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A tree-structured representation for book author and its recommendation using multilayer SOM

  • Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper introduces a new framework for author recommending using Multi-Layer Self-Organizing Map (ML-SOM). Concretely, an author is modeled by a tree-structured representation, and an MLSOM-based system is used as an efficient solution to the content-based author recommending problem. The tree-structured representation formulates author features in a hierarchy of author biography, written books and book comments. To efficiently tackle the tree-structured representation, we use an MLSOM algorithm that serves as a clustering technique to handle authors. The effectiveness of our approach was examined in a large-scale dataset containing 7426 authors, 205805 books they wrote, and 3027502 comments that readers have provided. The experimental results corroborate that the proposed approach outperforms current algorithms and can provide a promising solution to author recommendation.

Original languageEnglish
Title of host publication2015 International Joint Conference on Neural Networks, IJCNN 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479919604, 9781479919604, 9781479919604, 9781479919604
DOIs
StatePublished - 28 Sep 2015
Externally publishedYes
EventInternational Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland
Duration: 12 Jul 201517 Jul 2015

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2015-September

Conference

ConferenceInternational Joint Conference on Neural Networks, IJCNN 2015
Country/TerritoryIreland
CityKillarney
Period12/07/1517/07/15

Keywords

  • author recommendation
  • content-based recommendation
  • self-organizing map
  • tree-structured representation

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