Integrating Query Performance Prediction in Term Scoring for Diachronic Thesaurus

Chaya Liebeskind; Ido Dagan

doi:10.18653/v1/w15-3714

Integrating Query Performance Prediction in Term Scoring for Diachronic Thesaurus

Chaya Liebeskind
, Ido Dagan

Department of Computer Science and Artificial Intelligence

Bar-Ilan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

A diachronic thesaurus is a lexical resource that aims to map between modern terms and their semantically related terms in earlier periods. In this paper, we investigate the task of collecting a list of relevant modern target terms for a domain-specific diachronic thesaurus. We propose a supervised learning scheme, which integrates features from two closely related fields: Terminology Extraction and Query Performance Prediction (QPP). Our method further expands modern candidate terms with ancient related terms, before assessing their corpus relevancy with QPP measures. We evaluate the empirical benefit of our method for a thesaurus for a diachronic Jewish corpus. c 2015 Association for Computational Linguistics and The Asian Federation of Natural Language Processing.

Original language	American English
Title of host publication	LaTeCH 2015
Editors	Kalliopi A. Zervanou, Marieke van Erp, Beatrice Alex
Publisher	Association for Computational Linguistics (ACL)
Pages	89-94
Number of pages	6
ISBN (Electronic)	9781941643631
DOIs	https://doi.org/10.18653/v1/w15-3714
State	Published - 1 Jul 2015
Event	9th SIGHUM Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, LaTeCH 2015 - Beijing, China Duration: 30 Jul 2015 → …

Publication series

Name	ACL Anthology

Conference

Conference	9th SIGHUM Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, LaTeCH 2015
Country/Territory	China
City	Beijing
Period	30/07/15 → …

Bibliographical note

Publisher Copyright:
© 2015 Proceedings of the Annual Meeting of the Association for Computational Linguistics.

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10.18653/v1/w15-3714

https://www.aclweb.org/anthology/W15-3714.pdfLicense: CC BY

Cite this

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title = "Integrating Query Performance Prediction in Term Scoring for Diachronic Thesaurus",

abstract = "A diachronic thesaurus is a lexical resource that aims to map between modern terms and their semantically related terms in earlier periods. In this paper, we investigate the task of collecting a list of relevant modern target terms for a domain-specific diachronic thesaurus. We propose a supervised learning scheme, which integrates features from two closely related fields: Terminology Extraction and Query Performance Prediction (QPP). Our method further expands modern candidate terms with ancient related terms, before assessing their corpus relevancy with QPP measures. We evaluate the empirical benefit of our method for a thesaurus for a diachronic Jewish corpus. c 2015 Association for Computational Linguistics and The Asian Federation of Natural Language Processing.",

author = "Chaya Liebeskind and Ido Dagan",

note = "Publisher Copyright: {\textcopyright} 2015 Proceedings of the Annual Meeting of the Association for Computational Linguistics.; 9th SIGHUM Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, LaTeCH 2015 ; Conference date: 30-07-2015",

year = "2015",

month = jul,

day = "1",

doi = "10.18653/v1/w15-3714",

language = "American English",

series = "ACL Anthology",

publisher = "Association for Computational Linguistics (ACL)",

pages = "89--94",

editor = "Zervanou, \{Kalliopi A.\} and \{van Erp\}, Marieke and Beatrice Alex",

booktitle = "LaTeCH 2015",

address = "United States",

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Liebeskind, C & Dagan, I 2015, Integrating Query Performance Prediction in Term Scoring for Diachronic Thesaurus. in KA Zervanou, M van Erp & B Alex (eds), LaTeCH 2015. ACL Anthology, Association for Computational Linguistics (ACL), pp. 89-94, 9th SIGHUM Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, LaTeCH 2015, Beijing, China, 30/07/15. https://doi.org/10.18653/v1/w15-3714

Integrating Query Performance Prediction in Term Scoring for Diachronic Thesaurus. / Liebeskind, Chaya; Dagan, Ido.
LaTeCH 2015. ed. / Kalliopi A. Zervanou; Marieke van Erp; Beatrice Alex. Association for Computational Linguistics (ACL), 2015. p. 89-94 (ACL Anthology).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - A diachronic thesaurus is a lexical resource that aims to map between modern terms and their semantically related terms in earlier periods. In this paper, we investigate the task of collecting a list of relevant modern target terms for a domain-specific diachronic thesaurus. We propose a supervised learning scheme, which integrates features from two closely related fields: Terminology Extraction and Query Performance Prediction (QPP). Our method further expands modern candidate terms with ancient related terms, before assessing their corpus relevancy with QPP measures. We evaluate the empirical benefit of our method for a thesaurus for a diachronic Jewish corpus. c 2015 Association for Computational Linguistics and The Asian Federation of Natural Language Processing.

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Integrating Query Performance Prediction in Term Scoring for Diachronic Thesaurus

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