Abstract
Fresh information is important for real business. 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
