id stringlengths 20 52 | title stringlengths 3 459 | abstract stringlengths 0 12.3k | classification_labels list | numerical_classification_labels list |
|---|---|---|---|---|
SCOPUS_ID:85144180199 | A DCRC Model for Text Classification | Traditional text classification models have some drawbacks, such as the inability of the model to focus on important parts of the text contextual information in text processing. To solve this problem, we fuse the long and short-term memory network BiGRU with a convolutional neural network to receive text sequence input... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
24,
3
] |
SCOPUS_ID:84880647287 | A DEVS-based M&S method for large-scale multi-agent systems | ABMS offers various simulation systems, tools, toolkits and languages for multi-agent system research. However, there is a need for a M&S method for L-systems(large-scale multi-agent systems) research as current ABMS method has some degree of difficulty in dealing with the scale and heterogeneity issues of L-systems. T... | [
"Cognitive Modeling",
"Linguistics & Cognitive NLP",
"Linguistic Theories"
] | [
2,
48,
57
] |
SCOPUS_ID:85083756664 | A DGA Domain Name Detection Method Based on Deep Learning Models with Mixed Word Embedding | DGA domain name detection plays a key role in preventing botnet attacks. It is practically significant in generating threat intelligence, blocking botnet command and control traffic, and maintaining cyber security. In recent years, DGA domain name detection algorithms have made great progress, from the methods using ma... | [
"Semantic Text Processing",
"Text Classification",
"Representation Learning",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
72,
36,
12,
24,
3
] |
SCOPUS_ID:85141474359 | A DIACHRONIC DESCRIPTION OF THE RHETORIC OF THE 18<sup>TH</sup> CENTURY | The article outlines the main ideas of a research project aimed to create scholarly papers and data-bases reflecting the formation of the Russian rhetorical tradition. Up to now, literary norms of the Russian language have been studied either in relation to syntactic structures severed from the living practice of versi... | [
"Speech & Audio in NLP",
"Multimodality"
] | [
70,
74
] |
SCOPUS_ID:85125558731 | A DIAGNOSTIC STUDY OF VISUAL QUESTION ANSWERING WITH ANALOGICAL REASONING | The deep learning community has made rapid progress in low-level visual perception tasks such as object localization, detection and segmentation. However, for tasks such as Visual Question Answering (VQA) and visual language grounding that require high-level reasoning abilities, huge gaps still exist between artificial... | [
"Visual Data in NLP",
"Question Answering",
"Natural Language Interfaces",
"Reasoning",
"Multimodality"
] | [
20,
27,
11,
8,
74
] |
SCOPUS_ID:85071385638 | A DIK-based question-answering architecture with multi-sources data for Medical Self-Service (KG) | Medical data is amplified in terms of speed and capacity in a very fast way, which creates obstacles for users to quickly access valid information. We present a DIK-based Question-Answering Architecture for Medical Self-Service. In addition, we propose a model based on the attention mechanism to extract high-quality me... | [
"Semantic Text Processing",
"Structured Data in NLP",
"Question Answering",
"Knowledge Representation",
"Natural Language Interfaces",
"Multimodality"
] | [
72,
50,
27,
18,
11,
74
] |
SCOPUS_ID:84911586165 | A DINOSAUR CAPER: PSYCHOLINGUISTICS PAST, PRESENT, AND FUTURE | [
"Psycholinguistics",
"Linguistics & Cognitive NLP"
] | [
77,
48
] | |
SCOPUS_ID:85124882915 | A DISCOURSE ANALYSIS OF CAREER EXPERIENCES OF WOMEN IN THE DEVELOPING COUNTRY | The efforts to reduce the widened effects of structural inequality for women in South Africa have resulted in varied experiences (Burns, Tomita, & Lund, 2017). The study problematised the unresearched and not well articulated social construct within the career experiences of women working in a telecommunication company... | [
"Discourse & Pragmatics",
"Semantic Text Processing"
] | [
71,
72
] |
SCOPUS_ID:85009081336 | A DISCRIMINATIVE TRAINING PROCEDURE BASED ON LANGUAGE MODEL AND DICTIONARY FOR LVCSR | In today's HMM-based speech recognition systems, the parameters are most commonly estimated according to the Maximum Likelihood criterion. Because of limited training data, however, discriminative objectives provide better parameter estimates with respect to the Maximum A-Posteriori decision used for decoding. The ques... | [
"Language Models",
"Semantic Text Processing",
"Speech & Audio in NLP",
"Text Generation",
"Speech Recognition",
"Multimodality"
] | [
52,
72,
70,
47,
10,
74
] |
SCOPUS_ID:85102077013 | A DNA Cryptographic Solution for Secured Image and Text Encryption | In recent days, DNA cryptography is gaining more popularity for providing better security to image and text data. This paper presents a DNA based cryptographic solution for image and textual information. Image encryption involves scrambling at pixel and bit levels based on hyperchaotic sequences. Both image and text en... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:80052423628 | A DNA assembly model of sentence generation | Recent results of corpus-based linguistics demonstrate that context-appropriate sentences can be generated by a stochastic constraint satisfaction process. Exploiting the similarity of constraint satisfaction and DNA self-assembly, we explore a DNA assembly model of sentence generation. The words and phrases in a langu... | [
"Language Models",
"Semantic Text Processing",
"Text Generation"
] | [
52,
72,
47
] |
SCOPUS_ID:85145877569 | A DNN-Based Accurate Masking Using Significant Feature Sets | Monaural speech separation has remained a very challenging problem for a longtime which can be addressed using a supervised learning approach that uses features of the noisy input to predict an accurate time-frequency mask. Effective acoustic phonetic features can help in the accurate mask prediction at low Signal-to-N... | [
"Language Models",
"Semantic Text Processing",
"Speech & Audio in NLP",
"Syntactic Text Processing",
"Phonetics",
"Multimodality"
] | [
52,
72,
70,
15,
64,
74
] |
SCOPUS_ID:85062795116 | A DNN-Based Framework for Converting Sign Language to Mandarin-Tibetan Cross-Lingual Emotional Speech | We proposed a method for converting sign-language to Mandarin-Tibetan bi-lingual emotional speech using a deep neural network (DNN)-based framework in the paper. We used a support vector machine (SVM) to classify the categories of sign-language by the sign-language features extracted from sign-language image with a tra... | [
"Multilinguality",
"Visual Data in NLP",
"Information Extraction & Text Mining",
"Information Retrieval",
"Speech & Audio in NLP",
"Cross-Lingual Transfer",
"Text Classification",
"Multimodality"
] | [
0,
20,
3,
24,
70,
19,
36,
74
] |
SCOPUS_ID:85098165215 | A DNN-HMM-DNN hybrid model for discovering word-like units from spoken captions and image regions | Discovering word-like units without textual transcriptions is an important step in low-resource speech technology. In this work, we demonstrate a model inspired by statistical machine translation and hidden Markov model/deep neural network (HMMDNN) hybrid systems. Our learning algorithm is capable of discovering the vi... | [
"Multilinguality",
"Visual Data in NLP",
"Low-Resource NLP",
"Machine Translation",
"Captioning",
"Speech & Audio in NLP",
"Text Generation",
"Responsible & Trustworthy NLP",
"Multimodality"
] | [
0,
20,
80,
51,
39,
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47,
4,
74
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SCOPUS_ID:67349252831 | A Danish phonetically annotated spontaneous speech corpus (DanPASS) | A corpus is described consisting of non-scripted monologues and dialogues, recorded by 27 speakers, comprising a total of 73,227 running words, corresponding to 9 h and 46 min of speech. The monologues were recorded as one-way communication with an unseen partner where the speaker performed three different tasks: (s)he... | [
"Speech & Audio in NLP",
"Syntactic Text Processing",
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents",
"Phonetics",
"Multimodality"
] | [
70,
15,
11,
38,
64,
74
] |
SCOPUS_ID:85149873292 | A Data Augmentation Method For English-Vietnamese Neural Machine Translation | The translation quality of machine translation systems depends on the parallel corpus used for training, in particular the quantity and quality of the corpus. However, building a high-quality and large-scale parallel corpus is complex and expensive, particularly for a specific domain parallel corpus. Therefore, data au... | [
"Multilinguality",
"Low-Resource NLP",
"Text Error Correction",
"Machine Translation",
"Syntactic Text Processing",
"Text Generation",
"Responsible & Trustworthy NLP"
] | [
0,
80,
26,
51,
15,
47,
4
] |
http://arxiv.org/abs/2110.09570v1 | A Data Bootstrapping Recipe for Low Resource Multilingual Relation Classification | Relation classification (sometimes called 'extraction') requires trustworthy datasets for fine-tuning large language models, as well as for evaluation. Data collection is challenging for Indian languages, because they are syntactically and morphologically diverse, as well as different from resource-rich languages like ... | [
"Multilinguality",
"Low-Resource NLP",
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Information Extraction & Text Mining",
"Text Classification",
"Responsible & Trustworthy NLP"
] | [
0,
80,
52,
72,
24,
3,
36,
4
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http://arxiv.org/abs/2205.03403v1 | A Data Cartography based MixUp for Pre-trained Language Models | MixUp is a data augmentation strategy where additional samples are generated during training by combining random pairs of training samples and their labels. However, selecting random pairs is not potentially an optimal choice. In this work, we propose TDMixUp, a novel MixUp strategy that leverages Training Dynamics and... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
http://arxiv.org/abs/1203.5084v1 | A Data Driven Approach to Query Expansion in Question Answering | Automated answering of natural language questions is an interesting and useful problem to solve. Question answering (QA) systems often perform information retrieval at an initial stage. Information retrieval (IR) performance, provided by engines such as Lucene, places a bound on overall system performance. For example,... | [
"Natural Language Interfaces",
"Question Answering",
"Information Retrieval"
] | [
11,
27,
24
] |
https://aclanthology.org//W06-3005/ | A Data Driven Approach to Relevancy Recognition for Contextual Question Answering | [
"Natural Language Interfaces",
"Question Answering"
] | [
11,
27
] | |
http://arxiv.org/abs/2002.05955v1 | A Data Efficient End-To-End Spoken Language Understanding Architecture | End-to-end architectures have been recently proposed for spoken language understanding (SLU) and semantic parsing. Based on a large amount of data, those models learn jointly acoustic and linguistic-sequential features. Such architectures give very good results in the context of domain, intent and slot detection, their... | [
"Responsible & Trustworthy NLP",
"Green & Sustainable NLP"
] | [
4,
68
] |
SCOPUS_ID:85138934037 | A Data Entry Optical Character Recognition Tool using Convolutional Neural Networks | Almost all institutions and organizations rely substantially on data to run their operations. Data is necessary for making informed decisions, adapting to change, and defining strategic objectives. Data administration has always relied on manual data entry. Manual input is used to entail transferring data from various ... | [
"Visual Data in NLP",
"Programming Languages in NLP",
"Multimodality"
] | [
20,
55,
74
] |
SCOPUS_ID:85099573410 | A Data Indexing Technique to Improve the Search Latency of and Queries for Large Scale Textual Documents | Boolean AND queries (BAQ) are one of the most important types of queries used in text searching. In this paper, a graph-based indexing technique is proposed to improve the search latency of BAQ. It shows how a graph structure represented using a hash table can reduce the number of intersections needed for the execution... | [
"Indexing",
"Structured Data in NLP",
"Information Retrieval",
"Multimodality"
] | [
69,
50,
24,
74
] |
SCOPUS_ID:85064530230 | A Data Preprocessing Method to Classify and Summarize Aspect-Based Opinions Using Deep Learning | Opinion summarization is based on aspect analyses of products, events or topics, which is a very interesting topic in natural language processing. Opinions are often expressed in various different ways in regards to objects. Therefore, it is important to express the characteristics of a product, event or topic in a fin... | [
"Semantic Text Processing",
"Information Retrieval",
"Summarization",
"Knowledge Representation",
"Text Generation",
"Sentiment Analysis",
"Text Classification",
"Information Extraction & Text Mining"
] | [
72,
24,
30,
18,
47,
78,
36,
3
] |
SCOPUS_ID:85032840925 | A Data Purpose Case Study of Privacy Policies | Privacy laws and international privacy standards require that companies collect only the data they have a stated purpose for, called collection limitation. Furthermore, these regimes prescribe that companies will not use data for purposes other than the purposes for which they were collected, called use limitation, exc... | [
"Ethical NLP",
"Responsible & Trustworthy NLP"
] | [
17,
4
] |
SCOPUS_ID:85090095497 | A Data Science Approach to Analysis of Tweets Based on Cyclone Fani | The advent of social media has contributed to faster as well as wider propagation of information and emotions of people. In the time of emergencies and natural disasters, social media becomes an important tool for communication, spreading of alerts and knowing the needs and feelings of people in crisis. In this paper, ... | [
"Sentiment Analysis"
] | [
78
] |
http://arxiv.org/abs/1911.10130v1 | A Data Set of Internet Claims and Comparison of their Sentiments with Credibility | In this modern era, communication has become faster and easier. This means fallacious information can spread as fast as reality. Considering the damage that fake news kindles on the psychology of people and the fact that such news proliferates faster than truth, we need to study the phenomenon that helps spread fake ne... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Ethical NLP",
"Sentiment Analysis",
"Reasoning",
"Fact & Claim Verification",
"Text Classification",
"Responsible & Trustworthy NLP"
] | [
3,
24,
17,
78,
8,
46,
36,
4
] |
https://aclanthology.org//2021.mtsummit-up.24/ | A Data-Centric Approach to Real-World Custom NMT for Arabic | In this presentation, we will present our approach to taking Custom NMT to the next level by building tailor-made NMT to fit the needs of businesses seeking to scale in the Arabic-speaking world. In close collaboration with customers in the MENA region and with a deep understanding of their data, we work on building a ... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
http://arxiv.org/abs/1606.06274v1 | A Data-Driven Approach for Semantic Role Labeling from Induced Grammar Structures in Language | Semantic roles play an important role in extracting knowledge from text. Current unsupervised approaches utilize features from grammar structures, to induce semantic roles. The dependence on these grammars, however, makes it difficult to adapt to noisy and new languages. In this paper we develop a data-driven approach ... | [
"Low-Resource NLP",
"Semantic Parsing",
"Semantic Text Processing",
"Responsible & Trustworthy NLP"
] | [
80,
40,
72,
4
] |
SCOPUS_ID:85147795187 | A Data-Driven Investigation of Noise-Adaptive Utterance Generation with Linguistic Modification | In noisy environments, speech can be hard to understand for humans. Spoken dialog systems can help to enhance the intelligibility of their output, either by modifying the speech synthesis (e.g., imitate Lombard speech) or by optimizing the language generation. We here focus on the second type of approach, by which an i... | [
"Paraphrasing",
"Speech & Audio in NLP",
"Text Generation",
"Multimodality"
] | [
32,
70,
47,
74
] |
SCOPUS_ID:85096424104 | A Data-Driven Method for Measuring the Negative Impact of Sentiment Towards China in the Context of COVID-19 | Social media is a valuable source of information that allows to study people opinions of many events that happen every day. Nowadays social networks are one of the most important communication methods that people use. Feelings towards nations can be measured today thanks to the advances in machine learning and big data... | [
"Information Extraction & Text Mining",
"Sentiment Analysis"
] | [
3,
78
] |
SCOPUS_ID:85030672673 | A Data-Driven Model of Tonal Chord Sequence Complexity | We present a compound language model of tonal chord sequences, and evaluate its capability to estimate perceived harmonic complexity. In order to build the compound model, we trained three different models: prediction by partial matching, a hidden Markov model and a deep recurrent neural network on a novel large datase... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:85128898546 | A Data-Driven Score Model to Assess Online News Articles in Event-Based Surveillance System | Online news sources are popular resources for learning about current health situations and developing event-based surveillance (EBS) systems. However, having access to diverse information originating from multiple sources can misinform stakeholders, eventually leading to false health risks. The existing literature cont... | [
"Information Extraction & Text Mining"
] | [
3
] |
SCOPUS_ID:85123624882 | A Data-Driven Semi-Automatic Framenet Development Methodology | FrameNet is a lexical semantic resource based on the linguistic theory of frame semantics. A number of framenet development strategies have been reported previously and all of them involve exploration of corpora and a fair amount of manual work. Despite previous efforts, there does not exist a well-thought-out automati... | [
"Linguistics & Cognitive NLP",
"Linguistic Theories"
] | [
48,
57
] |
http://arxiv.org/abs/2011.14084v2 | A Data-Driven Study of Commonsense Knowledge using the ConceptNet Knowledge Base | Acquiring commonsense knowledge and reasoning is recognized as an important frontier in achieving general Artificial Intelligence (AI). Recent research in the Natural Language Processing (NLP) community has demonstrated significant progress in this problem setting. Despite this progress, which is mainly on multiple-cho... | [
"Commonsense Reasoning",
"Knowledge Representation",
"Semantic Text Processing",
"Reasoning"
] | [
62,
18,
72,
8
] |
SCOPUS_ID:85134377701 | A Data-Efficient Method for One-Shot Text Classification | In this paper, we propose BiGBERT (Binary Grouping BERT), a data-efficient training method for one-shot text classification. With the idea of One-vs-Rest method, we designed an extensible output layer for BERT, which can increase the usability of the training data. To evaluate our approach, we conducted extensive exper... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
24,
3
] |
http://arxiv.org/abs/cmp-lg/9606024v1 | A Data-Oriented Approach to Semantic Interpretation | In Data-Oriented Parsing (DOP), an annotated language corpus is used as a stochastic grammar. The most probable analysis of a new input sentence is constructed by combining sub-analyses from the corpus in the most probable way. This approach has been succesfully used for syntactic analysis, using corpora with syntactic... | [
"Explainability & Interpretability in NLP",
"Syntactic Text Processing",
"Responsible & Trustworthy NLP"
] | [
81,
15,
4
] |
SCOPUS_ID:85125875546 | A Data-driven Affective Text Classification Analysis | Affective texts play a key role in sentiment classification/prediction and decision making. They are being increasingly used to form and/or share sentiments in financial, economic and/or political applications. However, the processing time is exponentially increased for large affective textual datasets. Moreover, casua... | [
"Visual Data in NLP",
"Information Retrieval",
"Multimodality",
"Sentiment Analysis",
"Emotion Analysis",
"Text Classification",
"Information Extraction & Text Mining"
] | [
20,
24,
74,
78,
61,
36,
3
] |
http://arxiv.org/abs/2005.12565v1 | A Data-driven Approach for Noise Reduction in Distantly Supervised Biomedical Relation Extraction | Fact triples are a common form of structured knowledge used within the biomedical domain. As the amount of unstructured scientific texts continues to grow, manual annotation of these texts for the task of relation extraction becomes increasingly expensive. Distant supervision offers a viable approach to combat this by ... | [
"Relation Extraction",
"Information Extraction & Text Mining"
] | [
75,
3
] |
SCOPUS_ID:85147955698 | A Data-driven Latent Semantic Analysis for Automatic Text Summarization using LDA Topic Modelling | With the advent and popularity of big data mining and huge text analysis in modern times, automated text summarization became prominent for extracting and retrieving important information from documents. This research investigates aspects of automatic text summarization from the perspectives of single and multiple docu... | [
"Summarization",
"Topic Modeling",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
9,
47,
3
] |
https://aclanthology.org//W13-4062/ | A Data-driven Model for Timing Feedback in a Map Task Dialogue System | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
11,
38
] | |
http://arxiv.org/abs/2006.16642v1 | A Data-driven Neural Network Architecture for Sentiment Analysis | The fabulous results of convolution neural networks in image-related tasks, attracted attention of text mining, sentiment analysis and other text analysis researchers. It is however difficult to find enough data for feeding such networks, optimize their parameters, and make the right design choices when constructing ne... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85116169703 | A Data-oriented Approach for Detecting offensive Language in Arabic Tweets | The growing popularity of social media (SM) platforms has made these platforms a crucial part of modern societies. Users from different cultures, backgrounds, demographics get aboard in an increasing manner to express their views, stances, and opinions on a varied range of topics. Since users on SM can easily hide thei... | [
"Text Classification",
"Ethical NLP",
"Responsible & Trustworthy NLP",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
17,
4,
24,
3
] |
SCOPUS_ID:85144203040 | A Data-to-Text Generation Model with Deduplicated Content Planning | Texts generated in data-to-text generation tasks often have repetitive parts. In order to get higher quality generated texts, we choose a data-to-text generation model with content planning, and add coverage mechanisms to both the content planning and text generation stages. In the content planning stage, a coverage me... | [
"Data-to-Text Generation",
"Semantic Text Processing",
"Text Generation",
"Representation Learning"
] | [
16,
72,
47,
12
] |
SCOPUS_ID:85115252591 | A Database and Visualization of the Similarity of Contemporary Lexicons | Lexical similarity data, quantifying the “proximity” of languages based on the similarity of their lexicons, has been increasingly used to estimate the cross-lingual reusability of language resources, for tasks such as bilingual lexicon induction or cross-lingual transfer. Existing similarity data, however, originates ... | [
"Cross-Lingual Transfer",
"Multilinguality"
] | [
19,
0
] |
https://aclanthology.org//2022.sigtyp-1.6/ | A Database for Modal Semantic Typology | This paper introduces a database for crosslinguistic modal semantics. The purpose of this database is to (1) enable ongoing consolidation of modal semantic typological knowledge into a repository according to uniform data standards and to (2) provide data for investigations in crosslinguistic modal semantic theory and ... | [
"Typology",
"Syntactic Text Processing",
"Multilinguality"
] | [
45,
15,
0
] |
SCOPUS_ID:84942247366 | A Database of On-Line Handwritten Mixed Objects Named 'Kondate' | This paper describes a database of on-line handwritten patterns mixed of text, figures, tables, maps, diagrams and so on. Now, pen-based and touch-based interfaces are spreading into people and their surfaces are getting large. People can write and draw mixed objects without paying attention on the difference of object... | [
"Structured Data in NLP",
"Multimodality"
] | [
50,
74
] |
SCOPUS_ID:85021624400 | A Database of Paradigmatic Semantic Relation Pairs for German Nouns, Verbs, and Adjectives | A new collection of semantically related word pairs in German is presented, which was compiled via human judgement experiments and comprises (i) a representative selection of target lexical units balanced for semantic category, polysemy, and corpus frequency, (ii) a set of humangenerated semantically related word pairs... | [
"Psycholinguistics",
"Linguistics & Cognitive NLP"
] | [
77,
48
] |
http://arxiv.org/abs/2003.04970v1 | A Dataset Independent Set of Baselines for Relation Prediction in Argument Mining | Argument Mining is the research area which aims at extracting argument components and predicting argumentative relations (i.e.,support and attack) from text. In particular, numerous approaches have been proposed in the literature to predict the relations holding between the arguments, and application-specific annotated... | [
"Argument Mining",
"Reasoning"
] | [
60,
8
] |
http://arxiv.org/abs/2205.04185v1 | A Dataset and BERT-based Models for Targeted Sentiment Analysis on Turkish Texts | Targeted Sentiment Analysis aims to extract sentiment towards a particular target from a given text. It is a field that is attracting attention due to the increasing accessibility of the Internet, which leads people to generate an enormous amount of data. Sentiment analysis, which in general requires annotated data for... | [
"Language Models",
"Semantic Text Processing",
"Sentiment Analysis"
] | [
52,
72,
78
] |
http://arxiv.org/abs/2106.02017v1 | A Dataset and Baselines for Multilingual Reply Suggestion | Reply suggestion models help users process emails and chats faster. Previous work only studies English reply suggestion. Instead, we present MRS, a multilingual reply suggestion dataset with ten languages. MRS can be used to compare two families of models: 1) retrieval models that select the reply from a fixed set and ... | [
"Information Retrieval",
"Multilinguality"
] | [
24,
0
] |
SCOPUS_ID:85101760993 | A Dataset and Baselines for Visual Question Answering on Art | Answering questions related to art pieces (paintings) is a difficult task, as it implies the understanding of not only the visual information that is shown in the picture, but also the contextual knowledge that is acquired through the study of the history of art. In this work, we introduce our first attempt towards bui... | [
"Visual Data in NLP",
"Natural Language Interfaces",
"Question Answering",
"Multimodality"
] | [
20,
11,
27,
74
] |
SCOPUS_ID:85147994474 | A Dataset for Analysis of Quality Code and Toxic Comments | Software development has an important human aspect, so it is known that the feelings of developers have a significant impact on software development and could affect the quality, productivity and performance of developers. In this study, we have begun the process of finding, understanding and relating these affects to ... | [
"Sentiment Analysis"
] | [
78
] |
http://arxiv.org/abs/2201.12888v1 | A Dataset for Medical Instructional Video Classification and Question Answering | This paper introduces a new challenge and datasets to foster research toward designing systems that can understand medical videos and provide visual answers to natural language questions. We believe medical videos may provide the best possible answers to many first aids, medical emergency, and medical education questio... | [
"Visual Data in NLP",
"Information Extraction & Text Mining",
"Information Retrieval",
"Question Answering",
"Natural Language Interfaces",
"Text Classification",
"Multimodality"
] | [
20,
3,
24,
27,
11,
36,
74
] |
http://arxiv.org/abs/2205.02289v1 | A Dataset for N-ary Relation Extraction of Drug Combinations | Combination therapies have become the standard of care for diseases such as cancer, tuberculosis, malaria and HIV. However, the combinatorial set of available multi-drug treatments creates a challenge in identifying effective combination therapies available in a situation. To assist medical professionals in identifying... | [
"Relation Extraction",
"Information Extraction & Text Mining"
] | [
75,
3
] |
http://arxiv.org/abs/2203.15568v1 | A Dataset for Speech Emotion Recognition in Greek Theatrical Plays | Machine learning methodologies can be adopted in cultural applications and propose new ways to distribute or even present the cultural content to the public. For instance, speech analytics can be adopted to automatically generate subtitles in theatrical plays, in order to (among other purposes) help people with hearing... | [
"Emotion Analysis",
"Multimodality",
"Speech & Audio in NLP",
"Sentiment Analysis"
] | [
61,
74,
70,
78
] |
http://arxiv.org/abs/2005.05257v3 | A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering | Legislation can be viewed as a body of prescriptive rules expressed in natural language. The application of legislation to facts of a case we refer to as statutory reasoning, where those facts are also expressed in natural language. Computational statutory reasoning is distinct from most existing work in machine readin... | [
"Natural Language Interfaces",
"Reasoning",
"Question Answering",
"Textual Inference"
] | [
11,
8,
27,
22
] |
SCOPUS_ID:85146262806 | A Dataset for Term Extraction in Hindi | Automatic Term Extraction (ATE) is one of the core problems in natural language processing and forms a key component of text mining pipelines of domain specific corpora. Complex low-level tasks such as machine translation and summarization for domain specific texts necessitate the use of term extraction systems. Howeve... | [
"Low-Resource NLP",
"Responsible & Trustworthy NLP",
"Term Extraction",
"Information Extraction & Text Mining"
] | [
80,
4,
1,
3
] |
SCOPUS_ID:85079244203 | A Dataset for the Sentiment Analysis of Indo-Pak Music Industry | The continuous increase in data creates a need, that data be analysed and useful hidden patterns be found and explored. If the data is readily available, it can easily be analysed. But most of the time it needs to be dug. Substantial increase in the use of social media and online services can be witnessed nowadays. Peo... | [
"Speech & Audio in NLP",
"Sentiment Analysis",
"Multimodality"
] | [
70,
78,
74
] |
http://arxiv.org/abs/2003.13016v1 | A Dataset of German Legal Documents for Named Entity Recognition | We describe a dataset developed for Named Entity Recognition in German federal court decisions. It consists of approx. 67,000 sentences with over 2 million tokens. The resource contains 54,000 manually annotated entities, mapped to 19 fine-grained semantic classes: person, judge, lawyer, country, city, street, landscap... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
https://aclanthology.org//W18-1105/ | A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection | Hate speech detection in social media texts is an important Natural language Processing task, which has several crucial applications like sentiment analysis, investigating cyberbullying and examining socio-political controversies. While relevant research has been done independently on code-mixed social media texts and ... | [
"Responsible & Trustworthy NLP",
"Ethical NLP",
"Sentiment Analysis"
] | [
4,
17,
78
] |
https://aclanthology.org//2022.nlp4pi-1.5/ | A Dataset of Sustainable Diet Arguments on Twitter | Sustainable development requires a significant change in our dietary habits. Argument mining can help achieve this goal by both affecting and helping understand people’s behavior. We design an annotation scheme for argument mining from online discourse around sustainable diets, including novel evidence types specific t... | [
"Green & Sustainable NLP",
"Ethical NLP",
"Argument Mining",
"Reasoning",
"Responsible & Trustworthy NLP"
] | [
68,
17,
60,
8,
4
] |
SCOPUS_ID:85144479030 | A Day at Work (with Text) | Text mining, information extraction, and opinion analysis are rich research areas, which have gained greatly in accessibility over the last 10–15 years. Today, there are many powerful tools and frameworks available, meaning that anybody with sufficient interest and time can integrate computational methods of working wi... | [
"Information Extraction & Text Mining"
] | [
3
] |
http://arxiv.org/abs/2210.00105v1 | A Decade of Knowledge Graphs in Natural Language Processing: A Survey | In pace with developments in the research field of artificial intelligence, knowledge graphs (KGs) have attracted a surge of interest from both academia and industry. As a representation of semantic relations between entities, KGs have proven to be particularly relevant for natural language processing (NLP), experienci... | [
"Knowledge Representation",
"Structured Data in NLP",
"Semantic Text Processing",
"Multimodality"
] | [
18,
50,
72,
74
] |
SCOPUS_ID:85133032625 | A Decade of Legal Argumentation Mining: Datasets and Approaches | The growing research field of argumentation mining (AM) in the past ten years has made it a popular topic in Natural Language Processing. However, there are still limited studies focusing on AM in the context of legal text (Legal AM), despite the fact that legal text analysis more generally has received much attention ... | [
"Argument Mining",
"Reasoning"
] | [
60,
8
] |
SCOPUS_ID:85105436117 | A Decade of Sentic Computing: Topic Modeling and Bibliometric Analysis | Research on sentic computing has received intensive attention in recent years, as indicated by the increased availability of academic literature. However, despite the growth in literature and researchers’ interests, there are no reviews on this topic. This study comprehensively explores the current research progress an... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85084948113 | A Decade on Script Identification from Natural Images/Videos: A Review | Text present in an image provides high level straight forward information about the image/ video in which it is present. Nowadays, analysis of script identification either in the natural image or document image facilitates benefits to the number of important applications. Automatic script identification is a highly cha... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:85079893139 | A Decentralized Context-aware Cross-domain Authorization Scheme for Pervasive Computing | Context-aware access control is one of the most frequently used methods for making authorization decisions in pervasive computing environments. To the best of our knowledge, most previous relevant researches resorted to centralized schemes to preserve all the contextual information. As a result, they neglected actual c... | [
"Linguistics & Cognitive NLP",
"Linguistic Theories"
] | [
48,
57
] |
SCOPUS_ID:85112856591 | A Decision Support System for Project Risk Management based on Ontology Learning | Project Risk Management (PRM) is one of the main concerns of project management executives and professionals. Although PRM frameworks and risk models are mature enough to provide a systematic approach for managing risks, these practices remain ad hoc and non-standardized. In addition, there is no significant work shift... | [
"Knowledge Representation",
"Semantic Text Processing"
] | [
18,
72
] |
SCOPUS_ID:85087158957 | A Decision Tree Based Supervised Program Interpretation Technique for Gurmukhi Language | Deciphering the right context of the given word is one of the main challenges in Natural Language Processing. The study of Word Sense Disambiguation helps in deciphering the right context of the given word in use. Decision Tree is a methodology discussed under the supervised techniques used in WSD. Gurmukhi is one of t... | [
"Programming Languages in NLP",
"Semantic Text Processing",
"Word Sense Disambiguation",
"Explainability & Interpretability in NLP",
"Responsible & Trustworthy NLP",
"Multimodality"
] | [
55,
72,
65,
81,
4,
74
] |
SCOPUS_ID:85149967615 | A Decision-Level Approach to Multimodal Sentiment Analysis | There has been near exponential increase in the use of images and video on various Social Media platforms in the last few years, in place of or in addition to the use of plain text. Automated sentiment analysis, at its core, is the capturing of human emotion by machine - the addition of image and video to social media ... | [
"Visual Data in NLP",
"Captioning",
"Text Generation",
"Sentiment Analysis",
"Multimodality"
] | [
20,
39,
47,
78,
74
] |
SCOPUS_ID:85079810027 | A Decision-Making Model Under Probabilistic Linguistic Circumstances with Unknown Criteria Weights for Online Customer Reviews | Online customer reviews (OCRs) provide much information about products or service, but the mass of information increases the difficulty for customers to make decisions. Thus, we establish a multi-criteria decision making (MCDM) model to evaluate products or service. To analyze OCRs, the sentiment analysis (SA) is intro... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85146786510 | A Decision-Support System to Analyse Customer Satisfaction Applied to a Tourism Transport Service | Due to the perishable nature of tourist products, which impacts supply and demand, the possibility of analysing the relationship between customers’ satisfaction and service quality can contribute to increased revenues. Machine learning techniques allow the analysis of how these services can be improved or developed and... | [
"Sentiment Analysis"
] | [
78
] |
http://arxiv.org/abs/1606.01933v2 | A Decomposable Attention Model for Natural Language Inference | We propose a simple neural architecture for natural language inference. Our approach uses attention to decompose the problem into subproblems that can be solved separately, thus making it trivially parallelizable. On the Stanford Natural Language Inference (SNLI) dataset, we obtain state-of-the-art results with almost ... | [
"Reasoning",
"Textual Inference"
] | [
8,
22
] |
http://arxiv.org/abs/cmp-lg/9404009v3 | A Deductive Account of Quantification in LFG | The relationship between Lexical-Functional Grammar (LFG) functional structures (f-structures) for sentences and their semantic interpretations can be expressed directly in a fragment of linear logic in a way that explains correctly the constrained interactions between quantifier scope ambiguity and bound anaphora. The... | [
"Reasoning"
] | [
8
] |
SCOPUS_ID:0014749746 | A Deductive Question-Answerer for Natural Language Inference | The question-answering aspects of the Protosynthex III prototype language processing system are described and exemplified in detail. The system is written in LISP 1.5 and operates on the Q-32 time-sharing system. The system's data structures and their semantic organization, the deductive question-answering formalism of... | [
"Natural Language Interfaces",
"Reasoning",
"Question Answering",
"Textual Inference"
] | [
11,
8,
27,
22
] |
http://arxiv.org/abs/1511.08277v1 | A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations | Matching natural language sentences is central for many applications such as information retrieval and question answering. Existing deep models rely on a single sentence representation or multiple granularity representations for matching. However, such methods cannot well capture the contextualized local information in... | [
"Language Models",
"Semantic Text Processing",
"Question Answering",
"Representation Learning",
"Natural Language Interfaces"
] | [
52,
72,
27,
12,
11
] |
https://aclanthology.org//W14-2405/ | A Deep Architecture for Semantic Parsing | Many successful approaches to semantic parsing build on top of the syntactic analysis of text, and make use of distributional representations or statistical models to match parses to ontology-specific queries. This paper presents a novel deep learning architecture which provides a semantic parsing system through the un... | [
"Knowledge Representation",
"Semantic Parsing",
"Semantic Text Processing",
"Syntactic Text Processing"
] | [
18,
40,
72,
15
] |
SCOPUS_ID:85076628890 | A Deep Attention based Framework for Image Caption Generation in Hindi Language | Image captioning refers to the process of generating a textual description for an image which defines the object and activity within the image. It is an intersection of computer vision and natural language processing where computer vision is used to understand the content of an image and language modelling from natural... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Captioning",
"Text Generation",
"Multimodality"
] | [
20,
52,
72,
39,
47,
74
] |
SCOPUS_ID:85129612499 | A Deep Attentive Multimodal Learning Approach for Disaster Identification From Social Media Posts | Microblogging platforms such as Twitter have become indispensable for disseminating valuable information, especially at times of natural and man-made disasters. Often people post multimedia contents with images and/or videos to report important information such as casualties, damages of infrastructure, and urgent needs... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:85073253859 | A Deep Bidirectional Highway Long Short-Term Memory Network Approach to Chinese Semantic Role Labeling | Existing approaches to Chinese semantic role labeling (SRL) mainly adopt deep long short-term memory (LSTM) neural networks to address the long-term dependencies problem. However, deep LSTM networks cannot address the vanishing gradient problem properly. In addition, the complexity of the Chinese language, as a hierogl... | [
"Language Models",
"Semantic Parsing",
"Semantic Text Processing"
] | [
52,
40,
72
] |
SCOPUS_ID:85067867363 | A Deep CFS Model for Text Clustering | With the fast development of the Internet technology, the court text information is collected from various fields at an unprecedented speed, such as Weibo and Wechat. This big court text information of high volume poses a vast challenge for the judge making reasonable decisions based on the vast cases. To cluster the r... | [
"Information Extraction & Text Mining",
"Text Clustering"
] | [
3,
29
] |
http://arxiv.org/abs/2201.12664v1 | A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment Datasets | Arabic sentiment analysis has become an important research field in recent years. Initially, work focused on Modern Standard Arabic (MSA), which is the most widely-used form. Since then, work has been carried out on several different dialects, including Egyptian, Levantine and Moroccan. Moreover, a number of datasets h... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85060016334 | A Deep CNN Model for Student Learning Pedagogy Detection Data Collection Using OCR | Student learning pedagogy detection requires a huge amount of data from students. Efficient process to collect the data is a major fact here. This paper proposes an approach based on Convolutional Neural Network (CNN) for Optical Character Recognition (OCR) and mainly shows a method to use this OCR system to extract in... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
http://arxiv.org/abs/1811.11374v1 | A Deep Cascade Model for Multi-Document Reading Comprehension | A fundamental trade-off between effectiveness and efficiency needs to be balanced when designing an online question answering system. Effectiveness comes from sophisticated functions such as extractive machine reading comprehension (MRC), while efficiency is obtained from improvements in preliminary retrieval component... | [
"Information Extraction & Text Mining",
"Green & Sustainable NLP",
"Machine Reading Comprehension",
"Reasoning",
"Responsible & Trustworthy NLP"
] | [
3,
68,
37,
8,
4
] |
SCOPUS_ID:85124280117 | A Deep Content-Based Model for Persian Rumor Verification | During the development of social media, there has been a transformation in social communication. Despite their positive applications in social interactions and news spread, it also provides an ideal platform for spreading rumors. Rumors can endanger the security of society in normal or critical situations. Therefore, i... | [
"Semantic Text Processing",
"Information Retrieval",
"Syntactic Text Processing",
"Representation Learning",
"Text Classification",
"Information Extraction & Text Mining"
] | [
72,
24,
15,
12,
36,
3
] |
SCOPUS_ID:85044472751 | A Deep Convolution Neural Network Based Model for Enhancing Text Video Frames for Detection | The main causes of getting poor results in video text detection is low quality of frames and which is affected by different factors like de-blurring, complex background, illumination etc. are few of the challenges encountered in image enhancement. This paper proposes a technique for enhancing image quality for better h... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:85080905257 | A Deep Convolutional Deblurring and Detection Neural Network for Localizing Text in Videos | Scene text in the video is usually vulnerable to various blurs like those caused by camera or text motions, which brings additional difficulty to reliably extract them from the video for content-based video applications. In this paper, we propose a novel fully convolutional deep neural network for deblurring and detect... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
http://arxiv.org/abs/2201.06313v3 | A Deep Convolutional Neural Networks Based Multi-Task Ensemble Model for Aspect and Polarity Classification in Persian Reviews | Aspect-based sentiment analysis is of great importance and application because of its ability to identify all aspects discussed in the text. However, aspect-based sentiment analysis will be most effective when, in addition to identifying all the aspects discussed in the text, it can also identify their polarity. Most p... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Information Retrieval",
"Information Extraction & Text Mining",
"Polarity Analysis",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis",
"Responsible & Trustworthy NLP",
"Text Classification",
"Green & Sustainable NLP"
] | [
52,
80,
72,
24,
3,
33,
23,
78,
4,
36,
68
] |
http://arxiv.org/abs/1906.12188v1 | A Deep Decoder Structure Based on WordEmbedding Regression for An Encoder-Decoder Based Model for Image Captioning | Generating textual descriptions for images has been an attractive problem for the computer vision and natural language processing researchers in recent years. Dozens of models based on deep learning have been proposed to solve this problem. The existing approaches are based on neural encoder-decoder structures equipped... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Captioning",
"Representation Learning",
"Text Generation",
"Multimodality"
] | [
20,
52,
72,
39,
12,
47,
74
] |
http://arxiv.org/abs/1811.04670v1 | A Deep Ensemble Framework for Fake News Detection and Classification | Fake news, rumor, incorrect information, and misinformation detection are nowadays crucial issues as these might have serious consequences for our social fabrics. The rate of such information is increasing rapidly due to the availability of enormous web information sources including social media feeds, news blogs, onli... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Ethical NLP",
"Reasoning",
"Fact & Claim Verification",
"Text Classification",
"Responsible & Trustworthy NLP"
] | [
3,
24,
17,
8,
46,
36,
4
] |
http://arxiv.org/abs/1805.06553v1 | A Deep Ensemble Model with Slot Alignment for Sequence-to-Sequence Natural Language Generation | Natural language generation lies at the core of generative dialogue systems and conversational agents. We describe an ensemble neural language generator, and present several novel methods for data representation and augmentation that yield improved results in our model. We test the model on three datasets in the restau... | [
"Language Models",
"Semantic Text Processing",
"Text Generation"
] | [
52,
72,
47
] |
SCOPUS_ID:85127754176 | A Deep Fusion Matching Network Semantic Reasoning Model | As the vital technology of natural language understanding, sentence representation reasoning technology mainly focuses on sentence representation methods and reasoning models. Although the performance has been improved, there are still some problems, such as incomplete sentence semantic expression, lack of depth of rea... | [
"Semantic Text Processing",
"Representation Learning",
"Explainability & Interpretability in NLP",
"Reasoning",
"Responsible & Trustworthy NLP"
] | [
72,
12,
81,
8,
4
] |
http://arxiv.org/abs/1709.05074v1 | A Deep Generative Framework for Paraphrase Generation | Paraphrase generation is an important problem in NLP, especially in question answering, information retrieval, information extraction, conversation systems, to name a few. In this paper, we address the problem of generating paraphrases automatically. Our proposed method is based on a combination of deep generative mode... | [
"Paraphrasing",
"Text Generation"
] | [
32,
47
] |
http://arxiv.org/abs/1906.08972v1 | A Deep Generative Model for Code-Switched Text | Code-switching, the interleaving of two or more languages within a sentence or discourse is pervasive in multilingual societies. Accurate language models for code-switched text are critical for NLP tasks. State-of-the-art data-intensive neural language models are difficult to train well from scarce language-labeled cod... | [
"Code-Switching",
"Language Models",
"Semantic Text Processing",
"Multilinguality"
] | [
7,
52,
72,
0
] |
http://arxiv.org/abs/1807.02745v1 | A Deep Generative Model of Vowel Formant Typology | What makes some types of languages more probable than others? For instance, we know that almost all spoken languages contain the vowel phoneme /i/; why should that be? The field of linguistic typology seeks to answer these questions and, thereby, divine the mechanisms that underlie human language. In our work, we tackl... | [
"Typology",
"Syntactic Text Processing",
"Multilinguality"
] | [
45,
15,
0
] |
SCOPUS_ID:85062279624 | A Deep Hierarchical Neural Network Model for Aspect-based Sentiment Analysis | Aspect-based sentiment analysis has become one of the research hotspots in the field of natural language processing (NLP) in recent years. Different from ordinary sentiment analysis, aspect-based sentiment classification is a fine-grained task of sentiment analysis in the field of NLP, which need to infer different sen... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Representation Learning",
"Polarity Analysis",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis",
"Text Classification",
"Information Extraction & Text Mining"
] | [
52,
72,
24,
12,
33,
23,
78,
36,
3
] |
SCOPUS_ID:85118587974 | A Deep Language Model for Symptom Extraction From Clinical Text and its Application to Extract COVID-19 Symptoms From Social Media | Patients experience various symptoms when they haveeither acute or chronic diseases or undergo some treatments for diseases. Symptoms are often indicators of the severity of the disease and the need for hospitalization. Symptoms are often described in free text written as clinical notes in the Electronic Health Records... | [
"Language Models",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
52,
72,
3
] |
http://arxiv.org/abs/2011.10358v1 | A Deep Language-independent Network to analyze the impact of COVID-19 on the World via Sentiment Analysis | Towards the end of 2019, Wuhan experienced an outbreak of novel coronavirus, which soon spread all over the world, resulting in a deadly pandemic that infected millions of people around the globe. The government and public health agencies followed many strategies to counter the fatal virus. However, the virus severely ... | [
"Semantic Text Processing",
"Sentiment Analysis",
"Representation Learning"
] | [
72,
78,
12
] |
SCOPUS_ID:85109142457 | A Deep Learning Approach Combining CNN and Bi-LSTM with SVM Classifier for Arabic Sentiment Analysis | Deep learning models have recently been proven to be successful in various natural language processing tasks, including sentiment analysis. Conventionally, a deep learning model’s architecture includes a feature extraction layer followed by a fully connected layer used to train the model parameters and classification t... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Sentiment Analysis",
"Text Classification",
"Information Extraction & Text Mining"
] | [
52,
72,
24,
78,
36,
3
] |
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