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A Grammatical Approach to the Extraction of Index Terms

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TLDR
This article proposes to apply shallow parsing, implemented by means of cascades of finite-state transducers, to extract complex index terms based on an approximate grammar of Spanish to improve the effectiveness of the index terms extracted.
Abstract
The extraction of the keywords that characterize each document in a given collection is one of the most important components of an Information Retrieval system. In this article, we propose to apply shallow parsing, implemented by means of cascades of finite-state transducers, to extract complex index terms based on an approximate grammar of Spanish. The effectiveness of the index terms extracted has been evaluated through the CLEF collection.

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BookDOI

Comparative Evaluation of Multilingual Information Access Systems

TL;DR: The paper discusses the evaluation approach adopted, describes the tracks and tasks offered and the test collections used, and provides an outline of the guidelines given to the participants.

COLE experiments at CLEF 2002 Spanish monolingual track

TL;DR: The authors applied Natural Language Processing techniques for single word and multi-word term conflation in the CLEF 2013 CLEF workshop on Semantic Semantic Conflusion (SemEval 2013).
Book ChapterDOI

COLE Experiments at CLEF 2003 in the Spanish Monolingual Track

TL;DR: This work has continued applying Natural Language Processing techniques for single word and multi-word term conflation with the employment of syntactic dependencies as complex index terms, in an attempt to solve the problems derived from syntactic variation.

COLE experiments at CLEF 2003 Spanish monolingual track

TL;DR: This paper applied Natural Language Processing techniques for single word and multi-word term conflation in Spanish monolingual Spanish monolinguistic track, using a shallow parser based on cascades of finite-state transducers.
Journal Article

Morphological and syntactic processing for text retrieval

TL;DR: This paper described the application of lemmatization and shallow parsing as a linguistically-based alternative to stemming in Text Retrieval, with the aim of managing linguistic variation at both word level and phrase level.
References
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Journal ArticleDOI

Partial parsing via finite-state cascades

TL;DR: Deterministic parsers specified by finite state cascades may be more accurate than exhaustive search stochastic context free parsers and extended at modest cost to construct parse trees with finite feature structures.
Book ChapterDOI

NLP for Term Variant Extraction: Synergy Between Morphology, Lexicon, and Syntax

TL;DR: A natural language processing (NLP) approach to automatic indexing over controlled vocabulary which accounts for term variation is presented, applied to the French language.
Proceedings Article

Xerox TREC-5 site report : Routing, filtering, NLP, and Spanish tracks

TL;DR: Xerox participated in TREC-5 through experiments carried out separately and conjointly at the Ranx Xerox Research Centre in Grenoble and the Xerox Palo Alto Research Center, and the work on routing and filtering.
Book ChapterDOI

Comparing the Effect of Syntactic vs. Statistical Phrase Indexing Strategies for Dutch

TL;DR: The results showed that the at least need a compound splitting algorithm for good quality retrieval for Dutch texts, since a purely non-linguistic indexing strategy, with or without phrases, does not seem to be very effective for Dutch.