Syntagmatic and paradigmatic representations of term variation

Jacquemin, Christian

doi:10.3115/1034678.1034733

Cited by 61 publications

(48 citation statements)

References 5 publications

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“…In any case, they do not "change" the meaning as they refer to the same concept. Daille et al (1996) and Jacquemin (1999Jacquemin ( , 2001 further identified types of variation that modified the meaning of terms.…”

Section: Introductionmentioning

confidence: 99%

Enhancing automatic term recognition through recognition of variation

Nenadié

Ananiadou

McNaught

2004

Proceedings of the 20th International Conference on Computational Linguistics - COLING '04

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Terminological variation is an integral part of the linguistic ability to realise a concept in many ways, but it is typically considered an obstacle to automatic term recognition (ATR) and term management. We present a method that integrates term variation in a hybrid ATR approach, in which term candidates are recognised by a set of linguistic filters and termhood assignment is based on joint frequency of occurrence of all term variants. We evaluate the effectiveness of incorporating specific types of term variation by comparing it to the performance of a baseline method that treats term variants as separate terms. We show that ATR precision is enhanced by considering joint termhoods of all term variants, while recall benefits by the introduction of new candidates through consideration of different variation types. On a biomedical test corpus we show that precision can be increased by 20-70% for the top ranked terms, while recall improves generally by 2-25%.

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Section: Introductionmentioning

confidence: 99%

Enhancing automatic term recognition through recognition of variation

Nenadié

Ananiadou

McNaught

2004

Proceedings of the 20th International Conference on Computational Linguistics - COLING '04

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“…Even so, real improvements are usually obtained only for incomplete and relatively short queries (Voorhees, 1994). One possibility consists in working with phrase-level semantic variation (Jacquemin, 1999), which reduces the problem of word-sense ambiguity because of the existence of a context in the complex term itself. Moreover, it would be possible to employ a fuzzy notion of synonymy which measures the degree of synonymy between two terms (Sobrino et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

Extraction of complex index terms in non-English IR: A shallow parsing based approach

Vilares

Alonso

Vilares

2008

Information Processing & Management

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The performance of Information Retrieval systems is limited by the linguistic variation present in natural language texts. Word-level Natural Language Processing techniques have been shown to be useful in reducing this variation. In this article, we summarize our work on the extension of these techniques for dealing with phrase-level variation in European languages, taking Spanish as a case in point. We propose the use of syntactic dependencies as complex index terms in an attempt to solve the problems deriving from both syntactic and morpho-syntactic variation and, in this way, to obtain more precise index terms. Such dependencies are obtained through a shallow parser based on cascades of finite-state transducers in order to reduce as far as possible the overhead due to this parsing process. The use of different sources of syntactic information, queries or documents, has been also studied, as has the restriction of the dependencies applied to those obtained from noun phrases. Our approaches have been tested using the CLEF corpus, obtaining consistent improvements with regard to classical word-level non-linguistic techniques. Results show, on the one hand, that syntactic information extracted from documents is more useful than that from queries. On the other hand, it has been demonstrated that by restricting dependencies to those corresponding to noun phrases, important reductions of storage and management costs can be achieved, albeit at the expense of a slight reduction in performance.

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“…This set of documents is then processed by a third module, made of FASTR (Jacquemin, 1999), a shallow transformational natural language analyser and of a ranker. This module can select, among documents found by the search engine, a subset that satisfies more refined criteria.…”

Section: Selection Of Relevant Documentsmentioning

confidence: 99%

“…The original terms are extracted from the questions. The tool used for extracting text sequences that correspond to occurrences or variants of these terms is FASTR (Jacquemin, 1999). The ranking of the documents relies on a weighted combination of the terms and variants extracted from the documents.…”

Section: Document Ranking Evaluationmentioning

confidence: 99%

Two levels of evaluation in a complex NL system

Berthelin

Grau

Hurault-Plantet

2001

Proceedings of the Workshop on Evaluation for Language and Dialogue Systems -

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The QALC question-answering system, developed at LIMSI, has been a participant for two years in the QA track of the TREC conference. In this paper, we present a quantitative evaluation of various modules in our system, based on two criteria: first, the numbers of documents containing the correct answer and selected by the system; secondly, the number of answers found. The first criterion is used for evaluating locally the modules in the system, which contribute in selecting documents that are likely to contain the answer. The second one provides a global evaluation of the system. As such, it also serves for an indirect evaluation of various modules.

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Syntagmatic and paradigmatic representations of term variation

Cited by 61 publications

References 5 publications

Enhancing automatic term recognition through recognition of variation

Enhancing automatic term recognition through recognition of variation

Extraction of complex index terms in non-English IR: A shallow parsing based approach

Two levels of evaluation in a complex NL system

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