UNED at WebCLEF 2008: applying high restrictive summarization, low restrictive information retrieval and multilingual techniques

Authors:
Enrique Amigó;Juan Martinez-Romo;Lourdes Araujo;Víctor Peinado
Affiliations:
NLP & IR Group at UNED, ETSI Informática, UNED, Madrid, Spain;NLP & IR Group at UNED, ETSI Informática, UNED, Madrid, Spain;NLP & IR Group at UNED, ETSI Informática, UNED, Madrid, Spain;NLP & IR Group at UNED, ETSI Informática, UNED, Madrid, Spain
Venue:
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Year:
2008

Citing 3
Cited 0

An empirical study of information synthesis tasks

ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Using syntactic information to extract relevant terms for multi-document summarization

COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Using Centrality to Rank Web Snippets

Advances in Multilingual and Multimodal Information Retrieval

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes our participation in the WebCLEF 2008 task, targeted at snippet retrieval from new data. Our system assumes that the task can be tackled as a summarization problem and that the document retrieval and multilinguism treatment steps can be ignored. Our approach assumes also that the redundancy of information in the Web allows the system to be very restrictive when picking information pieces. Our evaluation results suggest that, while the first assumption is feasible, the second one is not always true.