Detecting Document Genre for Personalization of Information Retrieval

Authors:
Gheorghe Muresan;Catherine L. Smith;Michael Cole;Lu Liu;Nicholas J. Belkin
Affiliations:
Rutgers University;Rutgers University;Rutgers University;Rutgers University;Rutgers University
Venue:
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 03
Year:
2006

Citing 0
Cited 4

Towards genre classification for IR in the workplace

IIiX Proceedings of the 1st international conference on Information interaction in context
Classifying web genres in context: A case study documenting the web genres used by a software engineer

Information Processing and Management: an International Journal
Inferring document utility via a decision-making based retrieval model

International Journal of Knowledge-based and Intelligent Engineering Systems
Testing a genre-enabled application: a preliminary assessment

FDIA'08 Proceedings of the 2nd BCS IRSG conference on Future Directions in Information Access

Quantified Score

Hi-index	0.00

Visualization

Abstract

We report on the effectiveness of language models for personalization of retrieval results based on a searcher's preference for document genre. In principle, such preferences can be obtained via implicit relevance feedback through the observation of the searcher's actions and behavior during search sessions. While our approach did not produce significant improvement to retrieval effectiveness, the methodology and experimental setting can and are being used for further work on exploring genre-based personalization.