An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics

Amizadeh, Saeed; Wang, Shuguang; Hauskrecht, Milos

doi:10.5591/978-1-57735-516-8/IJCAI11-198

An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics

Saeed Amizadeh, Shuguang Wang, Milos Hauskrecht

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 1159-1163.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-198

Abstract

In this paper, we propose a new framework for constructing text metrics which can be used to compare and support inferences among terms and sets of terms. Our metric is derived from data-driven kernels on graphs that let us capture global relations among terms and sets of terms, regardless of their complexity and size. To compute the metric efficiently for any two subsets of terms, we develop an approximation technique that relies on the precompiled term-term similarities. To scale-up the approach to problems with huge number of terms, we develop and experiment with a solution that subsamples the term space. We demonstrate the benefits of the whole framework on two text inference tasks: prediction of terms in the article from its abstract and query expansion in information retrieval.

Saeed Amizadeh, Shuguang Wang, and Milos Hauskrecht. 2011. An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 1159–1163. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-198

@inproceedings{ijcai2011p198,
  title     = {An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics},
  author    = {Amizadeh, Saeed and Wang, Shuguang and Hauskrecht, Milos},
  booktitle = {Proceedings of the Twenty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-11}},
  publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
  editor    = {Toby Walsh},
  pages     = {1159--1163},
  year      = {2011},
  month     = {7},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-198},
  url       = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-198},
}

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TI  - An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics
AU  - Amizadeh, Saeed
AU  - Wang, Shuguang
AU  - Hauskrecht, Milos
T2  - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11
PB  - AAAI Press/International Joint Conferences on Artificial Intelligence
PY  - 2011
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EP  - 1163
DO  - 10.5591/978-1-57735-516-8/IJCAI11-198
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