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Web News Sentence Searching Using Linguistic Graph Similarity

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Databases and Information Systems (DB&IS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 615))

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Abstract

As the amount of news publications increases each day, so does the need for effective search algorithms. Because simple word-based approaches are inherently limited, ignoring much of the information in natural language, in this paper we propose a linguistic approach called Destiny, which utilizes this information to improve search results. The major difference from approaches that represent text as a bag-of-words is that Destiny represents sentences as graphs, with words as nodes and the grammatical relations between words as edges. The proposed algorithm is evaluated using a custom corpus of user-rated sentences and compared to a TF-IDF baseline, performs significantly better in terms of Mean Average Precision, normalized Discounted Cumulative Gain, and Spearman’s Rho.

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Acknowledgment

The authors are partially supported by the Dutch national program COMMIT.

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Authors and Affiliations

  1. Erasmus University Rotterdam, PO Box 1738, 3000 DR, Rotterdam, The Netherlands

    Kim Schouten & Flavius Frasincar

Authors
  1. Kim Schouten
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  2. Flavius Frasincar
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Corresponding author

Correspondence to Flavius Frasincar .

Editor information

Editors and Affiliations

  1. University of Latvia, Riga, Latvia

    Guntis Arnicans

  2. University of Latvia, Riga, Latvia

    Vineta Arnicane

  3. University of Latvia, Riga, Latvia

    Juris Borzovs

  4. University of Latvia, Riga, Latvia

    Laila Niedrite

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© 2016 Springer International Publishing Switzerland

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Schouten, K., Frasincar, F. (2016). Web News Sentence Searching Using Linguistic Graph Similarity. In: Arnicans, G., Arnicane, V., Borzovs, J., Niedrite, L. (eds) Databases and Information Systems. DB&IS 2016. Communications in Computer and Information Science, vol 615. Springer, Cham. https://doi.org/10.1007/978-3-319-40180-5_22

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  • DOI: https://doi.org/10.1007/978-3-319-40180-5_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40179-9

  • Online ISBN: 978-3-319-40180-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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