Expert discovery: A web mining approach

Expert discovery is a quest in search of finding an answer to a question: Who is the best expert of a specific subject in a particular domain within a peculiar array of parameters? Expert with domain knowledge in any fields is crucial for consulting in industry, academia and scientific community. Aim of this study is to address the issues for expert-finding task in real-world community. Collaboration with expertise is critical requirement in business corporate, such as in fields of engineering, geographies, bio-informatics, and medical domains. We have proposed multifaceted web mining heuristic that results into the design and development of a tool using data from Growbag, dblpXML with Authors home pages resource to find people of desired expertise. We mined more than 2,500 Author's web pages based on the credibility of 12 key parameters while parsing on each page for a large number of co-occurred keyword and all available general terms. It presents evidence to validate this quantification as a measure of expertise. The prototype enables users easily to distinguish someone, who has briefly worked in a particular area with more extensive experience, resulting in the capability to locate people with broader expertise through large parts of the product. Through this extension to the web enabling methodology, we have shown that the implemented tool delivers a novel web mining idea with improved results

Expert discovery: A web mining approach Keywords:

Web mining , multifaceted , social computing , expert discovery , high profile , higher order co-occurrence