Ақпаратты іздеу

A system is proposed here for assigning a derived P-marker to a given transformed sentence and obtaining the corresponding base P-marker at the same time. Rules of analytical phrase-structure grammar …...

: Several methods to represent meanings of words have been proposed. However, they are not useful for information retrieval systems, because they cannot deal with the entities which cannot be …...

Recent theories of focusing and reference rely crucially on discourse structure to constrain the availability of discourse entities for reference, but deriving the structure of an arbitrary discourse has proved …...

We describe a method for obtaining subject-dependent word sets relative to some (subjecO domain. Using the subject classifications given in the machine-readable ver- sion of Longman's Dictionary of Contemporary English, …...

We have been addressing the problem of providing access to the free text in biomedical databases. The focus of our work is the development of SPECIALIST, an experimental NLP system …...

We developed a prototype information retrieval sys- tem which uses advanced natural language process- ing techniques to enhance the effectiveness of tradi- tional key-word based document retrieval. The back- bone …...

In information retrieval, the content of a document may be represented as a collection of terms: words, stems, phrases, or other units derived or inferred from the text of the …...

In this paper we demonstrate that speech recognition can be effectively applied to information retrieval (IR) applications. Our system exploits the fact that the intended words of a spo- ken …...

Many information retrieval(IR) systems retrieve relevant documents based on exact matching of keywords between a query and documents. This method degrades precision rate. In order to solve the problem, we …...

Many researches found lexical preferences to be critical in resolving attachment ambiguity [WFB 90][FBK 82][ MP 80]. Most notably, information from Verb-Obj-Prep-Noun structures (VOPN) has been used to show that …...

In this paper we describe an architecture and functionality of main components of a workbench for an acquisition of do- main knowledge from large text corpora. The workbench supports an …...

The development of natural language pro- ccssing (NLP) systems that perform ma- chine translation (MT) and information re- trieval (IR) has highlighted the need for the automatic recognition of proper …...

The shift from Computational Linguistics to Language Engineering is indicative of new trends in NLP. This paper reviews two NLP engineering problems: reuse and integration, while relating these concerns to …...

This paper discusses research on distin- guishing word meanings in the context of information retrieval systems. We conduc- ted experiments with three sources of evid- ence for making these distinctions: …...

This paper addresses the problem of iden- tifying likely topics of texts by their posi- tion in the text. It describes the automated training and evaluation of an Optimal Posi- …...

We investigate the effects of lexicon size and stopwords on Chinese information retrieval using our method of short-word segmentation based on simple language usage rules and statistics. These rules allow …...

A layered approach to information retrieval permits the inclusion of multiple search en- gines as well as multiple databases, with a natural language layer to convert English queries for use …...

A layered approach to information retrieval permits the inclusion of multiple search en- gines as well as nmltiple databases, with a natural language layer to convert English queries for use …...

This paper presents a practical foreign language writing support tool which makes it much easier to utilize dictionary and example sentence resources. Like a Kana-Kanji conversion front-end processor used to …...

This paper describes a domain independent, automat- ically trained call router which directs customer calls based on their response to an open-ended "How may ldi- rect your call?" query. Routing …...

We investigated both English and Chinese ad-hoc information retrieval (IR). Part of our objectives is to study the use of term, phrasal and topical concept level evidence, either individually or …...

Applied discourse analysis is a hot topic in In- formation Retrieval (IR) and the related field of Information Extraction (IE). Although in- teresting observations about discourse can be made "by …...

We describe a trainable and scalable sum- marization system which utilizes features derived from information retrieval, inibr- mation extraction, and NLP techniques and on-line resources. The system con> bines these …...

AbstractAmong the three main applications using multilinguality, i.e., information retrieval, summarization and text generation, the first one could be considered to be the core and the other two its supporting …...

Accurate nominal compound analysis is cru- cial for in application of natural language pro- cessing such as information retrieval and ex- traction as well as nominal compound inter- pretation. I,n …...

A number of previous experiments on the role of lexical ambiguity, in Information Retrieval are re- produced on the'IR-Semcor test collection (derived from Semcor), where both queries and documents are …...

Previous comparisons of document and query translation suffered difficulty due to differing quality of machine translation in these two opposite directions. We avoid this difficulty by training identical statistical translation …...

Most documents are about more than one subject, but many NLP and IR techniques implicitly assume documents have just one topic. We describe new clues that mark shifts to new …...

Subjectivity is a pragmatic, sentence-level feature that has important implications for text processing applica- tions such as information extraction and information re- trieval. We study the effects of dynamic adjectives, …...

Repetition is very common. Adaptive language models, which allow probabilities to change or adapt after seeing just a few words of a text, were introduced in speech recognition to account …...

We describe and evaluate an implemented system for general-knowledge question answering. The sys- tem combines techniques for standard ad-hoc infor- mation retrieval (IR), query-dependent text summa- rization, and shallow syntactic …...

In this paper, we propose an Inductive Logic Programming learning method which aims at automatically extracting special Noun-Verb (N- V) pairs from a corpus in order to build up semantic …...

Oral communication is ubiquitous and carries important in- formation yet it is also time consuming to document. Given the development of storage media and networks one could just record and …...

We present the technique of Virtual Annotation as a specialization of Predictive Annotation for answering definitional What is questions. These questions generally have the property that the type of the …...

Fusion and clustering are two approaches to improving the effectiveness of information retrieval. In fusion, ranked lists are combined together by various means. The motivation is that different IR systems …...

This paper describes an evaluation of an existing technique that locates sentences containing descriptions of a query word or phrase. The experiments expand on previous tests by exploring the effectiveness …...

This paper describes SCANMail, a system that allows users to browse and search their voicemail messages by content through a GUI. Content based navigation is realized by use of automatic …...

We studied contrast and variability in a corpus of gene names to identify potential heuristics for use in performing entity identification in the molecular biology domain. Based on our findings, …...

Covering ambiguity is one of the two basic types of ambiguities in Chinese word segmentation. We regard its resolution as equivalent to word sense disambiguation, and make use of the …...

It is popular in WSD to use contextual information in training sense tagged data. Co-occurring words within a limited window-sized context support one sense among the semantically ambiguous ones of …...

� This� paper� discusses� the� challenges� and� pro- poses� a� solution� to� performing� information� re- trieval�on�the�Web�using�Chinese�natural�language� speech� query.� The� main� contribution� of� this� re- search�is�in�devising�a�divide-and-conquer�strategy� to� alleviate� the� speech� recognition� …...

Link detection has been regarded as a core technology for the Topic Detection and Tracking tasks of new event detection. In this paper we formulate story link detec- tion and …...

Language model based IR system proposed in recent 5 years has introduced the language model approach in the speech recognition area into the IR community and improves the performance of …...

This paper presents a method to construct Japanese KATAKANA variant list from large corpus. Our method is useful for information retrieval, information extrac- tion, question answering, and so on, because …...

For Sinequa’s second participation to the Senseval evaluation, two systems using contextual semantic have been proposed. Based on different approaches, they both share the same data preprocessing and enrichment. The …...

The work presented in this paper is the first step in a project which aims to cluster and sum- marise electronic discussions in the context of help-desk applications. The eventual …...

Irregular (so-called broken) plural identification in modern standard Arabic is a problematic issue for information retrieval (IR) and language engineering applications, but their effect on the performance of IR has …...

In this paper we describe a biography summarization system using sentence classification and ideas from information retrieval. Although the individual techniques are not new, assembling and applying them to generate …...

Recently, shallow parsing has been applied to various information processing systems, such as information retrieval, information extraction, question answering, and automatic document summarization. A shallow parser is suitable for online …...

Recent studies into Web retrieval have shown that word sense disambiguation can increase retrieval effectiveness. How- ever, it remains unclear as to the mini- mum disambiguation accuracy required and the …...

We consider the problem of training logis- tic regression models for binary classifi- cation in information extraction and infor- mation retrieval tasks. Fitting probabilis- tic models for use with such …...

The trend in information retrieval sys- tems is from document to sub-document retrieval, such as sentences in a summari- zation system and words or phrases in question-answering system. Despite this …...

. The automatic alignment of parallel corpora is a very rich source of information for automatic translation, multilingual document indexing, information retrieval, etc. The rapid growth of the use of …...

. Traditional approaches for information retrieval from texts depend on the term frequency. A shortcoming of these schemes, which consider only occurrences of the terms in a document, is that …...

This paper presents a hybrid approach to question answering in the clinical domain that combines techniques from summarization and information retrieval. We tackle a frequently-occurring class of questions that takes …...

spaces and how that intimate relation- ship might be exploited when applied in computational linguistics. It is also about an approach to information retrieval, because the analysis of natural language, …...

. We propose an information retrieval method based on question identification. We have implemented and integrated a prototype Chinese speech IR system for a commercial PDA with this method for …...

An automatic word spacing is one of the important tasks in Korean language pro- cessing and information retrieval. Since there are a number of confusing cases in word spacing of …...

Information retrieval systems are fre- quently required to handle long queries. Simply using all terms in the query or re- lying on the underlying retrieval model to appropriately weight terms …...

Many systems for tasks such as question answer- ing, multi-document summarization, and infor- mation retrieval need robust numerical measures of lexical relatedness. Standard thesaurus-based measures of word pair similarity are …...

This paper addresses the task of provid- ing extended responses to questions re- garding specialized topics. This task is an amalgam of information retrieval, topical summarization, and Information Extrac- tion …...

One of the main challenges in the applica- tions (i.e.: text summarization, question an- swering, information retrieval, etc.) of Natural Language Processing is to deter- mine which of the several …...

In Modern Mongolian, a content word can be inflected when concatenated with suf- fixes. Identifying the original forms of content words is crucial for natural lan- guage processing and information …...

Supervised approaches to Word Sense Dis- ambiguation (WSD) have been shown to outperform other approaches but are ham- pered by reliance on labeled training ex- amples (the data acquisition bottleneck). …...

Automatic estimation of word significance oriented for speech-based Information Re- trieval (IR) is addressed. Since the sig- nificance of words differs in IR, automatic speech recognition (ASR) performance has been …...

Web-search queries are known to be short, but little else is known about their structure. In this paper we investigate the applicability of part-of-speech tagging to typical English- language web …...

Semantic similarity is a central concept that extends across numerous fields such as artificial intelligence, natural language processing, cognitive science and psychol- ogy. Accurate measurement of semantic similarity between words …...

The use of lexical semantic knowledge in information retrieval has been a field of ac- tive study for a long time. Collaborative knowledge bases like Wikipedia and Wik- tionary, which …...

Good hypertext writing style mandates that link texts clearly indicate the nature of the link tar- get. While this guideline is routinely ignored in HTML, the lightweight markup languages used …...

We present a simple and effective method for extracting parallel sentences from comparable corpora. We employ a sta- tistical machine translation (SMT) system built from small amounts of parallel texts …...

AbstractThis paper describes the development of a new Swedish scientific medical corpus. We provide a detailed description of the characteristics of this new collection as well results of an application …...

AbstractIn this paper, we present the design, collection, transcription and analysis of a Mandarin Chinese Broadcast Collection of over 3000 hours. The data was collected by Hong Kong University of …...

AbstractFor mining intellectual property texts (patents), a broad-coverage lexicon that covers general English words together with terminology from the patent domain is indispensable. The patent domain is very diffuse as …...

AbstractIn recent years, considerable attention has been dedicated to language modeling methods in information retrieval. Although these approaches generally allow exploitation of any type of language model, most of the …...

Near-synonyms are useful knowledge re- sources for many natural language applica- tions such as query expansion for information retrieval (IR) and paraphrasing for text gen- eration. However, near-synonyms are not …...

We present a novel Evaluation Metric for Morphological Analysis (EMMA) that is both linguistically appealing and empirically sound. EMMA uses a graph- based assignment algorithm, optimized via integer linear programming, …...

AbstractWe present an experimental framework for Entity Mention Detection in which two different classifiers are combined to exploit Data Redundancy attained through the annotation of a large text corpus, as …...

AbstractThe focus of information retrieval evaluations, such as NIST’s TREC evaluations (e.g. Voorhees 2003), is on evaluation of the information content of system responses. On the other hand, retrieval tasks …...

In this paper we examine different linguistic features for sentimental polarity classification, and perform a comparative study on this task between blog and re- view data. We found that results …...

AbstractThis paper describes the development and evaluation of enhancements to the specialized information retrieval capabilities of a multimodal reporting system. The system enables collection and dissemination of information through a …...

AbstractThis paper compares several indexing methods for person names extracted from text, developed for an information retrieval system with requirements for fast approximate matching of noisy and multicultural Romanized names. …...

Multi-document summarization has been an important problem in infor- mation retrieval. It aims to dis- till the most important information from a set of documents to gener- ate a compressed …...

AbstractIn this paper, we present a multimodal parallel text-image corpus, and propose an image annotation method that exploits the textual information associated with images. Our corpus contains news articles composed …...

There is considerable interest in interdis- ciplinary combinations of automatic speech recognition (ASR), machine learning, natu- ral language processing, text classification and information retrieval. Many of these boxes, especially ASR, …...

AbstractWe have previously reported on ProPOSEL, a purpose-built Prosody and PoS English Lexicon compatible with the Python Natural Language ToolKit. ProPOSEC is a new corpus research resource built using this …...

AbstractMachine transliteration is used in a number of NLP applications ranging from machine translation and information retrieval to input mechanisms for non-roman scripts. Many popular Input Method Editors for Indian …...

AbstractWithout any doubt corpora are vital tools for linguistic studies and solution for applied tasks. Although corpora opportunities are very useful, there is a need of another kind of software …...

AbstractDuring the last years the campaign of mass digitization made available catalogues and valuable rare manuscripts and old printed books vie the Internet. The Manuscriptorium digital library ingested hundreds of …...

Information retrieval (IR) and figurative language processing (FLP) could scarcely be more different in their treatment of lan- guage and meaning. IR views language as an open-ended set of mostly …...

We present a data-driven approach to generat- ing responses to Twitter status posts, based on phrase-based Statistical Machine Translation. We find that mapping conversational stimuli onto responses is more difficult …...

. An interesting issue “whether the factual search result is better than the satisfactory one?” is discussed in this paper, and all effort is to illustrate the publicly recognized conception …...

Topic modeling for information retrieval (IR) has attracted significant attention and demonstrated good performance in a wide variety of tasks over the years. In this paper, we first present a …...

AbstractThe Semantic Annotation (SA) task consists in establishing the relation between a textual entity (word or group of words designating a named entity of the real world or a concept) …...

Started from the very beginning, Stemming has been playing significant roles in several Natural Language Processing Applications such as information retrieval (IR), machine translation (MT), morph analysis and deciding the …...

AbstractIn order to extract meaningful phrases from corpora (e. g. in an information retrieval context) intensive knowledge of the domain in question and the respective documents is generally needed. When …...

Lexical-phonetic automata for spoken utterance indexing and retrieval This paper presents a method for indexing spoken utterances which combines lexical and phonetic hypotheses in a hybrid index built from automata. …...

AbstractAlthough lexicography of Latin has a long tradition dating back to ancient grammarians, and almost all Latin grammars devote to wordformation at least one part of the section(s) concerning morphology, …...

Traditional general readability methods tend to underperform in domain-specific document retrieval because they fail to effectively differentiate the reading difficulty of the individual domain-specific terms and the semantic associations between …...

The geographical properties of words have re- cently begun to be exploited for geolocating documents based solely on their text, often in the context of social media and online content. …...

AbstractLanguage statistics are widely used to characterize and better understand language. In parallel, the amount of text mining and information retrieval methods grew rapidly within the last decades, with many …...

Citations are a valuable resource for characterizing scientific publications that has already been used in applications such as summarization and information retrieval. These applications could be even better served by …...

Information structure, i.e the way speakers construct sentences to present new information in the context of old, can capture rich linguistic information about the discourse structure of scientific documents. Information …...

Techniques that compare short text seg- ments using dependency paths (or simply, paths) appear in a wide range of automated language processing applications including question answering (QA). However, few models …...

Mining Partial Annotation Rules for Named Entity Recognition During the last decades, the unremitting increase of numeric data available has led to a more and more urgent need for efficient …...

Unsupervised CRF for knowledge discovery Knowledge discovery aims at bringing out coherent groups of entities. They are usually based on clustering ; the challenge is then to define a notion …...

Text classification methods for tasks like factoid question answering typi- cally use manually defined string match- ing rules or bag of words representa- tions. These methods are ineffective when question …...

. In this paper, we address the issue of building and improving a distributional thesaurus. We first show that existing tools from the information retrieval domain can be directly used …...

The most widely used similarity measure in the field of natural language processing may be co- sine similarity. However, in the context of Twitter, the large scale of massive tweet …...

Statistical language modeling (LM) that purports to quantify the acceptability of a given piece of text has long been an in- teresting yet challenging research area. In particular, language modeling …...

In this paper, a new hybrid algorithm that combines both token-based and character-based approaches is presented. The basic Levenshtein approach also has been extended to the token-based distance metric. The …...

Translation retrieval aims to find the most likely translation among a set of target-language strings for a given source-language string. Previous studies consider the single-best translation as a query for …...

AbstractThis paper deals with information retrieval on semantically enriched web-scale document collections. It particularly focuses on web-crawled content in which mentions of entities appearing in Freebase, DBpedia and other Linked …...

Uncertainty detection is essential for many NLP applications. For instance, in information re- trieval, it is of primary importance to distinguish among factual, negated and uncertain informa- tion. Current research …...

The extraction of domain terminology is a task that is increasingly used for different ap- plication processes of natural language such as the information recovery, the creation of spe- cialized …...

AbstractMorphological analysis is a fundamental task in natural-language processing, which is used in other NLP applications such as part-of-speech tagging, syntactic parsing, information retrieval, machine translation, etc. In this paper, …...

AbstractReaders usually rely on abstracts to identify relevant medical information from scientific articles. Abstracts are also essential to advanced information retrieval methods. More than 50 thousand scientific publications in PubMed …...

AbstractWe present Ambient Search, an open source system for displaying and retrieving relevant documents in real time for speech input. The system works ambiently, that is, it unobstructively listens to …...

Most sentence embedding models typical- ly represent each sentence only using word surface, which makes these models indis- criminative for ubiquitous homonymy and polysemy. In order to enhance represen- tation …...

AbstractDistributional thesauri are useful in many tasks of Natural Language Processing. In this paper, we address the problem of building and evaluating such thesauri with the help of Information Retrieval …...

AbstractThere is a rich flora of word space models that have proven their efficiency in many different applications including information retrieval (Dumais, 1988), word sense disambiguation (Schutze, 1992), various semantic …...

AbstractOrdinal regression which is known with learning to rank has long been used in information retrieval (IR). Learning to rank algorithms, have been tailored in document ranking, information filtering, and …...

AbstractRanking is used for a wide array of problems, most notably information retrieval (search). Kendall’s τ, Average Precision, and nDCG are a few popular approaches to the evaluation of ranking. …...

Ranking is an important task in the field of in- formation retrieval. Ranking may be used in different modules in natural language pro- cessing such as search engines. In this …...

This paper describes our IR (Information Re- trieval) based method for SemEval 2016 task 1, Semantic Textual Similarity (STS). The main feature of our approach is to extend a conventional …...

AbstractParsing Web information, namely parsing content to find relevant documents on the basis of a user’s query, represents a crucial step to guarantee fast and accurate Information Retrieval (IR). Generally, …...

AbstractWe present a WordNet like structured resource for slang words and neologisms on the internet. The dynamism of language is often an indication that current language technology tools trained on …...

AbstractAspect extraction identifies relevant features from a textual description of an entity, e.g., a phone, and is typically targeted to product descriptions, reviews, and other short texts as an enabling …...

AbstractWord Sense Disambiguation (WSD) is one of the open problems in the area of natural language processing. Various supervised, unsupervised and knowledge based approaches have been proposed for automatically determining …...

AbstractVideo event detection is a challenging problem in information and multimedia retrieval. Different from single action detection, event detection requires a richer level of semantic information from video. In order …...

AbstractVolatility prediction—an essential concept in financial markets—has recently been addressed using sentiment analysis methods. We investigate the sentiment of annual disclosures of companies in stock markets to forecast volatility. We …...

AbstractRecently, a significant number of studies have focused on neural information retrieval (IR) models. One category of works use unlabeled data to train general word embeddings based on term proximity, …...

This paper describes a small but unique digitized collection of medieval Latin charters. This collection consists of 57 charters of 7 types illustrating various purposes of issuance by the Royal …...

We propose approaches that use information retrieval methods for the automatic calculation of CO2-footprints of cooking recipes. A particular challenge is the “long tail problem” that arises with the large …...

AbstractTechnical support problems are very complex. In contrast to regular web queries (that contain few keywords) or factoid questions (which are a few sentences), these problems usually include attributes like …...

Smart solutions and solid solutions are two different approaches for computational linguistics. To receive a satisfactory result at a minimum cost, smart solutions use special properties of the on-hand application. …...

The European "Tenders Electronic Daily" (TED) is a large source of semi-structured and multilingual data that is very valuable to the Natural Language Processing community. This data sets can effectively …...

AbstractIn this paper, we propose a novel framework for sarcasm generation; the system takes a literal negative opinion as input and translates it into a sarcastic version. Our framework does …...

AbstractSemantic role labeling (SRL) is an important task for understanding natural languages, where the objective is to analyse propositions expressed by the verb and to identify each word that bears …...

AbstractWe present a novel approach to automatic question answering that does not depend on the performance of an information retrieval (IR) system and does not require that the training data …...

AbstractCalculating Semantic Textual Similarity (STS) plays a significant role in many applications such as question answering, document summarisation, information retrieval and information extraction. All modern state of the art STS …...

AbstractThe information revolution brought with it information pollution. Information retrieval and extraction help us cope with abundant information from diverse sources. But some sources are of anonymous authorship, and some …...

AbstractWe present HEAD-QA, a multi-choice question answering testbed to encourage research on complex reasoning. The questions come from exams to access a specialized position in the Spanish healthcare system, and …...

AbstractElectronic Health Records (EHRs) contain both structured content and unstructured (text) content about a patient’s medical history. In the unstructured text parts, there are common sections such as Assessment and …...

AbstractThis paper studies the problem of non-factoid question answering, where the answer may span over multiple sentences. Existing solutions can be categorized into representation- and interaction-focused approaches. We combine their …...

AbstractApplications such as machine translation, speech recognition, and information retrieval require efficient handling of noun compounds as they are one of the possible sources for out of vocabulary words. In-depth …...

AbstractIn politics, neologisms are frequently invented for partisan objectives. For example, “undocumented workers” and “illegal aliens” refer to the same group of people (i.e., they have the same denotation), but …...

AbstractGenerative models for Information Retrieval, where ranking of documents is viewed as the task of generating a query from a document’s language model, were very successful in various IR tasks …...

AbstractThe SARS-CoV-2 (COVID-19) pandemic spotlighted the importance of moving quickly with biomedical research. However, as the number of biomedical research papers continue to increase, the task of finding relevant articles …...

AbstractA promising application of AI to healthcare is the retrieval of information from electronic health records (EHRs), e.g. to aid clinicians in finding relevant information for a consultation or to …...

AbstractThe goal of this work is to build conversational Question Answering (QA) interfaces for the large body of domain-specific information available in FAQ sites. We present DoQA, a dataset with …...

AbstractNeural approaches to learning term embeddings have led to improved computation of similarity and ranking in information retrieval (IR). So far neural representation learning has not been extended to meta-textual …...

AbstractRecently, pre-trained language models such as BERT have shown state-of-the-art accuracies in text matching. When being applied to IR (or QA), the BERT-based matching models need to online calculate the …...

AbstractLearning to interview patients to find out their disease is an essential part of the training of medical students. The practical part of this training has traditionally relied on paid …...

AbstractExisting machine reading comprehension (MRC) models do not scale effectively to real-world applications like web-level information retrieval and question answering (QA). We argue that this stems from the nature of …...

AbstractNamed entity disambiguation is an important task that plays the role of bridge between text and knowledge. However, the performance of existing methods drops dramatically for short text, which is …...

AbstractInformation retrieval (IR) for precision medicine (PM) often involves looking for multiple pieces of evidence that characterize a patient case. This typically includes at least the name of a condition …...

AbstractThe key to effortless end-user programming is natural language. We examine how to teach intelligent systems new functions, expressed in natural language. As a first step, we collected 3168 samples …...

AbstractResearch on the application of NLP in symbol-based Augmentative and Alternative Communication (AAC) tools for improving social interaction support is scarce. We contribute a novel method for generating context-related vocabulary …...

AbstractPassage retrieval and ranking is a key task in open-domain question answering and information retrieval. Current effective approaches mostly rely on pre-trained deep language model-based retrievers and rankers. These methods …...

AbstractWith the need of fast retrieval speed and small memory footprint, document hashing has been playing a crucial role in large-scale information retrieval. To generate high-quality hashing code, both semantics …...

AbstractUnsupervised representation learning of words from large multilingual corpora is useful for downstream tasks such as word sense disambiguation, semantic text similarity, and information retrieval. The representation precision of log-bilinear …...

AbstractIdentifying whether a word carries the same meaning or different meaning in two contexts is an important research area in natural language processing which plays a significant role in many …...

AbstractThis paper presents a novel framework for reconstructing multi-hop explanations in science Question Answering (QA). While existing approaches for multi-hop reasoning build explanations considering each question in isolation, we propose …...

AbstractDense passage retrieval has been shown to be an effective approach for information retrieval tasks such as open domain question answering. Under this paradigm, a dual-encoder model is learned to …...

AbstractAsymmetric text matching has becoming increasingly indispensable for many downstream tasks (e.g., IR and NLP). Here, asymmetry means that the documents involved for matching hold different amounts of information, e.g., …...

AbstractThe goal of an information retrieval system is to retrieve documents that are most relevant to a given user query from a huge collection of documents, which usually requires time-consuming …...

AbstractSpelling correction utilities have become commonplace during the writing process, however, many spelling correction utilities suffer due to the size and quality of dictionaries available to aid correction. Many terms, …...

AbstractMany clinical informatics tasks that are based on electronic health records (EHR) need relevant patient cohorts to be selected based on findings, symptoms and diseases. Frequently, these conditions are described …...

We study the information retrieval task to identify the relevant law articles for a query on a legal issue in when the legal system in question is statute law. In …...

AbstractWord embeddings (Mikolov et al., 2013; Pennington et al., 2014) have been used to bolster the performance of natural language processing systems in a wide variety of tasks, including information …...

AbstractThis paper describes the first experiments towards tracking the complex and international network of text reuse within the Early Modern (XV-XVII centuries) community of Neo-Latin humanists. Our research, conducted within …...

AbstractIR models using a pretrained language model significantly outperform lexical approaches like BM25. In particular, SPLADE, which encodes texts to sparse vectors, is an effective model for practical use because …...

AbstractMany text generation applications require the generated text to be factually consistent with input information. Automatic evaluation of factual consistency is challenging. Previous work has developed various metrics that often …...

AbstractModern machine learning relies on datasets to develop and validate research ideas. Given the growth of publicly available data, finding the right dataset to use is increasingly difficult. Any research …...

AbstractIn this paper, we propose Vocab-Expander at https://vocab-expander.com, an online tool that enables end-users (e.g., technology scouts) to create and expand a vocabulary of their domain of interest. It utilizes …...

AbstractLong-form question answering (LFQA) aims at answering complex, open-ended questions with detailed, paragraph-length responses. The de facto paradigm of LFQA necessitates two procedures: information retrieval, which searches for relevant supporting …...