Interleaved Retrieval of Documents and Diagnostic Trees for Self Help Portals

Self help portals are online portals for product sales and customer support. Today, consumers can resolve most of their problems pertaining to a product by accessing information from these portals. The information on self help portals is often organized as solution documents and diagnostic trees. A diagnostic tree encodes the diagnostic steps for iteratively narrowing down the scope of user's problem and then eventually presenting the most relevant set of solution documents to the user. Typically, search is enabled only for solution documents. In this paper, we present algorithms for unified, interleaved retrieval of solution documents and diagnostic trees that can lead to more efficient resolution of user problems, especially when users' queries are imprecise. We show that interleaved retrieval of documents and diagnostic trees leads to an improvement up to 10% in precision for help desk queries in a selected help desk topic.

By: Dinesh Garg, Nanda Kambhatla, Gopal Pingali

Published in: RI08008 in 2008


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