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Graph Structures for Knowledge Representation and Reasoning pp 39–57Cite as

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

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Part of the book series: Lecture Notes in Computer Science ((LNAI,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.

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Author information

Authors and Affiliations

  1. eBay Inc, San Jose, CA, USA

    Boris A. Galitsky

  2. Higher School of Economics, Moscow, Russia

    Dmitry Ilvovsky, Sergei O. Kuznetsov & Fedor Strok

Authors
  1. Boris A. Galitsky
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  2. Dmitry Ilvovsky
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  3. Sergei O. Kuznetsov
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  4. Fedor Strok
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Editor information

Editors and Affiliations

  1. LIRMM, 161, rue ADA, 34392, Montpellier Cedex 5, France

    Madalina Croitoru

  2. Fakultät Informatik, Technische Universität Dresden, Nöthnitzer Str. 46, 01187, Dresden, Germany

    Sebastian Rudolph

  3. Institute of Information Systems, Vienna University of Technology, Austria

    Stefan Woltran

  4. Laboratoire d’Informatique de Paris 6 (LIP6/UPMC), Université Pierre et Marie Curie, 4, place Jussieu, 75005, Paris, France

    Christophe Gonzales

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Galitsky, B.A., Ilvovsky, D., Kuznetsov, S.O., Strok, F. (2014). Finding Maximal Common Sub-parse Thickets for Multi-sentence Search. In: Croitoru, M., Rudolph, S., Woltran, S., Gonzales, C. (eds) Graph Structures for Knowledge Representation and Reasoning. Lecture Notes in Computer Science(), vol 8323. Springer, Cham. https://doi.org/10.1007/978-3-319-04534-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-04534-4_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04533-7

  • Online ISBN: 978-3-319-04534-4

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