Tag and Neighbor based Recommender systems for Medical events

Karunakar Reddy Bayyapu, Peter Dolog

Research output: Contribution to journalConference article in JournalResearchpeer-review

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Abstract

This paper presents an extension of a multifactor recommendation approach based on user tagging with term neighbours. Neighbours of words in tag vectors and documents provide for hitting larger set of documents and not only those matching with direct tag vectors or content of the documents. Tag popularity, tag representativeness and tag similarity are applied similarly as in the original approach but also to neighbours. By doing so, we treat the documents which have been added to the result set by considering word neighbours in the same way as the others. This provides an advantage in the situations where the quality of tags is lower. We discuss the approach on the examples from the existing Medworm system to indicate the usefulness of the approach.
Original languageEnglish
JournalCEUR Workshop Proceedings
Pages (from-to)14-24
Number of pages10
ISSN1613-0073
Publication statusPublished - 8 Apr 2010
EventProceedings of the First International Workshop on Web Science and Information Exchange in the Medical Web, MedEx 2010. WWW2010 web conference - Raleigh, NC, United States
Duration: 26 Apr 201030 Apr 2010

Workshop

WorkshopProceedings of the First International Workshop on Web Science and Information Exchange in the Medical Web, MedEx 2010. WWW2010 web conference
CountryUnited States
CityRaleigh, NC
Period26/04/201030/04/2010

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Recommender systems

Bibliographical note

Proceedings of the First International Workshop on Web Science and Information Exchange in the Medical Web, MedEx 2010

Keywords

  • recommender systems
  • tags and neighbors
  • algorithms
  • medical events

Cite this

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title = "Tag and Neighbor based Recommender systems for Medical events",
abstract = "This paper presents an extension of a multifactor recommendation approach based on user tagging with term neighbours. Neighbours of words in tag vectors and documents provide for hitting larger set of documents and not only those matching with direct tag vectors or content of the documents. Tag popularity, tag representativeness and tag similarity are applied similarly as in the original approach but also to neighbours. By doing so, we treat the documents which have been added to the result set by considering word neighbours in the same way as the others. This provides an advantage in the situations where the quality of tags is lower. We discuss the approach on the examples from the existing Medworm system to indicate the usefulness of the approach.",
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Tag and Neighbor based Recommender systems for Medical events. / Bayyapu, Karunakar Reddy; Dolog, Peter.

In: CEUR Workshop Proceedings, 08.04.2010, p. 14-24.

Research output: Contribution to journalConference article in JournalResearchpeer-review

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T1 - Tag and Neighbor based Recommender systems for Medical events

AU - Bayyapu, Karunakar Reddy

AU - Dolog, Peter

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PY - 2010/4/8

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N2 - This paper presents an extension of a multifactor recommendation approach based on user tagging with term neighbours. Neighbours of words in tag vectors and documents provide for hitting larger set of documents and not only those matching with direct tag vectors or content of the documents. Tag popularity, tag representativeness and tag similarity are applied similarly as in the original approach but also to neighbours. By doing so, we treat the documents which have been added to the result set by considering word neighbours in the same way as the others. This provides an advantage in the situations where the quality of tags is lower. We discuss the approach on the examples from the existing Medworm system to indicate the usefulness of the approach.

AB - This paper presents an extension of a multifactor recommendation approach based on user tagging with term neighbours. Neighbours of words in tag vectors and documents provide for hitting larger set of documents and not only those matching with direct tag vectors or content of the documents. Tag popularity, tag representativeness and tag similarity are applied similarly as in the original approach but also to neighbours. By doing so, we treat the documents which have been added to the result set by considering word neighbours in the same way as the others. This provides an advantage in the situations where the quality of tags is lower. We discuss the approach on the examples from the existing Medworm system to indicate the usefulness of the approach.

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KW - algorithms

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M3 - Conference article in Journal

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