Component Ranking and Automatic Query Refinement for XML Retrieval

Queries over XML documents challenge search engines to return the most relevant XML components that satisfy the query concepts. In a previous work[6] we described an algorithm to retrieve the most relevant XML components that performed relatively well in INEX'03. In this paper we show an improvement to that algorithm by introducing a document pivot that compensates for missing terms statistics in small components. Using this new algorithm we achieved improvements of 30%-50% in the Mean Average Precision over the previous algorithm. We then describe a general mechanism to apply existing Automatic Query Refinement (AQR) methods on top of our XML retrieval algorithm and demonstrate a particular such method that achieved top results in INEX'04. Keywords XML Search, Information Retrieval, Vector Space Model, Automatic Query Refinement.

• Type: Conference
• Year: 2004
• Where: INEX
• Authors: Yosi Mass, Matan Mandelbrod
• Keywords: Algorithm, Automatic Query Refinement, INEX 2004, Information Management, Relevant Xml Components