A Probabilistic Retrieval Model for Semistructured Data

  • Authors:
  • Jinyoung Kim;Xiaobing Xue;W. Bruce Croft

  • Affiliations:
  • Center for Intelligent Information Retrieval Department of Computer Science, University of Massachusetts Amherst,;Center for Intelligent Information Retrieval Department of Computer Science, University of Massachusetts Amherst,;Center for Intelligent Information Retrieval Department of Computer Science, University of Massachusetts Amherst,

  • Venue:
  • ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Retrieving semistructured (XML) data typically requires either a structured query such as XPath, or a keyword query that does not take structure into account. In this paper, we infer structural information automatically from keyword queries and incorporate this into a retrieval model. More specifically, we propose the concept of a mapping probability, which maps each query word into a related field (or XML element). This mapping probability is used as a weight to combine the language models estimated from each field. Experiments on two test collections show that our retrieval model based on mapping probabilities outperforms baseline techniques significantly.