hungry problem for low-resource languages. However, few researches have focused on the scenario where the source-language labeled data is also limited in some specific domains. A common approach for thi... | [
"Multilinguality",
"Low-Resource NLP",
"Language Models",
"Machine Translation",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Representation Learning",
"Named Entity Recognition",
"Text Generation",
"Cross-Lingual Transfer",
"Responsible & Trustworthy NLP"
] | [
0,
80,
52,
51,
72,
3,
12,
34,
47,
19,
4
] |
http://arxiv.org/abs/2109.03277v1 | A Dual-Decoder Conformer for Multilingual Speech Recognition | Transformer-based models have recently become very popular for sequence-to-sequence applications such as machine translation and speech recognition. This work proposes a dual-decoder transformer model for low-resource multilingual speech recognition for Indian languages. Our proposed model consists of a Conformer [1] e... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Information Extraction & Text Mining",
"Speech & Audio in NLP",
"Multimodality",
"Text Generation",
"Speech Recognition",
"Text Classification",
"Multilinguality"
] | [
52,
72,
24,
3,
70,
74,
47,
10,
36,
0
] |
SCOPUS_ID:85135036721 | A Dual-Expert Framework for Event Argument Extraction | Event argument extraction (EAE) is an important information extraction task, which aims to identify the arguments of an event described in a given text and classify the roles played by them. A key characteristic in realistic EAE data is that the instance numbers of different roles follow an obvious long-tail distributi... | [
"Language Models",
"Semantic Text Processing",
"Event Extraction",
"Argument Mining",
"Reasoning",
"Information Extraction & Text Mining"
] | [
52,
72,
31,
60,
8,
3
] |
SCOPUS_ID:85102633576 | A Dual-Index Based Representation for Processing XPath Queries on Very Large XML Documents | Although XML processing has been intensively studied in recent years, designing efficient implementations for evaluating XPath queries on XML documents remains a challenge in case XML documents are very large. In this study, we implemented a tree-shaped data structure called partial tree that is intrinsically suitable ... | [
"Semantic Text Processing",
"Green & Sustainable NLP",
"Representation Learning",
"Indexing",
"Information Retrieval",
"Responsible & Trustworthy NLP"
] | [
72,
68,
12,
69,
24,
4
] |
SCOPUS_ID:85132723477 | A Dual-Pointer guided transition system for end-to-end structured sentiment analysis with global graph reasoning | Structured sentiment analysis is a newly proposed task, which aims to summarize the overall sentiment and opinion status on given texts, i.e., the opinion expression, the sentiment polarity of the opinion, the holder of the opinion, and the target the opinion towards. In this work, we investigate a transition-based mod... | [
"Structured Data in NLP",
"Sentiment Analysis",
"Knowledge Graph Reasoning",
"Reasoning",
"Multimodality"
] | [
50,
78,
54,
8,
74
] |
SCOPUS_ID:85084285674 | A Dual-Purpose Refreshable Braille Display Based on Real Time Object Detection and Optical Character Recognition | This paper proposes a dual-purpose braille system for the visually impaired people. There are two main features of this system-object detection and optical character recognition. Real time object detection will help a visually impaired person to know about the things around him and optical character recognition will he... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
http://arxiv.org/abs/2104.07221v1 | A Dual-Questioning Attention Network for Emotion-Cause Pair Extraction with Context Awareness | Emotion-cause pair extraction (ECPE), an emerging task in sentiment analysis, aims at extracting pairs of emotions and their corresponding causes in documents. This is a more challenging problem than emotion cause extraction (ECE), since it requires no emotion signals which are demonstrated as an important role in the ... | [
"Information Extraction & Text Mining"
] | [
3
] |
SCOPUS_ID:85141431321 | A Dual-channel Text Classification Model based on an Interactive Attention Mechanism | Aiming at the problem that convolutional neural network(CNN) focuses on local features and lacks the ability of text context feature extraction, In this paper, we propose a dual-channel text classification model based on Interactive Attention Mechanism(IAM). The model uses skip-gram to embed words into dense low latitu... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:84959907412 | A Dyadic Perspective on Speech Accommodation and Social Connection: Both Partners' Rejection Sensitivity Matters | Findings from confederate paradigms predict that mimicry is an adaptive route to social connection for rejection-sensitive individuals (Lakin, Chartrand, & Arkin, 2008). However, dyadic perspectives predict that whether mimicry leads to perceived connection depends on the rejection sensitivity (RS) of both partners in ... | [
"Linguistics & Cognitive NLP",
"Speech & Audio in NLP",
"Psycholinguistics",
"Multimodality"
] | [
48,
70,
77,
74
] |
http://arxiv.org/abs/cmp-lg/9508007v1 | A Dynamic Approach to Rhythm in Language: Toward a Temporal Phonology | It is proposed that the theory of dynamical systems offers appropriate tools to model many phonological aspects of both speech production and perception. A dynamic account of speech rhythm is shown to be useful for description of both Japanese mora timing and English timing in a phrase repetition task. This orientation... | [
"Syntactic Text Processing",
"Phonology",
"Speech & Audio in NLP",
"Multimodality"
] | [
15,
6,
70,
74
] |
SCOPUS_ID:85082583169 | A Dynamic Bayesian Network Approach for Analysing Topic-Sentiment Evolution | Sentiment analysis is one of the key tasks of natural language understanding. Sentiment Evolution models the dynamics of sentiment orientation over time. It can help people have a more profound and deep understanding of opinion and sentiment implied in user generated content. Existing work mainly focuses on sentiment c... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85034664290 | A Dynamic Conditional Random Field Based Framework for Sentence-Level Sentiment Analysis of Chinese Microblog | With the increasing popularity of social media, the Sentiment Analysis (SA) of the Microblog has raised as a new research topic. In this paper, we present WDCRF: a Word2vec and Dynamic Conditional Random Field (DCRF) based framework for Sentiment Analysis of Chinese Microblog. Our contributions include: firstly, to add... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Text Classification",
"Sentiment Analysis"
] | [
3,
24,
36,
78
] |
SCOPUS_ID:85115269071 | A Dynamic Convolutional Neural Network Approach for Legal Text Classification | The Amount of legal information that is being produced on a daily basis in courts is increasing enormously. The processing of such data has been receiving considerate attention thanks to their availability in an electronic form and the progress made in Artificial Intelligence application. Indeed, deep learning has show... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:85092187673 | A Dynamic Emergency Decision-Making Method Based on Group Decision Making with Uncertainty Information | In emergency decision making (EDM), it is necessary to generate an effective alternative quickly. Case-based reasoning (CBR) has been applied to EDM; however, choosing the most suitable case from a set of similar cases after case retrieval remains challenging. This study proposes a dynamic method based on case retrieva... | [
"Reasoning",
"Information Retrieval"
] | [
8,
24
] |
http://arxiv.org/abs/1905.05550v2 | A Dynamic Evolutionary Framework for Timeline Generation based on Distributed Representations | Given the collection of timestamped web documents related to the evolving topic, timeline summarization (TS) highlights its most important events in the form of relevant summaries to represent the development of a topic over time. Most of the previous work focuses on fully-observable ranking models and depends on hand-... | [
"Semantic Text Processing",
"Representation Learning"
] | [
72,
12
] |
http://arxiv.org/abs/2108.01377v1 | A Dynamic Head Importance Computation Mechanism for Neural Machine Translation | Multiple parallel attention mechanisms that use multiple attention heads facilitate greater performance of the Transformer model for various applications e.g., Neural Machine Translation (NMT), text classification. In multi-head attention mechanism, different heads attend to different parts of the input. However, the l... | [
"Language Models",
"Machine Translation",
"Semantic Text Processing",
"Text Generation",
"Multilinguality"
] | [
52,
51,
72,
47,
0
] |
SCOPUS_ID:85116488127 | A Dynamic Multi-criteria Multi-engine Approach for Text Simplification | In this work we present a multi-criteria multi-engine approach for text simplification. The main goal is to demonstrate a way to take advantage of a pool of systems, since in the literature several systems have been proposed for the task, and the results have been improving considerably. Note though, that such systems ... | [
"Paraphrasing",
"Text Generation"
] | [
32,
47
] |
SCOPUS_ID:85097441331 | A Dynamic Network Approach to the Study of Syntax | Usage-based linguists and psychologists have produced a large body of empirical results suggesting that linguistic structure is derived from language use. However, while researchers agree that these results characterize grammar as an emergent phenomenon, there is no consensus among usage-based scholars as to how the va... | [
"Linguistics & Cognitive NLP",
"Syntactic Text Processing",
"Linguistic Theories"
] | [
48,
15,
57
] |
SCOPUS_ID:85043724057 | A Dynamic Neural Field Model of Speech Cue Compensation | Categorical speech content can often be perceived directly from continuous auditory cues in the speech stream, but human-level performance on speech recognition tasks requires compensation for contextual variables like speaker identity. Regression modeling by McMurray and Jongman (2011) has suggested that for many fric... | [
"Text Generation",
"Speech Recognition",
"Speech & Audio in NLP",
"Multimodality"
] | [
47,
10,
70,
74
] |
http://arxiv.org/abs/1805.05202v2 | A Dynamic Oracle for Linear-Time 2-Planar Dependency Parsing | We propose an efficient dynamic oracle for training the 2-Planar transition-based parser, a linear-time parser with over 99% coverage on non-projective syntactic corpora. This novel approach outperforms the static training strategy in the vast majority of languages tested and scored better on most datasets than the arc... | [
"Syntactic Parsing",
"Syntactic Text Processing"
] | [
28,
15
] |
SCOPUS_ID:85083327894 | A Dynamic Parameter Enhanced Network for distant supervised relation extraction | Distant Supervised Relation Extraction (DSRE) is usually formulated as a problem about classifying a bag of sentences that contains two query entities into the predefined relation classes. Most existing methods consider those relation classes as distinct semantic categories while ignoring their potential connections to... | [
"Language Models",
"Relation Extraction",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
52,
75,
72,
3
] |
SCOPUS_ID:85075163575 | A Dynamic Perspective on Publics and Counterpublics: The Role of the Blogosphere in Pushing the Issue of Climate Change During the 2016 US Presidential Campaign | Climate change was hardly debated during the 2016 US presidential campaign. Against this background and building upon Fraser's concept of counterpublics (1990), this paper examines whether climate change advocates used the English-speaking blogosphere to push their positions forward. This study uses blog data starting ... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
http://arxiv.org/abs/cs/0310041v1 | A Dynamic Programming Algorithm for the Segmentation of Greek Texts | In this paper we introduce a dynamic programming algorithm to perform linear text segmentation by global minimization of a segmentation cost function which consists of: (a) within-segment word similarity and (b) prior information about segment length. The evaluation of the segmentation accuracy of the algorithm on a te... | [
"Programming Languages in NLP",
"Multimodality"
] | [
55,
74
] |
https://aclanthology.org//W08-1125/ | A Dynamic Programming Approach to Document Length Constraints | [
"Programming Languages in NLP",
"Text Generation",
"Multimodality"
] | [
55,
47,
74
] | |
https://aclanthology.org//W19-5943/ | A Dynamic Strategy Coach for Effective Negotiation | Negotiation is a complex activity involving strategic reasoning, persuasion, and psychology. An average person is often far from an expert in negotiation. Our goal is to assist humans to become better negotiators through a machine-in-the-loop approach that combines machine’s advantage at data-driven decision-making and... | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
11,
38
] |
SCOPUS_ID:85029211108 | A Dynamic Topic Model and Matrix Factorization-Based Travel Recommendation Method Exploiting Ubiquitous Data | The vast volumes of community-contributed geotagged photos (CCGPs) available on the Web can be utilized to make travel location recommendations. The sparsity of user location interactions makes it difficult to learn travel preferences, because a user usually visits only a limited number of travel locations. Static topi... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85075828562 | A Dynamic Word Representation Model Based on Deep Context | The currently used word embedding techniques use fixed vectors to represent words without the concept of context and dynamics. This paper proposes a deep neural network CoDyWor to model the context of words so that words in different contexts have different vector representations of words. First of all, each layer of t... | [
"Named Entity Recognition",
"Information Extraction & Text Mining",
"Semantic Text Processing",
"Representation Learning"
] | [
34,
3,
72,
12
] |
http://arxiv.org/abs/2205.12176v1 | A Dynamic, Interpreted CheckList for Meaning-oriented NLG Metric Evaluation -- through the Lens of Semantic Similarity Rating | Evaluating the quality of generated text is difficult, since traditional NLG evaluation metrics, focusing more on surface form than meaning, often fail to assign appropriate scores. This is especially problematic for AMR-to-text evaluation, given the abstract nature of AMR. Our work aims to support the development and ... | [
"Semantic Text Processing",
"Structured Data in NLP",
"Semantic Similarity",
"Representation Learning",
"Explainability & Interpretability in NLP",
"Text Generation",
"Responsible & Trustworthy NLP",
"Multimodality"
] | [
72,
50,
53,
12,
81,
47,
4,
74
] |
SCOPUS_ID:85116111438 | A Entity Attention-based model for Entity Relation Classification for Chinese Literature Text | Entity relation classification is one of the basic tasks in natural language processing. The performance of the existing relational classification in Chinese literature text is not ideal. To address the issues, we propose a entity attention-based model for entity relation classification for Chinese literature text. Our... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:85123106752 | A Entity Relation Extraction Model with Enhanced Position Attention in Food Domain | Entity-relationship extraction is a fine-grained task for constructing a knowledge graph of food public opinion in the field of food public opinion, and it is also an important research topic in the field of current information extraction. This paper aims at the multi-entity-to-relationship problem that often occurs in... | [
"Language Models",
"Semantic Text Processing",
"Relation Extraction",
"Sentiment Analysis",
"Information Extraction & Text Mining"
] | [
52,
72,
75,
78,
3
] |
SCOPUS_ID:85029740048 | A Europe of multiple flows: Contested discursive integration in trans-European transport infrastructure policy-making | This paper presents an examination of the extent to which discursive integration is accompanying the European integration process, by focusing on the development of trans-European transport infrastructure networks. Because they facilitate movement across nation-state borders, these networks are central to European inte... | [
"Discourse & Pragmatics",
"Semantic Text Processing"
] | [
71,
72
] |
SCOPUS_ID:85148694879 | A Event Extraction Method of Document-Level Based on the Self-attention Mechanism | Event extraction is an important task in the field of natural language processing. However, most of the existing event extraction techniques focus on sentence-level extraction, which inevitably ignores the contextual features of sentences and the occurrence of multiple event trigger words in the same sentence. Therefor... | [
"Event Extraction",
"Language Models",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
31,
52,
72,
3
] |
SCOPUS_ID:85149245234 | A FAISS-based Search for Story Generation | Stories have the power to change human perspectives and have applications in game development and film making. An intelligent system can generate appropriate stories for a set of keywords. We aim to build a system capable of getting stories by providing keywords as input. The stories must have a relation with the input... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Text Generation"
] | [
52,
72,
24,
47
] |
SCOPUS_ID:85135376883 | A FAST MULTILINGUAL PROBABILISTIC TAGGER | This paper presents and compares two versions of a novel automatic tagging system which is both language and tagset independent and has close to real-time response in personal computers. The system's prediction model is based on the HMM chain theory and tags each word of a text, which includes also unknown words, using... | [
"Tagging",
"Syntactic Text Processing",
"Multilinguality"
] | [
63,
15,
0
] |
SCOPUS_ID:85050754079 | A FKSVM model based on Fisher criterion for text classification | Text classification is the process of automatically assigning a given document to its previous category. It is widely used in artificial intelligence and natural language processing. In this paper, we propose a new classification model named FKSVM in order to improve the accuracy of text classification. According to th... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
http://arxiv.org/abs/1611.00801v1 | A FOFE-based Local Detection Approach for Named Entity Recognition and Mention Detection | In this paper, we study a novel approach for named entity recognition (NER) and mention detection in natural language processing. Instead of treating NER as a sequence labelling problem, we propose a new local detection approach, which rely on the recent fixed-size ordinally forgetting encoding (FOFE) method to fully e... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
http://arxiv.org/abs/0905.0740v1 | A FORTRAN coded regular expression Compiler for IBM 1130 Computing System | REC (Regular Expression Compiler) is a concise programming language which allows students to write programs without knowledge of the complicated syntax of languages like FORTRAN and ALGOL. The language is recursive and contains only four elements for control. This paper describes an interpreter of REC written in FORTRA... | [
"Programming Languages in NLP",
"Multimodality"
] | [
55,
74
] |
SCOPUS_ID:85142716877 | A Face Recognition and Sentiment Analysis Activity System using Machine Learning Algorithm | As well known, there has always been a strong connection between the attendance of a student being linked to their performance which indeed refers totheir success ultimately, and seminars play an important rolewhen it comes to assisting the students to meet industries' expectations. And the traditional way of collectin... | [
"Visual Data in NLP",
"Multimodality",
"Sentiment Analysis"
] | [
20,
74,
78
] |
SCOPUS_ID:85114636489 | A Facial Landmark Detection Method Based on Deep Knowledge Transfer | Facial landmark detection is a crucial preprocessing step in many applications that process facial images. Deep-learning-based methods have become mainstream and achieved outstanding performance in facial landmark detection. However, accurate models typically have a large number of parameters, which results in high com... | [
"Language Models",
"Responsible & Trustworthy NLP",
"Semantic Text Processing",
"Green & Sustainable NLP"
] | [
52,
4,
72,
68
] |
https://aclanthology.org//2021.fever-1.13/ | A Fact Checking and Verification System for FEVEROUS Using a Zero-Shot Learning Approach | In this paper, we propose a novel fact checking and verification system to check claims against Wikipedia content. Our system retrieves relevant Wikipedia pages using Anserini, uses BERT-large-cased question answering model to select correct evidence, and verifies claims using XLNET natural language inference model by ... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Structured Data in NLP",
"Question Answering",
"Multimodality",
"Natural Language Interfaces",
"Ethical NLP",
"Reasoning",
"Fact & Claim Verification",
"Responsible & Trustworthy NLP"
] | [
52,
80,
72,
50,
27,
74,
11,
17,
8,
46,
4
] |
http://arxiv.org/abs/1803.00712v3 | A Factoid Question Answering System for Vietnamese | In this paper, we describe the development of an end-to-end factoid question answering system for the Vietnamese language. This system combines both statistical models and ontology-based methods in a chain of processing modules to provide high-quality mappings from natural language text to entities. We present the chal... | [
"Natural Language Interfaces",
"Question Answering"
] | [
11,
27
] |
SCOPUS_ID:85117443057 | A Factoid based Question Answering System based on Dependency Analysis and Wikidata | Over the last years, the use and the need for automated question answering systems have become more important than ever. The main reasons for this relate to the constant increase of the information that is available in textual form as well as the need to facilitate users in getting information they seek in a precise, f... | [
"Natural Language Interfaces",
"Question Answering"
] | [
11,
27
] |
http://arxiv.org/abs/1604.05878v1 | A Factorization Machine Framework for Testing Bigram Embeddings in Knowledgebase Completion | Embedding-based Knowledge Base Completion models have so far mostly combined distributed representations of individual entities or relations to compute truth scores of missing links. Facts can however also be represented using pairwise embeddings, i.e. embeddings for pairs of entities and relations. In this paper we ex... | [
"Semantic Text Processing",
"Representation Learning"
] | [
72,
12
] |
http://arxiv.org/abs/1602.01576v1 | A Factorized Recurrent Neural Network based architecture for medium to large vocabulary Language Modelling | Statistical language models are central to many applications that use semantics. Recurrent Neural Networks (RNN) are known to produce state of the art results for language modelling, outperforming their traditional n-gram counterparts in many cases. To generate a probability distribution across a vocabulary, these mode... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
http://arxiv.org/abs/1911.01460v1 | A Failure of Aspect Sentiment Classifiers and an Adaptive Re-weighting Solution | Aspect-based sentiment classification (ASC) is an important task in fine-grained sentiment analysis.~Deep supervised ASC approaches typically model this task as a pair-wise classification task that takes an aspect and a sentence containing the aspect and outputs the polarity of the aspect in that sentence. However, we ... | [
"Text Classification",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
23,
78,
24,
3
] |
SCOPUS_ID:85114774687 | A Fair and Comprehensive Comparison of Multimodal Tweet Sentiment Analysis Methods | Opinion and sentiment analysis is a vital task to characterize subjective information in social media posts. In this paper, we present a comprehensive experimental evaluation and comparison with six state-of-the-art methods, from which we have re-implemented one of them. In addition, we investigate different textual an... | [
"Semantic Text Processing",
"Representation Learning",
"Ethical NLP",
"Sentiment Analysis",
"Responsible & Trustworthy NLP",
"Multimodality"
] | [
72,
12,
17,
78,
4,
74
] |
SCOPUS_ID:85141788467 | A Fake News Detection System based on Combination of Word Embedded Techniques and Hybrid Deep Learning Model | At present, most people prefer using different online sources for reading news. These sources can easily spread fake news for several malicious reasons. Detecting this unreliable news is an important task in the Natural Language Processing (NLP) field. Many governments and technology companies are engaged in this resea... | [
"Language Models",
"Semantic Text Processing",
"Ethical NLP",
"Reasoning",
"Fact & Claim Verification",
"Responsible & Trustworthy NLP"
] | [
52,
72,
17,
8,
46,
4
] |
SCOPUS_ID:85130247821 | A Fake News Detection and Credibility Ranking Platform for Portuguese Online News | The growth of social media has enabled the spread of tendentiously fake news content in a disorganized and fast manner. Despite the extensive research on fake news detection methods, algorithms and applications [1], most of the studies focused on Natural Language Processing (NLP) techniques for English content analysis... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Ethical NLP",
"Reasoning",
"Fact & Claim Verification",
"Text Classification",
"Responsible & Trustworthy NLP"
] | [
3,
24,
17,
8,
46,
36,
4
] |
https://aclanthology.org//2021.iwpt-1.8/ | A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing | We evaluate the efficacy of predicted UPOS tags as input features for dependency parsers in lower resource settings to evaluate how treebank size affects the impact tagging accuracy has on parsing performance. We do this for real low resource universal dependency treebanks, artificially low resource data with varying t... | [
"Low-Resource NLP",
"Syntactic Text Processing",
"Syntactic Parsing",
"Tagging",
"Responsible & Trustworthy NLP"
] | [
80,
15,
28,
63,
4
] |
SCOPUS_ID:56749149816 | A Farsi part-of-speech tagger based on Markov model | This paper describes applying a Part-Of-Speech (POS) tagging system on an unreported Farsi corpus by using a Markov model. Some aspects of Farsi morphology and some issues in developing a tagging system are offered. By simulation we evaluate this method on the corpus. To our knowledge, this is first time that a statist... | [
"Tagging",
"Syntactic Text Processing"
] | [
63,
15
] |
SCOPUS_ID:85043594170 | A Fast Algorithm for Posterior Inference with Latent Dirichlet Allocation | Latent Dirichlet Allocation (LDA) [1], among various forms of topic models, is an important probabilistic generative model for analyzing large collections of text corpora. The problem of posterior inference for individual texts is very important in streaming environments, but is often intractable in the worst case. To ... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85009874545 | A Fast Asymmetric Extremum Content Defined Chunking Algorithm for Data Deduplication in Backup Storage Systems | Chunk-level deduplication plays an important role in backup storage systems. Existing Content-Defined Chunking (CDC) algorithms, while robust in finding suitable chunk boundaries, face the key challenges of (1) low chunking throughput that renders the chunking stage a serious deduplication performance bottleneck, (2) l... | [
"Responsible & Trustworthy NLP",
"Chunking",
"Syntactic Text Processing",
"Green & Sustainable NLP"
] | [
4,
43,
15,
68
] |
http://arxiv.org/abs/2205.07646v1 | A Fast Attention Network for Joint Intent Detection and Slot Filling on Edge Devices | Intent detection and slot filling are two main tasks in natural language understanding and play an essential role in task-oriented dialogue systems. The joint learning of both tasks can improve inference accuracy and is popular in recent works. However, most joint models ignore the inference latency and cannot meet the... | [
"Semantic Text Processing",
"Semantic Parsing",
"Intent Recognition",
"Natural Language Interfaces",
"Sentiment Analysis",
"Dialogue Systems & Conversational Agents"
] | [
72,
40,
79,
11,
78,
38
] |
http://arxiv.org/abs/1802.10078v1 | A Fast Deep Learning Model for Textual Relevance in Biomedical Information Retrieval | Publications in the life sciences are characterized by a large technical vocabulary, with many lexical and semantic variations for expressing the same concept. Towards addressing the problem of relevance in biomedical literature search, we introduce a deep learning model for the relevance of a document's text to a keyw... | [
"Information Retrieval"
] | [
24
] |
SCOPUS_ID:85082167856 | A Fast Estimation of Initial Rotor Position for Low-Speed Free-Running IPMSM | Fast and reliable initial rotor position detection is essential for restarting sensorless permanent magnet synchronous motors (PMSMs) in free-running condition. In this article, a fast initial rotor position estimation method for low-speed free-running motor is proposed, which utilizes a combined sinusoidal current and... | [
"Polarity Analysis",
"Sentiment Analysis"
] | [
33,
78
] |
SCOPUS_ID:85132713369 | A Fast Indoor Positioning Using a Knowledge-Distilled Convolutional Neural Network (KD-CNN) | Fingerprint-based indoor positioning systems (F-IPS) may provide inexpensive solutions to GPS-denied environments. Most F-IPSs adopt traditional machine learning for position prediction, resulting in low accuracy. Deep neural networks (DNN) were recently employed for F-IPSs to minimize positioning errors. Nevertheless,... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Green & Sustainable NLP",
"Responsible & Trustworthy NLP",
"Multimodality"
] | [
20,
52,
72,
68,
4,
74
] |
SCOPUS_ID:85087029453 | A Fast Mode of Tweets Polarity Detection | Polarity detection is an emerging area of research in text mining. Polarity detection is observing and identifying the sentiment inclination of text, whether it is positive or negative. In this paper, a fast mode of supervised learning for polarity detection on tweets is proposed, that is using datasets available in pu... | [
"Polarity Analysis",
"Sentiment Analysis"
] | [
33,
78
] |
SCOPUS_ID:85041829184 | A Fast Multi-level Plagiarism Detection Method Based on Document Embedding Representation | Nowadays, global networks facilitate access to vast amount of textual information and enhance the feasibility of plagiarism as a consequence. Given the amount of text material produced everyday, the need for an automated fast plagiarism detection system is more crucial than ever. Plagiarism detection is defined as iden... | [
"Semantic Text Processing",
"Representation Learning"
] | [
72,
12
] |
http://arxiv.org/abs/2204.09656v2 | A Fast Post-Training Pruning Framework for Transformers | Pruning is an effective way to reduce the huge inference cost of Transformer models. However, prior work on pruning Transformers requires retraining the models. This can add high training cost and high complexity to model deployment, making it difficult to use in many practical situations. To address this, we propose a... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:85102010507 | A Fast Search System for Remote Sensing Imagery Based on Bag of Visual Words and Latent Dirichlet Allocation | In this paper, we present our image search system for remote sensing imagery leveraging the capabilities of Elasticsearch, a well-known full-text search engine. We use bag of visual words and bag of visual topics model to represent the earth observation images in a text- equivalent format. The image files are stored in... | [
"Visual Data in NLP",
"Information Retrieval",
"Multimodality"
] | [
20,
24,
74
] |
SCOPUS_ID:85047193555 | A Fast Uyghur Text Detector for Complex Background Images | Uyghur text localization in images with complex backgrounds is a challenging yet important task for many applications. Generally, Uyghur characters in images consist of strokes with uniform features, and they are distinct from backgrounds in color, intensity, and texture. Based on these differences, we propose a FASTro... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
https://aclanthology.org//W06-1008/ | A Fast and Accurate Method for Detecting English-Japanese Parallel Texts | [
"Multilinguality"
] | [
0
] | |
SCOPUS_ID:85044994675 | A Fast and Accurate Rule-Base Generation Method for Mamdani Fuzzy Systems | The problem of learning fuzzy rule bases is analyzed from the perspective of finding a favorable balance between the accuracy of the system, the speed required to learn the rules, and, finally, the interpretability of the rule bases obtained. Therefore, we introduce a complete design procedure to learn and then optimiz... | [
"Explainability & Interpretability in NLP",
"Responsible & Trustworthy NLP"
] | [
81,
4
] |
http://arxiv.org/abs/1709.06307v2 | A Fast and Accurate Vietnamese Word Segmenter | We propose a novel approach to Vietnamese word segmentation. Our approach is based on the Single Classification Ripple Down Rules methodology (Compton and Jansen, 1990), where rules are stored in an exception structure and new rules are only added to correct segmentation errors given by existing rules. Experimental res... | [
"Text Segmentation",
"Syntactic Text Processing"
] | [
21,
15
] |
SCOPUS_ID:85013046481 | A Fast and Efficient Framework for Creating Parallel Corpus | Objectives: A framework involving Scansnap SV600 scanner and Google Optical character recognition (OCR) for creating parallel corpus which is a very essential component of Statistical Machine Translation (SMT). Methods and Analysis: Training a language model for a SMT system highly depends on the availability of a para... | [
"Visual Data in NLP",
"Machine Translation",
"Green & Sustainable NLP",
"Multimodality",
"Text Generation",
"Responsible & Trustworthy NLP",
"Multilinguality"
] | [
20,
51,
68,
74,
47,
4,
0
] |
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