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Finding Maximal Common Sub-parse Thickets for Multi-sentence Search

  • Boris A. Galitsky
  • Dmitry Ilvovsky
  • Sergei O. Kuznetsov
  • Fedor Strok
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8323)

Abstract

We develop a graph representation and learning technique for parse structures for paragraphs of text. We introduce Parse Thicket (PT) as a set of syntactic parse trees augmented by a number of arcs for inter-sentence word-word relations such as co-reference and taxonomic relations. These arcs are also derived from other sources, including Speech Act and Rhetoric Structure theories. We provide a detailed illustration of how PTs are built from parse trees and generalized as phrases by computing maximal common subgraphs. The proposed approach is subject to evaluation in the product search and recommendation domain, where search queries include multiple sentences. We draw the comparison for search relevance improvement by pair-wise sentence generalization, phrase-level generalization, and generalizations of PTs as graphs.

Keywords

Maximal Clique Parse Tree Suffix Tree Maximal Clique Problem Common Subgraph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Boris A. Galitsky
    • 1
  • Dmitry Ilvovsky
    • 2
  • Sergei O. Kuznetsov
    • 2
  • Fedor Strok
    • 2
  1. 1.eBay IncSan JoseUSA
  2. 2.Higher School of EconomicsMoscowRussia

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