Click data as implicit feedback in web search Public Deposited

http://ir.library.oregonstate.edu/concern/defaults/1c18dg662

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • Search sessions consist of a person presenting a query to a search engine, followed by that person examining the search results, selecting some of those search results for further review, possibly following some series of hyperlinks, and perhaps backtracking to previously viewed pages in the session. The series of pages selected for viewing in a search session, sometimes called the click data, is intuitively a source of relevance feedback information to the search engine. We are interested in how that relevance feedback can be used to improve the search results quality for all users, not just the current user. For example, the search engine could learn which documents are frequently visited when certain search queries are given. In this article, we address three issues related to using click data as implicit relevance feedback: (1) How click data beyond the search results page might be more reliable than just the clicks from the search results page; (2) Whether we can further subselect from this click data to get even more reliable relevance feedback; and (3) How the reliability of click data for relevance feedback changes when the goal becomes finding one document for the user that completely meets their information needs (if possible). We refer to these documents as the ones that are strictly relevant to the query. Our conclusions are based on empirical data from a live website with manual assessment of relevance. We found that considering all of the click data in a search session as relevance feedback has the potential to increase both precision and recall of the feedback data. We further found that, when the goal is identifying strictly relevant documents, that it could be useful to focus on last visited documents rather than all documents visited in a search session.
Resource Type
Date Available
Date Issued
Citation
  • Information Processing & Management. 43 (3): 791-807
Non-Academic Affiliation
Series
Keyword
Rights Statement
Funding Statement (additional comments about funding)
Publisher
Language
File Format
File Extent
  • 1070057 bytes
Replaces
Additional Information
  • description.provenance : Approved for entry into archive by Jeanne Davidson(jeanne.davidson@oregonstate.edu) on 2007-01-29T16:52:30Z (GMT) No. of bitstreams: 1 Jung-IPM-2007.pdf: 1070057 bytes, checksum: d24e30684ed900ee5fe7984b250af724 (MD5)
  • description.provenance : Submitted by Janet Webster (janet.webster@oregonstate.edu) on 2007-01-29T16:47:36Z No. of bitstreams: 1 Jung-IPM-2007.pdf: 1070057 bytes, checksum: d24e30684ed900ee5fe7984b250af724 (MD5)
  • description.provenance : Made available in DSpace on 2007-01-30T17:14:29Z (GMT). No. of bitstreams: 1 Jung-IPM-2007.pdf: 1070057 bytes, checksum: d24e30684ed900ee5fe7984b250af724 (MD5) Previous issue date: 2007-05
ISSN
  • 0306-4573

Relationships

Parents:

This work has no parents.

Last modified

Downloadable Content

Download PDF

Items