Kshitij: A Search and Page Recommendation System for Wikipedia

Semantic information helps in identifying the context of a document. It will be interesting to find out how effectively this information can be used in recommending related documents in a partially annotated knowledge base such as Wikipedia. In this paper, we present a generic recommendation system that utilizes the stored as well as dynamically extracted semantics from Wikipedia. The system generates two kinds of recommendations - for search results and for each page viewed by the user. It explores different meta-information such as links and categories in this process. Our experiments show that the system is able to yield good quality recommendations and help in improving the user experience. Though the algorithms are tested on Wikipedia, external systems that do not have access to structured data can benefit from the recommendations.

• Type: Conference
• Year: 2008
• Where: COMAD
• Authors: Phanikumar Bhamidipati, Kamalakar Karlapalem
• Keywords: COMAD 2008, Generic Recommendation, Knowledge Base, Knowledge Management, Semantic Information