Effective and efficient structured retrieval

  • Authors:

  • Le Zhao;Jamie Callan

  • Affiliations:

  • Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA

  • Venue:
  • Proceedings of the 18th ACM conference on Information and knowledge management
  • Year:
  • 2009

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Abstract

Search engines that support structured documents typically support structure created by the author (e.g., title, section), and may also support structure added by an annotation process (e.g., part of speech, named entity, semantic role). Exploiting such structure can be difficult. Query structure may fail to match structure in a relevant document for a variety of reasons, thus structured queries, although containing more information than keyword queries, are often less effective than unstructured queries. This paper studies retrieval of sentences with annotations for a question answering task. Three problems of structured retrieval are identified and solutions proposed. Structural mismatch is addressed by query structure expansion of predicted relevant structures. Lack of presence of all key aspects of a question is solved by Boolean filtering of result sentences. The score variations of the annotator generated fields with all the different lengths are accounted for by using field specific smoothing. Experiments show that each solution incrementally improves structured retrieval, and a combination of Boolean filtering, structural expansion, and keyword queries outperforms keyword and simple structured retrieval baselines.