Learning features through feedback for blog distillation

Dehong Gao, Renxian Zhang, Wenjie Li, Yiu Keung Lau, Kam Fai Wong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

The paper is focused on blogosphere research based on the TREC blog distillation task, and aims to explore unbiased and significant features automatically and efficiently. Feedback from faceted feeds is introduced to harvest relevant features and information gain is used to select discriminative features. The evaluation result shows that the selected feedback features can greatly improve the performance and adapt well to the terabyte data.
Original languageEnglish
Title of host publicationSIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages1085-1086
Number of pages2
DOIs
Publication statusPublished - 1 Sep 2011
Event34th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'11 - Beijing, China
Duration: 24 Jul 201128 Jul 2011

Conference

Conference34th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'11
CountryChina
CityBeijing
Period24/07/1128/07/11

Keywords

  • Blog distillation
  • Faceted distillation
  • Feedback

ASJC Scopus subject areas

  • Information Systems

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