Adaptive Calculation of Scores for Fresh Information Retrieval

  • Authors:

  • Minoru UEHARA;Nobuyoshi SATO;Yoshifumi SAKAI

  • Affiliations:

  • Department of Information and Computer Sciences, Toyo University, Kawagoe, Saitama 350-8585 Japan;Plant Regulation Research Center, Toyo University, Itakura-machi, Gunma 372-0193 Japan;Graduate School of Agricultural Science, Tohoku University, Sendai, Miyagi 981-8555 Japan

  • Venue:
  • ICPADS '05 Proceedings of the 11th International Conference on Parallel and Distributed Systems - Volume 01
  • Year:
  • 2005

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Abstract

In business, we need fresh information. In order to realize fresh information retrieval, we need not only to collect documents in a short time, but also to rank the results in the suitable order. However, conventional ranking methods are not suited for fresh information retrieval because they ignore temporal value of information. So, we have proposed the novel ranking method FTF IDF for fresh information retrieval. FTF IDF extends TF IDF by means of using FTF(fresh term frequency) instead of TF(term frequency). FTF differs from TF because FTF decreases as time goes. The speed of decreasing FTF is determined by the dumping factor. The dumping factor is sensitive against small changes of documents. So, we use a threshold to ignore such small changes. In some papers we published, we detect the optimal threshold manually. In this paper, we proposed an adaptive calculating method in order to detect threshold automatically. In this method, the optimal value is determined by iterating to test generated thresholds. In this paper, we describe our method and its evaluation.