A Grid-enabled framework of expertise search engine using Web-based online communities

Existing search engines like Google, Yahoo!, Live etc. are not yet capable to answer queries that require deep semantic understanding of the query or the document. Instead, it is preferable to find and ask someone who has related expertise or experience on a topic and thus Web-based online communities have become important places for people to seek and share expertise. We need to gather the data that describes these online communities. But extracting, aggregating and analyzing data from these communities for finding experts on a single framework is a challenging task. Also there is no universal standard data structure for the outline of user participation in these communities. In this paper, we present a Grid-enabled framework of expertise search (GREFES) engine which utilizes online communities as sources for experts on various topics. This is a work in progress. We also propose an open data structure called SNML (Social Network Markup Language) to outline user participation in online communities. The architecture addresses major challenges in crawling of community data and query processing by utilizing Grid. An expert ranking algorithm is also discussed and evaluated.