Examining the information retrieval process from an inductive perspective

Term-weighting functions derived from various models of retrieval aim to model human notions of relevance more accurately. However, there is a lack of analysis of the sources of evidence from which important features of these term weighting schemes originate. In general, features pertaining to these term-weighting schemes can be collected from (1) the document, (2) the entire collection and (3) the query. In this work, we perform an empirical analysis to determine the increase in effectiveness as information from these three different sources becomes more accurate. First, we determine the number of documents to be indexed to accurately estimate collection-wide features to obtain near optimal effectiveness for a range of a term-weighting functions. Similarly, we determine the amount of a document and query that must be sampled to achieve near-peak effectiveness. This analysis also allows us to determine the factors that contribute most to the performance of a termweighting function...

• Type: Journal
• Year: 2010
• Where: CIKM
• Authors: Ronan Cummins, Mounia Lalmas, Colm O'Riordan
• Keywords: CIKM 2010, Document, Information Technology, Term-weighting Function, Term-weighting Schemes