How do named entities contribute to retrieval effectiveness?

Authors:
Thomas Mandl;Christa Womser-Hacker
Affiliations:
Information Science, University of Hildesheim, Hildesheim, Germany;Information Science, University of Hildesheim, Hildesheim, Germany
Venue:
CLEF'04 Proceedings of the 5th conference on Cross-Language Evaluation Forum: multilingual Information Access for Text, Speech and Images
Year:
2004

Citing 5
Cited 5

Predicting query performance

SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
The effect of topic set size on retrieval experiment error

SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Topic structure modeling

SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Multilingual Topic Generation within the CLEF 2001 Experiments

CLEF '01 Revised Papers from the Second Workshop of the Cross-Language Evaluation Forum on Evaluation of Cross-Language Information Retrieval Systems
Cross-Language Evaluation Forum: Objectives, Results, Achievements

Information Retrieval

"They Are Out There, If You Know Where to Look": Mining Transliterations of OOV Query Terms for Cross-Language Information Retrieval

ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
MINT: a method for effective and scalable mining of named entity transliterations from large comparable corpora

EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Compositional Machine Transliteration

ACM Transactions on Asian Language Information Processing (TALIP)
Everybody loves a rich cousin: an empirical study of transliteration through bridge languages

HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Transliteration equivalence using canonical correlation analysis

ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval

Quantified Score

Hi-index	0.00

Visualization

Abstract

The search for features in topics and queries relevant for the performance in information retrieval is an important strategy for system optimization. Named entities in topics are a significant feature contributing to the quality of the retrieval results. In this contribution, we present an analysis on the correlation between the number of named entities present in a topic formulation and the final retrieval quality for these topics by retrieval systems within CLEF. The analysis includes the results of CLEF 2004. We found that a medium positive correlation exists for German, English and Spanish topics. Furthermore, the effect of the document or target language on the retrieval quality is also investigated.