Application of keyword map-based relevance feedback to interactive blog search
Yasufumi Takama, Tomoki Kajinami, Akio Matsumura · 2005
There exists vast amount of information in the Web, from which users usually gather information without definite information needs. The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for users' information needs. Although this approach is effective when the assumption that a user has concrete criteria on the relevance of retrieved documents is valid, it is expected that this assumption cannot always hold when searching Blog, which consists of vast number of short articles about various topics. In particular, it is assumed that a user is exploring the Blog space while having multiple interests at the same time. In this paper, keyword map-based relevance feedback is applied to interactive Blog search. Compared with the previous work on keyword map-based relevance feedback, the proposed algorithm can consider multiple topics, in which a user is interested on the keyword map.