Identifying Novel Information using latent Semantic Analysis in the WiQA Task at CLEF 2006

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F07%3A00502230" target="_blank" >RIV/49777513:23520/07:00502230 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Identifying Novel Information using latent Semantic Analysis in the WiQA Task at CLEF 2006

Popis výsledku v původním jazyce

In our two-stage system for the English monolingual WiQA Task, snippets were first retrieved if they contained an exact match with the title. Candidates were then passed to the Latent Semantic Analysis component which judged them Novel if their match with the article text was less than a threshold. In Run 1, the ten best swnippes were returned and in Run 2 the twenty best. Run 1 was superior, with Average Yield per Topic 2.46 and Precision 0.37. Compared to other groups, our performance was in the middle of the range excerpt for Precision where our system was the best. We attribute this to our use of exact title matches in the IR stage. In future work we will vary the approach used depending on the topic type, exploit co-references in conjuction with exact matches and make use of the elaborate hyperlink stucture which is a unique and most interesting aspect of the Wikipedia.

Název v anglickém jazyce

Identifying Novel Information using latent Semantic Analysis in the WiQA Task at CLEF 2006

Popis výsledku anglicky

In our two-stage system for the English monolingual WiQA Task, snippets were first retrieved if they contained an exact match with the title. Candidates were then passed to the Latent Semantic Analysis component which judged them Novel if their match with the article text was less than a threshold. In Run 1, the ten best swnippes were returned and in Run 2 the twenty best. Run 1 was superior, with Average Yield per Topic 2.46 and Precision 0.37. Compared to other groups, our performance was in the middle of the range excerpt for Precision where our system was the best. We attribute this to our use of exact title matches in the IR stage. In future work we will vary the approach used depending on the topic type, exploit co-references in conjuction with exact matches and make use of the elaborate hyperlink stucture which is a unique and most interesting aspect of the Wikipedia.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2007

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Evaluation of Multilingual and Multi-modal Information Retrieval

ISBN

978-3-540-74998-1

ISSN

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e-ISSN

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Počet stran výsledku

9

Strana od-do

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Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Alicante

Datum konání akce

22. 9. 2006

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000250568000066