id stringlengths 20 52 | title stringlengths 3 459 | abstract stringlengths 0 12.3k | classification_labels list | numerical_classification_labels list |
|---|---|---|---|---|
http://arxiv.org/abs/1905.04749v2 | A Benchmark Study of Machine Learning Models for Online Fake News Detection | The proliferation of fake news and its propagation on social media has become a major concern due to its ability to create devastating impacts. Different machine learning approaches have been suggested to detect fake news. However, most of those focused on a specific type of news (such as political) which leads us to t... | [
"Language Models",
"Semantic Text Processing",
"Ethical NLP",
"Reasoning",
"Fact & Claim Verification",
"Responsible & Trustworthy NLP"
] | [
52,
72,
17,
8,
46,
4
] |
SCOPUS_ID:85099607543 | A Benchmark Study on Machine Learning Methods using Several Feature Extraction Techniques for News Genre Detection from Bangla News Articles & Titles | Genre detection from news articles or news titles is one kind of text classification procedures where news articles or titles are categorized among different families. Nowadays, text classification has become a key research field in text mining and natural language understanding because of it's several applications, su... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
http://arxiv.org/abs/2211.07980v1 | A Benchmark and Dataset for Post-OCR text correction in Sanskrit | Sanskrit is a classical language with about 30 million extant manuscripts fit for digitisation, available in written, printed or scannedimage forms. However, it is still considered to be a low-resource language when it comes to available digital resources. In this work, we release a post-OCR text correction dataset con... | [
"Visual Data in NLP",
"Text Error Correction",
"Syntactic Text Processing",
"Multimodality"
] | [
20,
26,
15,
74
] |
SCOPUS_ID:85027982130 | A Benchmark and Evaluation for Text Extraction from PDF | Extracting the body text from a PDF document is an important but surprisingly difficult task. The reason is that PDF is a layout-based format which specifies the fonts and positions of the individual characters rather than the semantic units of the text (e.g., words or paragraphs) and their role in the document (e.g., ... | [
"Information Extraction & Text Mining"
] | [
3
] |
SCOPUS_ID:85104464876 | A Benchmark for Analyzing Chart Images | Charts are a compact method of displaying and comparing data. Automatically extracting data from charts is a key step in understanding the intent behind a chart which could lead to a better understanding of the document itself. To promote the development of automatically decompose and understand these visualizations. T... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
http://arxiv.org/abs/2201.05793v1 | A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases | Knowledge Base Question Answering (KBQA) tasks that involve complex reasoning are emerging as an important research direction. However, most existing KBQA datasets focus primarily on generic multi-hop reasoning over explicit facts, largely ignoring other reasoning types such as temporal, spatial, and taxonomic reasonin... | [
"Semantic Text Processing",
"Question Answering",
"Explainability & Interpretability in NLP",
"Knowledge Representation",
"Natural Language Interfaces",
"Reasoning",
"Responsible & Trustworthy NLP"
] | [
72,
27,
81,
18,
11,
8,
4
] |
http://arxiv.org/abs/2211.15421v1 | A Benchmark for Structured Extractions from Complex Documents | Understanding visually-rich business documents to extract structured data and automate business workflows has been receiving attention both in academia and industry. Although recent multi-modal language models have achieved impressive results, we find that existing benchmarks do not reflect the complexity of real docum... | [
"Low-Resource NLP",
"Language Models",
"Visual Data in NLP",
"Semantic Text Processing",
"Structured Data in NLP",
"Multimodality",
"Responsible & Trustworthy NLP",
"Information Extraction & Text Mining"
] | [
80,
52,
20,
72,
50,
74,
4,
3
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https://aclanthology.org//2020.nlpbt-1.4/ | A Benchmark for Structured Procedural Knowledge Extraction from Cooking Videos | Watching instructional videos are often used to learn about procedures. Video captioning is one way of automatically collecting such knowledge. However, it provides only an indirect, overall evaluation of multimodal models with no finer-grained quantitative measure of what they have learned. We propose instead, a bench... | [
"Visual Data in NLP",
"Multimodality",
"Information Extraction & Text Mining"
] | [
20,
74,
3
] |
SCOPUS_ID:85142007156 | A Benchmark for the Use of Topic Models for Text Visualization Tasks | Based on the assumption that semantic relatedness between documents is reflected in the distribution of the vocabulary, topic models are a widely used class of techniques for text analysis tasks. The application of topic models results in concepts, the so-called topics, and a high-dimensional description of the documen... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85132753357 | A Benchmark of Parsing Vietnamese Publications | In recent decades, digital transformation has received growing attention worldwide, that has leveraged the explosion of digitized document data. In this paper, we address the problem of parsing publications, in particular, Vietnamese publications. The Vietnamese publications are well-known with high variant, diverse la... | [
"Visual Data in NLP",
"Captioning",
"Text Generation",
"Multimodality"
] | [
20,
39,
47,
74
] |
http://arxiv.org/abs/2011.01615v1 | A Benchmark of Rule-Based and Neural Coreference Resolution in Dutch Novels and News | We evaluate a rule-based (Lee et al., 2013) and neural (Lee et al., 2018) coreference system on Dutch datasets of two domains: literary novels and news/Wikipedia text. The results provide insight into the relative strengths of data-driven and knowledge-driven systems, as well as the influence of domain, document length... | [
"Coreference Resolution",
"Information Extraction & Text Mining"
] | [
13,
3
] |
SCOPUS_ID:85131128251 | A Benchmark of Named Entity Recognition Approaches in Historical Documents Application to 19 <sup>th</sup> Century French Directories | Named entity recognition (NER) is a necessary step in many pipelines targeting historical documents. Indeed, such natural language processing techniques identify which class each text token belongs to, e.g. “person name”, “location”, “number”. Introducing a new public dataset built from 19th century French directories,... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Named Entity Recognition",
"Multimodality"
] | [
20,
52,
72,
3,
34,
74
] |
http://arxiv.org/abs/2003.07743v2 | A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs | Entity alignment seeks to find entities in different knowledge graphs (KGs) that refer to the same real-world object. Recent advancement in KG embedding impels the advent of embedding-based entity alignment, which encodes entities in a continuous embedding space and measures entity similarities based on the learned emb... | [
"Semantic Text Processing",
"Structured Data in NLP",
"Representation Learning",
"Knowledge Representation",
"Multimodality"
] | [
72,
50,
12,
18,
74
] |
http://arxiv.org/abs/2105.03409v1 | A Benchmarking on Cloud based Speech-To-Text Services for French Speech and Background Noise Effect | This study presents a large scale benchmarking on cloud based Speech-To-Text systems: {Google Cloud Speech-To-Text}, {Microsoft Azure Cognitive Services}, {Amazon Transcribe}, {IBM Watson Speech to Text}. For each systems, 40158 clean and noisy speech files about 101 hours are tested. Effect of background noise on STT ... | [
"Text Generation",
"Speech & Audio in NLP",
"Speech Recognition",
"Multimodality"
] | [
47,
70,
10,
74
] |
http://arxiv.org/abs/1406.3915v1 | A Bengali HMM Based Speech Synthesis System | The paper presents the capability of an HMM-based TTS system to produce Bengali speech. In this synthesis method, trajectories of speech parameters are generated from the trained Hidden Markov Models. A final speech waveform is synthesized from those speech parameters. In our experiments, spectral properties were repre... | [
"Speech & Audio in NLP",
"Multimodality"
] | [
70,
74
] |
https://aclanthology.org//W12-3507/ | A Bengali Speech Synthesizer on Android OS | [
"Speech & Audio in NLP",
"Multimodality"
] | [
70,
74
] | |
SCOPUS_ID:85081554585 | A Bengali Text Generation Approach in Context of Abstractive Text Summarization Using RNN | Automatic text summarization is one of the mentionable research areas of natural language processing. The amount of data is increasing rapidly, and the necessity of understanding the gist of any text is just a mandatory tool, nowadays. The area of text summarization has been developing since many years. Mentionable res... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85143124474 | A Bert-based Joint Model of Intent Recognition and Slot Filling Cross-correlation | Intent recognition and slot filling are two key steps in natural language understanding. In the past, the two steps were often completed separately, and a large number of joint modeling methods have recently demonstrated that the two are closely related and can leverage the shared knowledge between tasks to achieve bet... | [
"Language Models",
"Semantic Text Processing",
"Semantic Parsing",
"Intent Recognition",
"Sentiment Analysis"
] | [
52,
72,
40,
79,
78
] |
SCOPUS_ID:84859176984 | A Bespoked secure framework for an ontology-based data-extraction system | In this Bespoked Secure Framework for an Ontology-Based Data-Extraction System study, we report on the implementation of existing generalized framework with alternate technology. Implementation is done using Natural language processing instead of heuristic based method. Heuristic methods are based on assumptions. The a... | [
"Knowledge Representation",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
18,
72,
3
] |
SCOPUS_ID:0027576803 | A Best-First Language Processing Model Integrating the Unification Grammar and Markov Language Model for Speech Recognition Applications | In speech recognition applications, a language proscessing model is to find out a most promising sentence hypothesis for a given word lattice obtained from acoustic signal processor. Conventionally, either grammatical or statistical approaches can be used in such problems. In this paper a new language processing model ... | [
"Language Models",
"Semantic Text Processing",
"Speech & Audio in NLP",
"Text Generation",
"Speech Recognition",
"Multimodality"
] | [
52,
72,
70,
47,
10,
74
] |
http://arxiv.org/abs/2212.09052v1 | A Better Choice: Entire-space Datasets for Aspect Sentiment Triplet Extraction | Aspect sentiment triplet extraction (ASTE) aims to extract aspect term, sentiment and opinion term triplets from sentences. Since the initial datasets used to evaluate models on ASTE had flaws, several studies later corrected the initial datasets and released new versions of the datasets independently. As a result, dif... | [
"Information Extraction & Text Mining",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis"
] | [
3,
23,
78
] |
SCOPUS_ID:85121910195 | A Better Multiway Attention Framework for Fine-Tuning | Powerful pre-training models have been paid widespread attention. However, little attention has been devoted to solve downstream natural language understanding (NLU) tasks in fine-tuning stage. In this paper, we propose a novel architecture named multiway attention framework (MA) in fine-tuning stage. Which utilizes a ... | [
"Language Models",
"Semantic Text Processing",
"Representation Learning"
] | [
52,
72,
12
] |
http://arxiv.org/abs/2005.08271v2 | A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer | Dense video captioning aims to localize and describe important events in untrimmed videos. Existing methods mainly tackle this task by exploiting only visual features, while completely neglecting the audio track. Only a few prior works have utilized both modalities, yet they show poor results or demonstrate the importa... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Captioning",
"Speech & Audio in NLP",
"Text Generation",
"Multimodality"
] | [
20,
52,
72,
39,
70,
47,
74
] |
http://arxiv.org/abs/1909.02218v1 | A Better Way to Attend: Attention with Trees for Video Question Answering | We propose a new attention model for video question answering. The main idea of the attention models is to locate on the most informative parts of the visual data. The attention mechanisms are quite popular these days. However, most existing visual attention mechanisms regard the question as a whole. They ignore the wo... | [
"Visual Data in NLP",
"Natural Language Interfaces",
"Question Answering",
"Multimodality"
] | [
20,
11,
27,
74
] |
SCOPUS_ID:85125950349 | A Bi-Channel Math Word Problem Solver With Understanding and Reasoning | This paper addresses the problem of solving arithmetic word problems that are stated in Chinese with some commonsense implicit quantity relations. The addition of commonsense quantity relations is a critical step in building the machine solver for solving arithmetic word problems. This paper proposes a channel-based me... | [
"Commonsense Reasoning",
"Reasoning",
"Numerical Reasoning"
] | [
62,
8,
5
] |
SCOPUS_ID:85131146946 | A Bi-LSTM and GRU Hybrid Neural Network with BERT Feature Extraction for Amazon Textual Review Analysis | Nowadays, businesses move towards digital platforms for their product promotion and to improve their overall profit margin. Customer reviews determine the purchase decision of the specified products in the e-commerce system in this digital world. In this case, reviewing products before buying is the common scenario in ... | [
"Language Models",
"Information Extraction & Text Mining",
"Semantic Text Processing",
"Information Retrieval",
"Sentiment Analysis",
"Responsible & Trustworthy NLP",
"Text Classification",
"Green & Sustainable NLP"
] | [
52,
3,
72,
24,
78,
4,
36,
68
] |
http://arxiv.org/abs/1608.07720v1 | A Bi-LSTM-RNN Model for Relation Classification Using Low-Cost Sequence Features | Relation classification is associated with many potential applications in the artificial intelligence area. Recent approaches usually leverage neural networks based on structure features such as syntactic or dependency features to solve this problem. However, high-cost structure features make such approaches inconvenie... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
24,
3
] |
SCOPUS_ID:85135049491 | A Bi-level Individualized Adaptive Learning Recommendation System Based on Topic Modeling | Adaptive learning offers real attention to individual students’ differences and fits different needs from students. This study proposes a bi-level recommendation system with topic models, gradient descent, and a content-based filtering algorithm. In the first level, the learning materials were analyzed by a topic model... | [
"Language Models",
"Topic Modeling",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
52,
9,
72,
3
] |
SCOPUS_ID:85137266885 | A Bi-level representation learning model for medical visual question answering | Medical Visual Question Answering (VQA) targets at answering questions related to given medical images and it contains tremendous potential in healthcare services. However, researches on medical VQA are still facing challenges, particularly on how to learn a fine-grained multimodal semantic representation from relative... | [
"Visual Data in NLP",
"Semantic Text Processing",
"Question Answering",
"Representation Learning",
"Natural Language Interfaces",
"Reasoning",
"Multimodality"
] | [
20,
72,
27,
12,
11,
8,
74
] |
http://arxiv.org/abs/1812.10235v1 | A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling | Intent detection and slot filling are two main tasks for building a spoken language understanding(SLU) system. Multiple deep learning based models have demonstrated good results on these tasks . The most effective algorithms are based on the structures of sequence to sequence models (or "encoder-decoder" models), and g... | [
"Language Models",
"Semantic Text Processing",
"Semantic Parsing",
"Intent Recognition",
"Sentiment Analysis"
] | [
52,
72,
40,
79,
78
] |
SCOPUS_ID:85144059396 | A Bi-party Engaged Modeling Framework for Renewable Power Predictions with Privacy-preserving | This paper presents a pioneering study in developing data-driven models for predicting the future renewable power out-put sequence via using numerical weather predictions of multiple sites without breaching the data privacy. A novel bi-party engaged data-driven modeling framework (BEDMF) is developed to enable efficien... | [
"Language Models",
"Semantic Text Processing",
"Ethical NLP",
"Responsible & Trustworthy NLP"
] | [
52,
72,
17,
4
] |
SCOPUS_ID:85146199171 | A Bi-recursive Auto-encoders for Learning SemanticWord Embedding | The meaning of a word depends heavily on the context in which it is embedded. Deep neural network have recorded recently a great success in representing the words' meaning. Among them, auto-encoders based models have proven their robustness in representing the internal structure of several data. Thus, in this paper, we... | [
"Language Models",
"Semantic Text Processing",
"Representation Learning"
] | [
52,
72,
12
] |
SCOPUS_ID:85145355335 | A BiLSTM-CRF Based Approach to Word Segmentation in Chinese | This paper proposes a approach for word segmentation in Chinese. The word segmentation model in this paper combines Bi-directional Long Short-Term Memory (BiLSTM) and Conditional Random Fields (CRF), and proposes a four-state word segmentation model of DSZM, so that the model can not only consider the correlation betwe... | [
"Language Models",
"Text Segmentation",
"Semantic Text Processing",
"Syntactic Text Processing"
] | [
52,
21,
72,
15
] |
SCOPUS_ID:85116260167 | A BiLSTM-CRF Entity Type Tagger for Question Answering System | Question answering system over linked data (QALD) has been a very important research field in natural language processing (NLP). And the process of detecting useful words and assigning them with right entity types is crucial to the performance of QALD systems. Although entity-type taggers achieved good results using pr... | [
"Language Models",
"Semantic Text Processing",
"Structured Data in NLP",
"Question Answering",
"Syntactic Text Processing",
"Natural Language Interfaces",
"Tagging",
"Multimodality"
] | [
52,
72,
50,
27,
15,
11,
63,
74
] |
SCOPUS_ID:85079220701 | A BiLSTM-based system for cross-lingual pronoun prediction | We describe the Uppsala system for the 2017 DiscoMT shared task on cross-lingual pronoun prediction. The system is based on a lower layer of BiLSTMs reading the source and target sentences respectively. Classification is based on the BiLSTM representation of the source and target positions for the pronouns. In addition... | [
"Language Models",
"Semantic Text Processing",
"Cross-Lingual Transfer",
"Multilinguality"
] | [
52,
72,
19,
0
] |
SCOPUS_ID:85126998554 | A Biaffine Attention-Based Approach for Event Factor Extraction | Event extraction is an important task under certain profession domains. CCKS 2021 holds a communication domain event extraction benchmark and we purposed an approach with the biaffine attention mechanism to finish the task. The solution combines the state-of-the-art BERT-like base models and the biaffine attention mech... | [
"Event Extraction",
"Information Extraction & Text Mining"
] | [
31,
3
] |
SCOPUS_ID:85143058609 | A Biased Random-key Genetic Algorithm for Extractive Single-document Summarisation | Extractive text summarization has been dealt with by several metaheuristics that proved their efficiency. In those works the feasibility of solutions has been mostly guaranteed through some operators, whose role is to check and/or correct infeasible solutions. To reduce the complexity of the task, this works proposes a... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85121767904 | A Bibliometric Analysis of COVID-19 Vaccines and Sentiment Analysis | Recent statistical and social studies have shown that social media platforms such as Instagram, Facebook, and Twitter contain valuable data that influence human behaviors. This data can be used to track, fight, and control the spread of the COVID-19 and are an excellent asset for analyzing and understanding people's se... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85103676217 | A Bibliometric Analysis of Distributed Incremental Clustering on Images | Unstructured information is continuously irregular and streaming information from such a sequence is tedious because it lacks labels and accumulates with time. This is possible using Incremental Clustering algorithms that use previously learned information to accommodate new data and avoid retraining. This paper theref... | [
"Visual Data in NLP",
"Multimodality",
"Information Extraction & Text Mining",
"Text Clustering"
] | [
20,
74,
3,
29
] |
SCOPUS_ID:85149502500 | A Bibliometric Analysis of Machine Translation Post-editing from 2012 to 2021 | Machine translation post-editing (MTPE) has gained a lot of attention lately. This paper conducted a bibliometric analysis of 270 publications on MTPE retrieved from the core database of Web of Science in recent decade from 2012 to 2021 with the aid of literature analysis software VOSviewer. By means of keyword co-occu... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
SCOPUS_ID:85140917225 | A Bibliometric Review of Soft Computing for Recommender Systems and Sentiment Analysis | Soft computing, which focuses on approximate models and provides solutions to complicated real-life issues, has gained increasing momentum in application-specific domains, such as sentiment analysis and recommender systems, to emulate cognitive processes behind decision-making. In this work, bibliometrics and structura... | [
"Topic Modeling",
"Information Extraction & Text Mining",
"Sentiment Analysis"
] | [
9,
3,
78
] |
SCOPUS_ID:85136782321 | A Bibliometric Review of the Mathematics Journal | In this study, we conduct a bibliometric review of the Mathematics journal to map its thematic structure, and to identify major research trends for future research to build on. Our review focuses primarily on the bibliometric clusters derived from an application of a bibliographic coupling algorithm and offers insights... | [
"Topic Modeling",
"Reasoning",
"Numerical Reasoning",
"Information Extraction & Text Mining"
] | [
9,
8,
5,
3
] |
SCOPUS_ID:85142822650 | A Bibliometric Review of Methods and Algorithms for Generating Corpora for Learning Vector Word Embeddings | Natural Language Processing (NLP) problems are among the hardest Machine Learning (ML) problems due to the complex nature of the human language. The introduction of word embeddings improved the performance of ML models on various NLP tasks as text classification, sentiment analysis, machine translation, etc. Word embed... | [
"Semantic Text Processing",
"Representation Learning"
] | [
72,
12
] |
SCOPUS_ID:85098583158 | A Bibliometric Survey on Cognitive Document Processing | Heterogenous and voluminous unstructured data is produced from various sources like emails, social media tweets, reviews, videos, audio, images, PDFs, scanned documents, etc. Organizations need to store this wide range of unstructured data for more and longer periods so that they can examine information all the more pr... | [
"Visual Data in NLP",
"Structured Data in NLP",
"Multimodality"
] | [
20,
50,
74
] |
SCOPUS_ID:85119429385 | A Bibliometric and Sentiment Analysis of CARV and MCPC Conferences in the 21<sup>st</sup> Century: Towards Sustainable Customization | This opening paper of the CARV/MCPC 2021 book of proceedings presents a study of papers published within the series of Changeable, Agile, Reconfigurable and Virtual Conferences (CARV) and Mass Customization & Personalization Conference (MCPC). In total, 398 papers are included from the three most recent MCPC conference... | [
"Responsible & Trustworthy NLP",
"Sentiment Analysis",
"Green & Sustainable NLP"
] | [
4,
78,
68
] |
SCOPUS_ID:85092150955 | A Bichannel Transformer with Context Encoding for Document-Driven Conversation Generation in Social Media | Along with the development of social media on the internet, dialogue systems are becoming more and more intelligent to meet users' needs for communication, emotion, and social intercourse. Previous studies usually use sequence-to-sequence learning with recurrent neural networks for response generation. However, recurre... | [
"Language Models",
"Semantic Text Processing",
"Dialogue Response Generation",
"Natural Language Interfaces",
"Text Generation",
"Dialogue Systems & Conversational Agents"
] | [
52,
72,
14,
11,
47,
38
] |
https://aclanthology.org//2000.iwpt-1.32/ | A Bidirectional Bottom-up Parser for TAG | [
"Syntactic Parsing",
"Syntactic Text Processing"
] | [
28,
15
] | |
SCOPUS_ID:85089306946 | A Bidirectional Iterative Algorithm for Nested Named Entity Recognition | Nested named entity recognition (NER) is a special case of structured prediction in which annotated sequences can be contained inside each other. It is a challenging and significant problem in natural language processing. In this paper, we propose a novel framework for nested named entity recognition tasks. Our approac... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
SCOPUS_ID:85030155599 | A Bidirectional LSTM Approach with Word Embeddings for Sentence Boundary Detection | Recovering sentence boundaries from speech and its transcripts is essential for readability and downstream speech and language processing tasks. In this paper, we propose to use deep recurrent neural network to detect sentence boundaries in broadcast news by modeling rich prosodic and lexical features extracted at each... | [
"Language Models",
"Semantic Text Processing",
"Speech & Audio in NLP",
"Representation Learning",
"Multimodality"
] | [
52,
72,
70,
12,
74
] |
http://arxiv.org/abs/2008.13339v3 | A Bidirectional Tree Tagging Scheme for Joint Medical Relation Extraction | Joint medical relation extraction refers to extracting triples, composed of entities and relations, from the medical text with a single model. One of the solutions is to convert this task into a sequential tagging task. However, in the existing works, the methods of representing and tagging the triples in a linear way ... | [
"Tagging",
"Information Extraction & Text Mining",
"Syntactic Text Processing",
"Relation Extraction"
] | [
63,
3,
15,
75
] |
SCOPUS_ID:84920627406 | A Bidirectional View of Executive Function and Social Interaction | In this chapter, we explore the idea that the relation between social interaction and executive functions might be best characterized as bi-directionaldirectional. That is, that while developing executive function abilities almost definitely have considerable impact on emerging social understanding in young children, s... | [
"Stylistic Analysis",
"Sentiment Analysis"
] | [
67,
78
] |
SCOPUS_ID:85115262248 | A Big Data Approach for Healthcare Analysis During Covid-19 | In the present times, with the massive growth of the Internet, unbelievably enormous measures of data are in our reach. Although our lives have been changed by prepared access to boundless information, still we need to explore the use of technology in various thrust areas. In this paper, we have analyzed and classify t... | [
"Text Classification",
"Ethical NLP",
"Responsible & Trustworthy NLP",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
17,
4,
24,
3
] |
SCOPUS_ID:85124279426 | A Big Data Experiment to Evaluate the Effectiveness of Traditional Machine Learning Techniques Against LSTM Neural Networks in the Hotels Clients Opinion Mining | Context: Nowadays, client reviews on social networks can be a great source of knowledge extraction for strategic marketing planning. In the tourism area, opinions given by hotel clients in tourism social networks can drive improvements in service. In this context, traditional text mining techniques and new deep learnin... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Opinion Mining",
"Sentiment Analysis",
"Text Classification",
"Information Extraction & Text Mining"
] | [
52,
72,
24,
49,
78,
36,
3
] |
SCOPUS_ID:85067982465 | A Big Data Processing Framework for Polarity Detection in Social Network Data | Big Data refers to the extremely big datasets that are produced from different areas which exhibits certain trends and associations. Major areas of big data include medical data, sensor data, social networks such as facebook, twitter, youtube etc. Among this, social networks produce large amount of data per millisecond... | [
"Polarity Analysis",
"Sentiment Analysis"
] | [
33,
78
] |
SCOPUS_ID:85030527435 | A Big Data architecture for knowledge discovery in PubMed articles | The need of smart information retrieval systems is in contrast with the difficulties to deal with huge amount of data. In this paper we present a Big Data Analytics architecture used to implement a semantic similarity search tool for natural language texts in biomedical domain. The implemented methodology is based on W... | [
"Semantic Text Processing",
"Semantic Similarity",
"Representation Learning"
] | [
72,
53,
12
] |
SCOPUS_ID:85042535268 | A Big-Data Approach to Understanding the Thematic Landscape of the Field of Business Ethics, 1982–2016 | This study focuses on examining the thematic landscape of the history of scholarly publication in business ethics. We analyze the titles, abstracts, full texts, and citation information of all research papers published in the field’s leading journal, the Journal of Business Ethics, from its inaugural issue in February ... | [
"Responsible & Trustworthy NLP",
"Topic Modeling",
"Ethical NLP",
"Information Extraction & Text Mining"
] | [
4,
9,
17,
3
] |
SCOPUS_ID:85082115960 | A BigData approach for sentiment analysis of twitter data using Naive Bayes and SVM Algorithm | Data mining and sentiment analysis are two most versatile research areas in field of real time knowledge extraction. Real time twitter data analysis can plays very crucial role to observe the thinking and view point of people and users. Nowadays, social networking sites have become centric points to share your thoughts... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85090840643 | A Bigram-based Inference Model for Retrieving Abbreviated Phrases in Source Code | Expanding abbreviations in source code to their full meanings is very useful for software maintainers to comprehend the source code. The existing approaches, however, focus on expanding an abbreviation to a single word, i.e., unigram. They do not perform well when dealing with abbreviations of phrases that consist of m... | [
"Language Models",
"Programming Languages in NLP",
"Semantic Text Processing",
"Information Retrieval",
"Multimodality"
] | [
52,
55,
72,
24,
74
] |
SCOPUS_ID:85069954280 | A Bilingual Adversarial Autoencoder for Unsupervised Bilingual Lexicon Induction | Unsupervised bilingual lexicon induction aims to generate bilingual lexicons without any cross-lingual signals. Successfully solving this problem would benefit many downstream tasks, such as unsupervised machine translation and transfer learning. In this work, we propose an unsupervised framework, named bilingual adver... | [
"Language Models",
"Low-Resource NLP",
"Machine Translation",
"Semantic Text Processing",
"Robustness in NLP",
"Representation Learning",
"Text Generation",
"Responsible & Trustworthy NLP",
"Cross-Lingual Transfer",
"Multilinguality"
] | [
52,
80,
51,
72,
58,
12,
47,
4,
19,
0
] |
SCOPUS_ID:85111511541 | A Bilingual Comparison of Sentiment and Topics for a Product Event on Twitter | Social media enable companies to assess consumers’ opinions, complaints and needs. The systematic and data-driven analysis of social media to generate business value is summarized under the term Social Media Analytics which includes statistical, network-based and language-based approaches. We focus on textual data and ... | [
"Topic Modeling",
"Information Extraction & Text Mining",
"Sentiment Analysis",
"Multilinguality"
] | [
9,
3,
78,
0
] |
http://arxiv.org/abs/1911.03895v2 | A Bilingual Generative Transformer for Semantic Sentence Embedding | Semantic sentence embedding models encode natural language sentences into vectors, such that closeness in embedding space indicates closeness in the semantics between the sentences. Bilingual data offers a useful signal for learning such embeddings: properties shared by both sentences in a translation pair are likely s... | [
"Representation Learning",
"Language Models",
"Semantic Text Processing",
"Multilinguality"
] | [
12,
52,
72,
0
] |
https://aclanthology.org//W18-5027/ | A Bilingual Interactive Human Avatar Dialogue System | This demonstration paper presents a bilingual (Arabic-English) interactive human avatar dialogue system. The system is named TOIA (time-offset interaction application), as it simulates face-to-face conversations between humans using digital human avatars recorded in the past. TOIA is a conversational agent, similar to ... | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents",
"Multilinguality"
] | [
11,
38,
0
] |
SCOPUS_ID:85085711637 | A Bilingual Word Alignment Method of Chinese-English based on Recurrent Neural Network | Word alignment is an important step in statistical machine translation. Chinese-English bilingual language has a large difference in language characteristics, which may lead to some inconsistent results in word alignment. In this paper, a word alignment method based on recurrent neural network (RNN) is proposed. Firstl... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
SCOPUS_ID:0012402135 | A Bilingual lexical database for frame semantics | Frame semantics is a linguistic theory which is currently gaining ground. The creation of lexical entries for a large number of words presupposes the development of complex lexical acquisition techniques in order to identify the vocabulary for describing the elements of a 'frame'. In this paper, we show how a lexical-s... | [
"Linguistic Theories",
"Linguistics & Cognitive NLP",
"Multilinguality"
] | [
57,
48,
0
] |
http://arxiv.org/abs/2112.04888v1 | A Bilingual, OpenWorld Video Text Dataset and End-to-end Video Text Spotter with Transformer | Most existing video text spotting benchmarks focus on evaluating a single language and scenario with limited data. In this work, we introduce a large-scale, Bilingual, Open World Video text benchmark dataset(BOVText). There are four features for BOVText. Firstly, we provide 2,000+ videos with more than 1,750,000+ frame... | [
"Multilinguality",
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Multimodality"
] | [
0,
20,
52,
72,
74
] |
http://arxiv.org/abs/cs/0407046v1 | A Bimachine Compiler for Ranked Tagging Rules | This paper describes a novel method of compiling ranked tagging rules into a deterministic finite-state device called a bimachine. The rules are formulated in the framework of regular rewrite operations and allow unrestricted regular expressions in both left and right rule contexts. The compiler is illustrated by an ap... | [
"Tagging",
"Syntactic Text Processing"
] | [
63,
15
] |
SCOPUS_ID:85010303443 | A Binomial Heap Extractor for Automatic Keyword Extraction | Automatic Extraction of Keywords using Frequent Itemsets (AEKFI) is a new technique for keyword extraction which integrates adjacency of location of words within the document to automatically select the most discriminative words without using a corpus. This paper introduces a novel Binomial Heap Approach based AEKFI fo... | [
"Term Extraction",
"Information Extraction & Text Mining"
] | [
1,
3
] |
SCOPUS_ID:85088740670 | A Bioinspired Algorithm for Improving the Effectiveness of Knowledge Processing | The paper deals with an approach to improve the effectiveness of knowledge processing in terms of large dimensions. The authors suggest the model of classification of the information resources to be used as a preprocessing stage for their further integration. The amount of information produced, transferred and processe... | [
"Semantic Text Processing",
"Text Classification",
"Semantic Similarity",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
72,
36,
53,
24,
3
] |
SCOPUS_ID:85125183644 | A Biological Test Questions Naming Entity Recognition Method for Fusion Triggers | Training a neural model for named entity recognition (NER) in a new field often requires additional human annotations (for example, a large number of tagged instances), which are often expensive and time-consuming to collect. Therefore, one of the key research problems is how to obtain the supervision effect in an econ... | [
"Explainability & Interpretability in NLP",
"Named Entity Recognition",
"Information Extraction & Text Mining",
"Responsible & Trustworthy NLP"
] | [
81,
34,
3,
4
] |
SCOPUS_ID:85117803982 | A Biologically Inspired Computational Model of Time Perception | Time perception-how humans and animals perceive the passage of time-forms the basis for important cognitive skills, such as decision making, planning, and communication. In this work, we propose a framework for examining the mechanisms responsible for time perception. We first model neural time perception as a combinat... | [
"Cognitive Modeling",
"Linguistics & Cognitive NLP"
] | [
2,
48
] |
SCOPUS_ID:84903524955 | A Biologically Plausible SOM Representation of the Orthographic Form of 50,000 French Words | Recently, an important aspect of human visual word recognition has been characterized. The letter position is encoded in our brain using an explicit representation of order based on letter pairs: the open-bigram coding [15]. We hypothesize that spelling has evolved in order to minimize reading errors. Therefore, word r... | [
"Semantic Text Processing",
"Representation Learning"
] | [
72,
12
] |
http://arxiv.org/abs/1705.05437v1 | A Biomedical Information Extraction Primer for NLP Researchers | Biomedical Information Extraction is an exciting field at the crossroads of Natural Language Processing, Biology and Medicine. It encompasses a variety of different tasks that require application of state-of-the-art NLP techniques, such as NER and Relation Extraction. This paper provides an overview of the problems in ... | [
"Information Extraction & Text Mining"
] | [
3
] |
SCOPUS_ID:85149702077 | A Biomedical Named Entity Recognition Framework with Multi-granularity Prompt Tuning | Deep Learning based Biomedical named entity recognition (BioNER) requires a large number of annotated samples, but annotated medical data is very scarce. To address this challenge, this paper proposes Prompt-BioNER, a BioNER framework using prompt tuning. Specifically, the framework is based on multi-granularity prompt... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Named Entity Recognition",
"Responsible & Trustworthy NLP"
] | [
52,
80,
72,
3,
34,
4
] |
SCOPUS_ID:85124722182 | A Bisociated Research Paper Recommendation Model using BiSOLinkers | In the current days of information overload, it is nearly impossible to obtain a form of relevant knowledge from massive information repositories without using information retrieval and filtering tools. The academic field daily receives lots of research articles, thus making it virtually impossible for researchers to t... | [
"Topic Modeling",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
9,
24,
3
] |
http://arxiv.org/abs/cs/0108005v1 | A Bit of Progress in Language Modeling | In the past several years, a number of different language modeling improvements over simple trigram models have been found, including caching, higher-order n-grams, skipping, interpolated Kneser-Ney smoothing, and clustering. We present explorations of variations on, or of the limits of, each of these techniques, inclu... | [
"Language Models",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Text Clustering"
] | [
52,
72,
3,
29
] |
SCOPUS_ID:85103858112 | A Block-Level RNN Model for Resume Block Classification | Resume block classification is the most significant step in resume information extraction. However, the existing algorithms applied to resume block classification are all the general text classification algorithms, which failed to consider the contextual order of each block within a resume. In order to improve the perf... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:85125704976 | A Blockchain-Based Consent Mechanism for Access to Fitness Data in the Healthcare Context | Wearable fitness devices are widely used to track an individual's health and physical activities to improve the quality of health services. These devices sense a considerable amount of sensitive data processed by a centralized third party. While many researchers have thoroughly evaluated privacy issues surrounding wear... | [
"Responsible & Trustworthy NLP",
"Ethical NLP",
"Linguistics & Cognitive NLP",
"Linguistic Theories"
] | [
4,
17,
48,
57
] |
SCOPUS_ID:85123370866 | A Blockchain-Based Sentiment Analysis Framework for Reliable Feedback System | In many institutions, feedback collection is either carried out manually or in a generic centralized manner, both of which are prone to manipulation. To provide a legitimate and practical feedback system is still being explored in the area of industry and information security. With an increase in demand for user feedba... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85115667323 | A Blockchain-Based Verification System for Academic Certificates | Millions of students complete their education each year and go on to do higher studies or a corporate job. In this case student credentials are verified through a lengthy document verification process. This results in significant overhead as documents are transferred between institutions for verification. There is a ne... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:84983372464 | A Bloom filter based semi-index on q-grams | We present a simple q-gram based semi-index, which allows to look for a pattern typically only in a small fraction of text blocks. Several space-time tradeoffs are presented. Experiments on Pizza & Chili datasets show that our solution is up to three orders of magnitude faster than the Claude et al. (Journal of Discret... | [
"Indexing",
"Information Retrieval"
] | [
69,
24
] |
SCOPUS_ID:85139264329 | A Blueprint for Integrating Task-Oriented Conversational Agents in Education | Over the past few years, there has been an increase in the use of chatbots for educational purposes. Nevertheless, the chatbot technologies and architectures that are often applied to educational contexts are not necessarily designed for such contexts. While general-purpose chatbot technologies can be used in education... | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
11,
38
] |
SCOPUS_ID:85144603130 | A Bona Fide Turing Test | The constantly rising demand for human-like conversational agents and the accelerated development of natural language processing technology raise expectations for a breakthrough in intelligent machine research and development. However, measuring intelligence is impossible without a proper test. Alan Turing proposed a t... | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
11,
38
] |
SCOPUS_ID:85044056296 | A Bootstrap Method for Automatic Rule Acquisition on Emotion Cause Extraction | Emotion cause extraction is one of the promising research topics in sentiment analysis, but has not been well-investigated so far. This task enables us to obtain useful information for sentiment classification and possibly to gain further insights about human emotion as well. This paper proposes a bootstrapping techniq... | [
"Emotion Analysis",
"Sentiment Analysis",
"Information Extraction & Text Mining"
] | [
61,
78,
3
] |
SCOPUS_ID:85128343312 | A Bootstrap Training Approach for Language Model Classifiers | In this paper, we present a bootstrap training approach for language model (LM) classifiers. Training class dependent LM and running them in parallel, LM can serve as classifiers with any kind of symbol sequence, e.g., word or phoneme sequences for tasks like topic spotting or language identification (LID). Irrespectiv... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
24,
3
] |
SCOPUS_ID:85138352694 | A Bootstrapped Chinese Biomedical Named Entity Recognition Model Incorporating Lexicons | Biomedical named entity recognition (BioNER) is a sub-task of named entity recognition, aiming at recognizing named entities in medical text to boost the knowledge discovery. In this paper, we propose a bootstrapped model incorporating lexicons, which takes advantage of pretrained language model, semi-supervised learni... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Named Entity Recognition",
"Responsible & Trustworthy NLP"
] | [
52,
80,
72,
3,
34,
4
] |
http://arxiv.org/abs/2008.04276v1 | A Bootstrapped Model to Detect Abuse and Intent in White Supremacist Corpora | Intelligence analysts face a difficult problem: distinguishing extremist rhetoric from potential extremist violence. Many are content to express abuse against some target group, but only a few indicate a willingness to engage in violence. We address this problem by building a predictive model for intent, bootstrapping ... | [
"Intent Recognition",
"Sentiment Analysis"
] | [
79,
78
] |
https://aclanthology.org//2000.iwpt-1.5/ | A Bootstrapping Approach to Parser Development | This paper presents a robust parsing system for unrestricted Basque texts. It analyzes a sentence in two stages: a unification-based parser builds basic syntactic units such as NPs, PPs, and sentential complements, while a finite-state parser performs syntactic disambiguation and filtering of the results. The system ha... | [
"Text Classification",
"Syntactic Text Processing",
"Syntactic Parsing",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
15,
28,
24,
3
] |
SCOPUS_ID:85067254364 | A Bootstrapping Approach with CRF and Deep Learning Models for Improving the Biomedical Named Entity Recognition in Multi-Domains | Biomedical named entity recognition (biomedical NER) is a core component to build biomedical text processing systems, such as biomedical information retrieval and question answering systems. Recently, many studies based on machine learning have been developed for a biomedical NER. The machine learning-based approaches ... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
SCOPUS_ID:85049099038 | A Bootstrapping-based Method to Automatically Identify Data-usage Statements in Publications | Purpose: Our study proposes a bootstrapping-based method to automatically extract data-usage statements from academic texts. Design/methodology/approach: The method for data-usage statements extraction starts with seed entities and iteratively learns patterns and data-usage statements from unlabeled text. In each itera... | [
"Information Extraction & Text Mining"
] | [
3
] |
SCOPUS_ID:84944930145 | A Borda count for collective sentiment analysis | Sentiment analysis assigns a positive, negative or neutral polarity to an item or entity, extracting and aggregating individual opinions from their textual expressions by means of natural language processing tools. In this paper we observe that current sentiment analysis techniques are satisfactory in case there is a s... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85079725811 | A Bot and a Smile: Interpersonal Impressions of Chatbots and Humans Using Emoji in Computer-mediated Communication | Artificially intelligent (AI) agents increasingly occupy roles once served by humans in computer-mediated communication (CMC). Technological affordances like emoji give interactants (humans or bots) the ability to partially overcome the limited nonverbal information in CMC. However, despite the growth of chatbots as co... | [
"Natural Language Interfaces",
"Visual Data in NLP",
"Multimodality",
"Dialogue Systems & Conversational Agents"
] | [
11,
20,
74,
38
] |
SCOPUS_ID:85103442629 | A Bottom-Up Approach for Moroccan Legal Ontology Learning from Arabic Texts | Ontologies constitute an exciting model for representing a domain of interest, since they enable information-sharing and reuse. Existing inference machines can also use them to reason about various contexts. However, ontology construction is a time-consuming and challenging task. The ontology learning field answers thi... | [
"Knowledge Representation",
"Semantic Text Processing"
] | [
18,
72
] |
SCOPUS_ID:85128443098 | A Bottom-Up DAG Structure Extraction Model for Math Word Problems | Research on automatically solving mathematical word problems (MWP) has a long history. Most recent works adopt the Seq2Seq approach to predict the result equations as a sequence of quantities and operators. Although result equations can be written as a sequence, it is essentially a structure. More precisely, it is a Di... | [
"Reasoning",
"Numerical Reasoning",
"Information Extraction & Text Mining"
] | [
8,
5,
3
] |
https://aclanthology.org//W12-1628/ | A Bottom-Up Exploration of the Dimensions of Dialog State in Spoken Interaction | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
11,
38
] | |
SCOPUS_ID:85097203273 | A Boundary Assembling Method for Nested Biomedical Named Entity Recognition | Biomedical named entity recognition (BNER) is an important task in biomedical natural language processing, in which neologisms (new terms, words) are coined constantly. Most of the existing work can only identify biomedical named entities with flattened structures and ignore nested biomedical named entities and discont... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
SCOPUS_ID:85111245497 | A Boundary Determined Neural Model For Relation Extraction | Existing models extract entity relations only after two entity spans have been precisely extracted that influenced the performance of relation extraction. Compared with recognizing entity spans, because the boundary has a small granularity and a less ambiguity, it can be detected precisely and incorporated to learn bet... | [
"Relation Extraction",
"Information Extraction & Text Mining"
] | [
75,
3
] |
SCOPUS_ID:85138815713 | A Boundary Regression Model for Nested Named Entity Recognition | Recognizing named entities (NEs) is commonly treated as a classification problem, and a class tag for a word or an NE candidate in a sentence is predicted. In recent neural network developments, deep structures that map categorized features into continuous representations have been adopted. Using this approach, a dense... | [
"Named Entity Recognition",
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
34,
24,
36,
3
] |
SCOPUS_ID:85135375255 | A Bounded Transition Hidden Markov Model for Continuous Speech Recognition | An HMM for phonetic transcription is presented. The inter-state transitions are bounded around phone boundaries, which are estimated from the observation sequence by statistical phone boundary detectors. The detection is done using the ratio of two probabilities, a probability that the observation sequence in a window ... | [
"Speech & Audio in NLP",
"Syntactic Text Processing",
"Text Generation",
"Phonetics",
"Speech Recognition",
"Multimodality"
] | [
70,
15,
47,
64,
10,
74
] |
SCOPUS_ID:85057412305 | A Bounding Box Approach for Performing Dynamic Optical Character Recognition in MATLAB | OCR is used to recognize written or optical generated text by the computer. Machine learning and artificial intelligence are relying frequently on such automation process with high accuracy. This paper present setting of the threshold value is once for whole bounding box algorithm rather than the random threshold value... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:85080112548 | A Bourdieusian analysis of the multilingualism in a poverty-stricken ethnic minority area: can linguistic capital be transferred to economic capital? | Indigenous languages in poverty-stricken areas are often threatened by competition from the majority languages driving economic progress. Within the framework of the economics of linguistic exchanges, this paper discusses the possibility of transferring linguistic capital into economic capital, and the revaluation of m... | [
"Multilinguality"
] | [
0
] |
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