short-paper

Handling shape variations in geographical distance rankings for local news recommendation

Authors:

Jon Espen Ingvaldsen,

Dirk AhlersAuthors Info & Claims

GIR '15: Proceedings of the 9th Workshop on Geographic Information Retrieval

Article No.: 16, Pages 1 - 2

https://doi.org/10.1145/2837689.2837702

Published: 26 November 2015 Publication History

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Abstract

Geographical proximity is an important ranking feature in many context aware recommendation systems. News recommender systems are an example of such systems where the proximity between users and the news' geographical context is a particularly important relevance factor. In this paper, we will discuss ways to improve distance ranking by taking geographical entity sizes, shapes, and footprints into account when handling news items that are ranked for specific users.

References

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M. D. Adelfio and H. Samet. Structured toponym resolution using combined hierarchical place categories. In GIR '13, 2013.

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[2]

D. Ahlers. Granularity as a Qualitative Concept for GIR. In GIR'15. ACM, 2015.

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[3]

J. E. Ingvaldsen and J. A. Gulla. Taming news streams with linked data. In RCIS 2015. IEEE, 2015.

Crossref

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[4]

B. Martins and P. Calado. Learning to Rank for Geographic Information Retrieval. In GIR '10, 2010.

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[5]

H. Samet, J. Sankaranarayanan, M. D. Lieberman, M. D. Adelfio, B. C. Fruin, J. M. Lotkowski, D. Panozzo, J. Sperling, and B. E. Teitler. Reading news with maps by exploiting spatial synonyms. Communications of the ACM, 57(10):64--77, 2014.

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Index Terms

Handling shape variations in geographical distance rankings for local news recommendation
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems
  2. Information systems applications
    1. Spatial-temporal systems

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Information & Contributors

Information

Published In

GIR '15: Proceedings of the 9th Workshop on Geographic Information Retrieval

November 2015

90 pages

ISBN:9781450339377

DOI:10.1145/2837689

Editors:
Ross S. Purves
University of Zurich
,
Christopher B. Jones
Cardiff University

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 November 2015

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Short-paper

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Norges Teknisk-Naturvitenskapelige Universitet

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GIR '15

GIR '15: 9th Workshop on Geographic Information Retrieval

November 26 - 27, 2015

Paris, France

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Overall Acceptance Rate 46 of 61 submissions, 75%

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