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Speakers in dialogue produce speech in a piecemeal fashion and on-line as the dialogue progresses. When starting to speak, dialogue participants typically do not have a complete plan of how to say something or even what to say. Yet, they manage to rapidly integrate information from different sources in parallel and sim... | 0 |
While several theories of discourse structure for text exist, discourse parsing work has largely concentrated on Rhetorical Structure Theory (RST) (Mann and Thompson, 1988) and the RST Discourse Treebank (RST-DT) (Carlson et al., 2003) , which is the largest corpus of texts annotated with full discourse structures. The... | 0 |
Identifying document pairs that are mutual translations of one another in large multilingual document collections is an important processing step in harvesting parallel bilingual data from web crawls. The Shared Task on Bilingual Document Alignment at the First Conference on Machine Translation (WMT16) provides a commo... | 0 |
As natural language processing techniques become useful for an increasing number of new information domains, it is not always clear how best to identify information of interest, or to evaluate the output of automatic annotation tools. This can be especially challenging when target data in the form of long strings or na... | 0 |
Recently, many new features have been explored for SMT and significant performance have been obtained in terms of translation quality, such as syntactic features, sparse features, and reordering features. However, most of these features are manually designed on linguistic phenomena that are related to bilingual languag... | 0 |
Text mining of scientific literature originates from efforts to cope with the ever growing flood of publications in biomedicine (Swanson, 1986; Swanson, 1988; Swanson and Smalheiser, 1997; Hearst, 1999; Ananiadou et al., 2006; Zweigenbaum et al., 2007; Cohen and Hersh, 2005; Krallinger et al., 2008; Rodriguez-Esteban, ... | 0 |
The Speech Technology Group of the Universidad Politécnica de Madrid has participated in the sixth workshop on statistical machine translation in the Spanish-English and English-Spanish translation task.Our submission is based on the state-of-the-art SMT toolkit Moses (Koehn, 2010) adding a preprocessing and a post-pro... | 0 |
When we got news from newspapers and TVs which was thoroughly investigated and written by professional journalists, most of these messages are well-found and trustworthy. However, with the popularity of the internet, there are 2.5 quintillion bytes of data created each day at our current pace 1 . Everyone online is a p... | 0 |
E-HowNet is a lexical semantic representation model extended from HowNet and hence inherits the basic framework of HowNet. HowNet is an on-line common-sense knowledge base indexing relations of concepts gathered from lexicons of Chinese and English (Dong and Dong, 2006) . Each concept is represented and understood by i... | 0 |
For medical narratives such as clinical notes, event and time information can be useful in automated classification and prediction tasks. For example, the timeline of a patient's medical history can be used to predict whether they will be readmitted to the hospital within a certain time window. A medical timeline can a... | 0 |
The identification of semantic relations in text is at the core of Natural Language Processing and many of its applications. Detecting semantic relations between various text segments, such as phrases, sentences, and discourse spans, is important for automatic text understanding (Rosario, Hearst, and Fillmore 2002; Lap... | 0 |
In recent years, Transformer-based language models have brought dramatic improvements on a wide range of natural language tasks (Brown et al., 2020; Devlin et al., 2019) . The central innovation of Transformer architectures is the self-attention mechanism (Vaswani et al., 2017) , which has grown beyond NLP, extending i... | 0 |
The ability to identify and analyse temporal information is crucial for a variety of practical NLP applications such as information extraction, question answering, and summarisation. In multidocument summarisation, information must be extracted, potentially fused, and synthesised into a meaningful text. Knowledge about... | 0 |
A growing number of applications in natural language processing rely on knowledge about the semantic similarity between words. These similarities are used for example in ontology learning (Cimiano et al., 2005) , information retrieval (Müller et al., 2007) , and word sense disambiguation (Patwardhan et al., 2007) . One... | 0 |
Most assessment for placement, diagnosis, progress and achievement in our language programs are presently administered in paper and pencil (P&P) format. This format carries a number of administrative costs and inefficiencies. It requires new hard copy forms of assessments for each course and class, incurring costs asso... | 0 |
The task of semantic role labeling (SRL) involves predicting the predicate-argument structure of a sentence. More formally, for every predicate, the SRL model must identify all argument spans and label them with their semantic roles (see Figure 1 ). The most popular resources for estimating SRL models are PropBank (Pa... | 0 |
In the cognitive sciences, theories about how concrete concepts such as ELEPHANT are represented in the mind have often adopted a distributed, featurebased model of conceptual knowledge (e.g. Randall et al. (2004) , Tyler et al. (2000) ). According to such accounts, conceptual representations consist of patterns of act... | 0 |
A procedure includes some steps needed to achieve a particular goal (Momouchi, 1980) . Procedures are inherently hierarchical: a high-level procedure is composed of many lower-level procedures. For example, a procedure with the goal make videos consists of steps like purchase a camera, set up lighting, edit the video, ... | 0 |
The full stop, or period character, is ambiguous. As well as its use as a sentence delimiter, it is often collocated with abbreviations ("Prof."), occurs in numeric expressions ("13.2 mg"), including dates, and appears in a series of special names such as Web addresses. Minor variations exist between languages and dial... | 0 |
Modeling discourse coherence (the way parts of a text are linked into a coherent whole) is essential for summarization (Barzilay and McKeown, 2005 ), text planning (Hovy, 1988; Marcu, 1997) question-answering (Verberne et al., 2007) , and even psychiatric diagnosis (Elvevåg et al., 2007; Bedi et al., 2015) .Various fra... | 0 |
Bilingual lexicon learning (BLL) is the task of finding words that share a common meaning across different languages. It plays an important role in a variety of fundamental tasks in IR and NLP, e.g. cross-lingual information retrieval and statistical machine translation. The majority of current BLL models aim to learn ... | 0 |
From a linguistic perspective, a natural language sentence can be thought of as a set of nested constituents in the form of a tree structure (Partee et al., 2012) . When a parser is trained on labeled treebanks, the predicted constituency trees are useful for various natural language processing (NLP) tasks, including r... | 0 |
Traditional NLP tasks such as part-of-speech (POS) tagging or semantic role labeling (SRL) consists in tagging each word in a sentence with a tag. Another class of problems such as Named Entity Recognition (NER) or shallow parsing (chunking) consists in identifying and labeling phrases (i.e. groups of words) with prede... | 0 |
The identification of the syntactic class and the discovery of semantic information for words not contained in any on-line dictionary or thesaurus is an important and challengingproblem. Excellent methods have been developed for part-of-speech (POS) tagging using stochastic models trained on partially tagged corpora (C... | 0 |
Of the following events, a human reader can easily discern that (1) and (2) are semantically plausible, while (3) is nonsensical.(1) The person breathes the air.(2) The dentist breathes the helium.(3) The thought breathes the car. This ability is required for understanding natural language: specifically, modeling selec... | 0 |
Cross-Framework Meaning Representation Parsing (MRP) at CoNLL 2019 contains five different graph-based semantic representations, including DM, PSD, EDS, UCCA and AMR. The shared task releases training and testing data for all five frameworks. For different frameworks, organizers design different evaluation criteria and... | 0 |
There is a growing interest in the application of automatic and computer-aided approaches for extracting, summarizing, and analyzing both qualitative and quantitative financial data, as a series of FNP and related workshops (El-Haj et al., 2018; El-Haj, 2019; El-Haj et al., 2020b) recently demonstrates. However, before... | 0 |
Numerous formalisms and systems have been designed for representing the grammar of free word order languages [10] , [18) , [19] , [9] , [15) , [7] , [14) . Each formalism has tried to capture some examples of local scrambling or long distance scrambling. Some of the formalisms considered the role of discourse in scramb... | 0 |
The ability to understanding social nuances and human preferences is central to natural language understanding. This also enables better alignment of machine learning models with human values, eventually leading to better human-compatible AI applications Leslie, 2019; Rosenfeld and Kraus, 2018; Amodei et al., 2016; Rus... | 0 |
Automatic dialogue generation task is of great importance to many applications, ranging from open-domain chatbots (Higashinaka et al., 2014; Vinyals and Le, 2015; Li et al., 2016 Li et al., , 2017a to goal-oriented technical support agents (Bordes and Weston, 2016; Asri et al., 2017) . Recently there is an increasing a... | 0 |
Native language identification (NLI) is the task of determining an author's native language (L1) based on their writings in a second language (L2). NLI works under the assumption that an author's L1 will dispose them towards particular language production patterns in their L2, as influenced by their native language. Th... | 0 |
The most challenging problem in NLP is to program computers to understand natural languages. For a human being, efficient syllable-to-word (STW) conversion and word sense disambiguation (WSD) arise naturally while a sentence is understood. Therefore, in designing a natural language understanding (NLD) system, two basic... | 0 |
Word Sense Disambiguation (WSD) is concerned with the identification of the correct sense of an ambiguous word given its context. Although it can be thought of as an independent task, its importance is more easily realized when it is applied to particular tasks, such as Information Retrieval or Machine Translation (MT)... | 0 |
Presentation of knowledge in dialogue format is a popular way to communicate information effectively. It has been demonstrated in games, news, commercials, and educational entertainment. Usability studies have shown that for information acquirers dialogues often communicate information more effectively and persuade str... | 0 |
In the last years, NLP tools are being more and more used in tasks such as textual inference, machine translation, hate speech detection (Socher et al., 2012) . Most of these tasks rely on machine learning systems trained on large amounts of data, which have been manually labeled by annotators, often domain experts. In... | 0 |
Acquisition of prosody, in addition to vocabulary and grammar, is essential for language learners. However, intonation has been less-emphasized both in classroom and computer-assisted language instruction (Chun, 1998) . Outside of tone languages, it can be difficult to characterize the factors that lead to non-native p... | 0 |
Conversational agents (a.k.a. Chat-bots) are effective media to establish communications with human beings and have received much attention from academic and industrial experts in recent years . One essential fact promoting the research work on conversational agents is the explosive growth of human interaction data acc... | 0 |
One-on-one tutoring is often considered the goldstandard of educational interventions. Past work suggests that this form of personalized instruction can increase student performance by two standard deviation units (Bloom, 1984) . Chatbots, intelligent tutoring systems (ITS), and remote tutoring are often seen as a way ... | 0 |
Statistical language models are used in many natural language technologies, including automatic speech recognition (ASR), machine translation, handwriting recognition, and spelling correction, as a crucial component for improving system performance. A statistical language model represents a probability distribution ove... | 0 |
Multiplicity of languages is inherent to modern society. Phenomena such as globalization and technological development have extraordinarily increased the need for translating information from one language to another. One possibility to deal with this growing demand of translations is the use of machine translation (MT)... | 0 |
One of the major difficulties in studying speech production is the problem of observing how speakers coordinate various articulatory movements, i.e. the aspects that connect physiology and speech production. In a continuous speech, a set of coordinative structures is involved to organize the execution of such stereotyp... | 0 |
In Machine Translation (MT), the Quality Estimation (QE) task attempts to characterize the quality of a translation, without the availability of a (goldlabel) reference translation. The introduction of a QE system would consequently allow for the automatic analysis of machine-translated sentences without costly human r... | 0 |
Compared with a document, a title provides a compact representation of the information and therefore helps people quickly capture the main idea of a document without spending time on the details. Automatic title generation is a complex task, which not only requires finding the title words that reflects the document con... | 0 |
Natural language processing research has traditionally been divided into a number of separate tasks, each of which is believed to be an important subtask of the larger language comprehension or generation problem. These tasks are usually addressed separately, with systems designed to solve a single problem. However, ma... | 0 |
Use of topic-based models of dialogue has played a role in information retrieval (Oard et al., 2004) , information extraction (Baufaden, 2001) , and summarization (Zechner, 2001) . However, previous work on automatic topic segmentation has focused primarily on segmentation of expository text. We present Museli, a novel... | 0 |
We propose a new technique that biases early stage statistical machine translation (SMT) learning towards semantics. Our algorithm adopts the crosslingual evaluation metric XMEANT to initialize expectation-maximization (EM) outside probabilities during inversion transduction grammar or ITG (Wu, 1997) induction. We show... | 0 |
The World Wide Web (WWW) provides a vast amount of information and plentiful services, and continues to grow at a staggering rate. Because of its explosive growth, people are spending more and more time on the Web, performing various tasks, many of these tasks repetitive and tedious. The following is some typical scena... | 0 |
Multi-sentence compression (MSC) aims to generate a single shorter and grammatical sentence that preserves important information from a group of related sentences. Over the past decade, multisentence compression has attracted considerable attention owing to its potential applications, such as compressing the content to... | 0 |
The objective of NER is to identify and classify all tokens in a text document into predefined classes such as person, organization, location, miscellaneous. The Named Entity information in a document is used in many of the language processing tasks. NER was created as a subtask in Message Understanding Conference (MUC... | 0 |
Sentiment analysis is an important topic in computational linguistics that is of theoretical interest but also implies many real-world applications. Usually, two aspects are of importance in sentiment analysis. The first is the detection of subjectivity, i.e. whether a text or an expression is meant to express sentimen... | 0 |
Word classes are often used in language modelling to solve the problem of sparse data. Various clustering techniques have been proposed (Brown et al., 1992; Jardino and Adda, 1993; Martin et al., 1998) which perform automatic word clustering optimizing a maximum-likelihood criterion with iterative clustering algorithms... | 0 |
Massively Multilingual Models (MMMs) are neural networks that can perform a NLP task in multiple languages, relying on a shared set of parameters. At the time of writing, the state-of-the-art performance of MMMs is achieved by transformerbased models such as multilingual BERT (mBERT, Devlin et al., 2019) , XLM (Conneau... | 0 |
The HITECH (Health Information Technology for Economic and Clinical Health) Act, part of the 2009 economic stimulus package (American Recovery and Reinvestment Act) passed by the US Congress, aims at inducing more physicians to adopt Electronic Health Records (EHRs). An EHR is an evolving concept defined as a systemati... | 0 |
Speech disfluencies are characteristic for spontaneous speech. Different disfluency types can be distinguished: Filled pauses (FP) such as 'UH' or 'UM', restarts or repairs, and repetitions. It is widely accepted that disfluencies considerably degrade the performance of speech recognition due to unexpected word sequenc... | 0 |
The Japanese language has borrowed thousands of words from English, particularly since World War II, under the overwhelming economic and cultural influence of the United States. This massive borrowing over a comparatively short period of time provides a unique window on processes of loanword formation. Borrowed words m... | 0 |
Automatic machine translation metrics play a very important role in the development of MT systems and their evaluation. There are many different metrics of diverse nature and one would like to assess their quality. For this reason, the Metrics Shared Task is held annually at the Workshop of Statistical Machine Translat... | 0 |
Distributional thesauri are useful for many NLP tasks and their construction is an issue widely discussed for several years (Grefenstette, 1994) . However this is still a very active research field, maintained by the increasingly large number of available corpus and by many applications. These thesauri associate each o... | 0 |
In many democratic countries, political decisions are increasingly developed through the participation of citizens. Public participation processes allow citizens to voice their suggestions and concerns on specific issues, for example in urban planning, and thus influence decision-making processes. Participation can tak... | 0 |
Hebrew, Arabic, and other languages based on the Arabic script usually represent only consonants in writing and do not mark vowels. In such writing systems, diacritics are used for marking short vowels, gemination, and other phonetic units. In practice, diacritics are usually restricted to specific settings such as lan... | 0 |
It is important for much linguistic research to find datasets relating to hunches and hypotheses.Linguists and system developers would like to be able to find large numbers of examples quickly and easily.Our tool computes the Corpus Query Language (CQL) (Christ and Schulze, 1994) queries rapidly on large corpora using ... | 0 |
Automatic Metrics for machine translation (MT) evaluation have been receiving significant attention in the past two years, since IBM's BLEU metric was proposed and made available (Papineni et al 2002) . BLEU and the closely related NIST metric (Doddington, 2002) have been extensively used for comparative evaluation of ... | 0 |
In recent years, the semantic web (Berners-Lee et al., 2001) has been evolving as the nextgeneration web technology and has attracted the attention of many researchers in database and knowledge engineering communities. In the semantic web, contributions obtained from fields related to databases frequently refer to onto... | 0 |
In recent years, the detection of emerging events from publicly available data streams such as twitter messages has received a lot of attention. The approaches used range from topic modeling, incremental clustering, the concept of interestingness, and others (Hasan et al., 2017) . For example, methods relying on topic ... | 0 |
Joint learning of multiple types of linguistic structure results in models which produce more consistent outputs, and for which performance improves across all aspects of the joint structure. Joint models can be particularly useful for producing analyses of sentences which are used as input for higher-level, more seman... | 0 |
La fouille de données orales est un domaine de recherche visant à caractériser un flux audio contenant de la parole d'un ou plusieurs locuteurs à l'aide de descripteurs liés à la forme et au contenu du signal. Parmi ces descripteurs, le plus important est bien évidemment la transcription automatique en mots des paroles... | 0 |
Text-to-SQL translation is currently one of the most important tasks in semantic parsing. It involves mapping natural language sentences to SQL queries that can be executed on associated database tables. Most text-to-SQL data sets have two very important limitations: (1) they mostly contain only very simple SQL queries... | 0 |
For finding similarity between two documents, the general approach is to get the embeddings for the documents and use some similarity metric like cosine similarity to get similarity measures. Such work has been done in multiple domains like research papers, semantic similarity (Olizarenko and Radchenko, 2021) (Boom et ... | 0 |
A fundamental problem in distance education is student attrition, particularly during the early months of enrolment, which appears to be largely due to low morale. Graduation rates at distancelearning institutions are often less than 20% (Simpson, 2012) . Poor retention is evident at the level of individual modules or ... | 0 |
Non-Sentential Utterances (NSUs)-fragmentary utterances that convey a full sentential meaningare a common phenomenon in spoken dialogue. Because of their elliptical form and their highly context-dependent meaning, NSUs are a challenging problem for both linguistic theories and implemented dialogue systems. Although per... | 0 |
Until a few years ago, it was common to see NLP courses predominantly taught in either Computer Science or Linguistics departments, attended primarily by students from both the departments. In the past few years, there has been an increasing interest in NLP across disciplines. This is also reflected in the arrival of f... | 0 |
The goal of statistical machine translation (SMT) is to produce a target sentence e from a source sentence f . Among all possible target sentences the one with maximal probability is chosen. The classical Bayes relation is used to introduce a target language model (Brown et al., 1993) : where Pr(f |e) is the translatio... | 0 |
The availability of large datasets has been key to the success of deep learning in Natural Language Processing (NLP). This has galvanized the creation of larger datasets in order to train larger deep learning models. However, creating high quality datasets is expensive due to the sparsity of natural language, our inabi... | 0 |
Sentence alignment plays an important role in building bilingual corpora for statistical machine translation and many other tasks. Given documents from two languages, the task is to align sentences which are translations of each other. There are three main methods in sentence alignment including lengthbased, word-based... | 0 |
Despite being a form of language that has had the most impact across almost all human cultures, there have been very few attempts to apply computational linguistics to the genre of lyrics in music.As an attempt to motivate further research in this direction, we apply the learning algorithms of statistical machine trans... | 0 |
Data availability is a major obstacle in the development of more powerful Natural Language Processing (NLP) methods in the biomedical domain. In particular, current state-of-the-art (SOTA) neural techniques used for NLP rely on substantial amounts of training data.In the NLP community, this low-resource problem is typi... | 0 |
The translation paired comparison method precisely measures the capability of a speech translation system. In this method, native speakers compare a system's translation and the translations, made by examinees who have various TOEIC scores. The method requires two human costs: the data collection of examinees' translat... | 0 |
The ability to assign 'limited cross-serial dependencies' to the words in a sentence is a hallmark of mildly context-sensitive grammar formalisms (Joshi, 1985) . In the case of TAG, an exact definition of this ability can be given in terms of two graph-theoretic properties of the dependency structures induced by TAG de... | 0 |
Even the most sophisticated translation functionality is useless without a means of delivering it to the consumer. In an increasingly networked world, companies like Sail Labs are keenly interested in not only providing applications and services but also in building the systems by which people can make use of these ser... | 0 |
Cross-lingual model transfer approaches are concerned with creating statistical models for various tasks for languages poor in annotated resources, utilising resources or models available for these tasks in other languages. That includes approaches such as direct model transfer (Zeman and Resnik, 2008) and annotation p... | 0 |
Speech retrieval, like other tasks that require transforming the representation of language, suffers from both random and systematic errors that are introduced by the speech-to-text transducer. Limitations in signal processing, acoustic modeling, pronunciation, vocabulary, and language modeling can be accommodated in s... | 0 |
Natural languages are rich in ambiguities of many kinds (see examples 1, 3, 5 and 1). Furthermore, many sentences that do not seem ambiguous to humans, due to their extensive world knowledge, may present ambiguities to automatic parsers and to machine translation systems (see examples 2, 4, 6 and 8). Some of the more c... | 0 |
Recently, deep neural networks have made significant progress in complex pattern matching of various tasks such as computer vision and natural language processing. However, these models are limited in their ability to represent data structures such as graphs and trees, to use variables, and to handle representations ov... | 0 |
The task of extractive summarization can naturally be cast as a discrete optimization problem where the text source is considered as a set of sentences and the summary is created by selecting an optimal subset of the sentences under a length constraint (McDonald, 2007) . This view entails defining an objective function... | 0 |
Approaches to machine translation from French to Arabic are rare. Certainly, translation memory systems do exist (as for example the commercial system An-Nakel Al-Arabi from French to Arabic from CIMOS (Paris) 1 ) but the limitations of such systems are now well known to all specialists working in the domain. In this p... | 0 |
Dialogue is a language game of influence, action, and reaction that progresses in a turn-taking manner. Persuasion occurs through dialogue when a listener favorably evaluates the authority, claims, and evidentiality through the cues and arguments made by the speaker (Krippendorff, 1993; Schulte, 1980; Durik et al., 200... | 0 |
Modelling natural language with neural networks has been an extensively researched area for several years now. On the one hand, deep learning enormously reduced the cost of feature engineering. On the other hand, we are largely unaware of features that are used in estimating a neural model and, therefore, kinds of info... | 0 |
With the popularity of representation learning methods, such as Word2vec (Mikolov et al., 2013a) , words are represented as real-valued embedding vectors in the semantic space. Therefore, retrieval of similar word embeddings is one of the most basic operations in natural language processing with wide applicability in s... | 0 |
Identifying the most influential articles is of great importance in many areas of research. It is often the case that we are increasingly exposed to numerous papers published every day. Research on influence evaluation can be applied to measure the scholarly impact of universities and research facilities. Besides, it h... | 0 |
Natural language processing (NLP) research has been and is making astounding strides forward.1 EXPLAINABOARD keeps updated and is recently upgraded by supporting (1) multilingual multi-task benchmark and (2) more complicated task: machine translation, which reviewers also suggested.2 http://explainaboard.nlpedia.ai/ 3 ... | 0 |
Humans show a lot of variance in the way they express themselves in a conversation. Not only do they change their phrasing by exchanging words with similar meaning for each other, often whole sentences are used interchangeably although they do not have much in common on a surface level. For example, 'When will you be h... | 0 |
Because Japanese exhibits a flexible word order, potential factors that predict word orders of a given construction in Japanese have been recently delved into, particularly in the field of computational linguistics (Yamashita and Kondo, 2011; Orita, 2017) . One of the major findings relevant to the current study is 'lo... | 0 |
In this internet era, everyday people express opinions, comments, or sentiments; all of which can be accessed via the web. Particularly with the popularization of mobile computing devices, it has become easier than ever for people to share messages using social media services like Twitter or Facebook. However, such an ... | 0 |
Argument mining is the process of identifying argumentative structure contained within a text. It involves segmenting arguments into elementary discourse units (EDUs), distinguishing argumentative units from non-argumentative units, classifying argument components into classes such as premise and claim, identifying and... | 0 |
It is important for an annotated corpus that the markup is both correct and, in cases where variant analyses could be considered correct, consistent. Considerable research in the field of word sense disambiguation has concentrated on showing that the annotation of word senses can be done correctly and consistently, wit... | 0 |
Tokenization is the process of splitting text into smaller units called tokens (e.g., words). It is a fundamental preprocessing step for almost all NLP applications: sentiment analysis, question answering, machine translation, information retrieval, etc.Modern NLP models like BERT (Devlin et al., 2019) , GPT-3 (Brown e... | 0 |
Linguistically annotated corpora, such as treebanks (Marcus et al., 1993) or propbanks (Palmer et al., 2005) , are a crucial driver of progress in natural language processing research. As a cost-effective alternative to manual annotation, previous work explored the use of annotation projection in parallel corpora to au... | 0 |
For almost two decades, BLEU (Papineni et al., 2002) has been a key driver of the development of Machine Translation (MT) and MT Evaluation despite its blind spots. Marie et al. (2021) statistically support such trend, reporting that in the past decade, about 98.8% of research papers of ACL under the title of "MT" rega... | 0 |
Public opinion has a great impact on company and government decision making. In particular, companies have to constantly monitor public perception of their products, services, and key company representatives to ensure that good reputation is maintained. Recent cases of public figures making headlines for the wrong reas... | 0 |
Synonyms can be an important resource for Information Retrieval (IR) applications, and attempts have been made at using them to expand query terms (Voorhees, 1998) . In expanding query terms, overgeneration is as much of a problem as incompleteness or lack of synonym resources. Precision can dramatically drop because o... | 0 |
This paper describes the construction of DreamDrug, a dataset of drug-related product listings from darknet marketplaces with human-annotated drug entities, suitable for training and evaluating named entity recognition (NER) systems. We provide a detailed description of all steps of annotation and dataset construction,... | 0 |
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