On the value of temporal information in information retrieval

Author:

Alonso Omar1,Gertz Michael1,Baeza-Yates Ricardo2

Affiliation:

1. University of California at Davis, Davis, CA

2. Yahoo! Research Barcelona, Spain

Abstract

Time is an important dimension of any information space and can be very useful in information retrieval. Current information retrieval systems and applications do not take advantage of all the time information available in the content of documents to provide better search results and user experience. In this paper we show some of the areas that can benefit from exploiting such temporal information.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Management Information Systems

Reference14 articles.

1. Temporal summaries of new topics

2. Clustering of search results using temporal attributes

3. Google Timeline http://www.google.com/experimental/ Google Timeline http://www.google.com/experimental/

4. GUTime http://complingone.georgetown.edu/~linguist GUTime http://complingone.georgetown.edu/~linguist

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