Towards Real Intelligent Web Exploration

A significant problem of the dominant web search model is the lack of a realistic way to acquire user search context. Search engines use implicit feedback, which is extremely sparse and does not allow users to properly define what they want to know, or what they think of search results. In our proposed “web exploration engine” documents have been automatically pre-classified into a large number of categories representing a hierarchy of search contexts. Users can browse this structure or search within a particular category (context). Search is truly “local” as keyword relevance is not global but specific to the category. The main innovation we propose is the “floating” query resulting from this feature: the original search query is re-evaluated and the importance of its features re-calculated for every search context the user explores. Additionally, users can provide explicit feedback, which automatically modifies the search query.

This article was submitted to the 12th International Conference on Web Information System Engineering (WISE 2011) in Sydney, Australia (13-14 October 2011).

Download PDF version: Towards Real Intelligent Web Exploration (14 pages).

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