Adaptive calculation of scores for fresh information retrieval

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 FTFIDF for fresh information retrieval. FTF·IDF extends TF·IDF by means of using FTF(fresh term frequency) instead of TF(term frequency). FTP differs from TF because FTP decreases as time goes. The speed of decreasing FTP 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.