To make web search more effective, we address the problem of articulating a user?s information needs more effectively. This is done in an iterative way, by allowing the user to provide relevance feedback regarding individual segments of retrieved Web-pages. Previously applied methods are limited to discovering ?general importance values of segments? (based on the authors? ?objective views? i.e., main topics) rather than ?subjective importance values of segments? (based on a user?s ?subjective view? i.e., personal information needs).

In this paper, a user?s interests are incrementally identified by allowing the user to iteratively select relevant keywords or phrases from a set of system-recommended candidate-keywords and candidate-phrases (i.e., pseudo-relevance feedback). It makes it possible to discover ?subjective importance values of segments? that can be dynamically changed by the user by indicating their interests regarding retrieved Web-pages. The important segments, selected by the user, provide higher precision of pseudo-relevance feedback for further Web Information Retrieval purposes.