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Classification of user interest patterns using a virtual folksonomy

Published: 13 June 2011 Publication History

Abstract

User interest in topics and resources is known to be recurrent and to follow specific patterns, depending on the type of topic or resource. Traditional methods for predicting reoccurring patterns are based on ranking and associative models. In this paper we identify several 'canonical' patterns by clustering keywords related to visited resources, making use of a large repository of Web usage data. The keywords are derived from a 'virtual' folksonomy of tags assigned to these resources using a collaborative bookmarking system.

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  • (2015)Inferring User Interests on Social Media from Text and ImagesProceedings of the 2015 IEEE International Conference on Data Mining Workshop (ICDMW)10.1109/ICDMW.2015.208(1342-1347)Online publication date: 14-Nov-2015
  • (2014)User profiles based on revisitation timesProceedings of the 23rd International Conference on World Wide Web10.1145/2567948.2577380(359-360)Online publication date: 7-Apr-2014
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cover image ACM Conferences
JCDL '11: Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
June 2011
500 pages
ISBN:9781450307444
DOI:10.1145/1998076
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

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Publication History

Published: 13 June 2011

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Author Tags

  1. navigation support
  2. recommendation
  3. revisitation

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  • Research-article

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JCDL '11
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JCDL '11: Joint Conference on Digital Libraries
June 13 - 17, 2011
Ontario, Ottawa, Canada

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Overall Acceptance Rate 415 of 1,482 submissions, 28%

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Cited By

View all
  • (2022)Clustering Merchants and Accurate Marketing of Products Using the Segmentation Tree Vector Space ModelMathematical Problems in Engineering10.1155/2022/73531512022(1-11)Online publication date: 29-Mar-2022
  • (2015)Inferring User Interests on Social Media from Text and ImagesProceedings of the 2015 IEEE International Conference on Data Mining Workshop (ICDMW)10.1109/ICDMW.2015.208(1342-1347)Online publication date: 14-Nov-2015
  • (2014)User profiles based on revisitation timesProceedings of the 23rd International Conference on World Wide Web10.1145/2567948.2577380(359-360)Online publication date: 7-Apr-2014
  • (2014)Internets copy: Current state, problems and perspectives2014 IEEE 8th International Conference on Application of Information and Communication Technologies (AICT)10.1109/ICAICT.2014.7035938(1-7)Online publication date: Oct-2014
  • (2012)The Identification of the Target E-Space for the Company’s AdvertisingThe 7th International Scientific Conference "Business and Management 2012". Selected papers10.3846/bm.2012.114(887-894)Online publication date: 2012
  • (2012)Generation of User Interest Ontology Using ID3 Algorithm in the Social WebIT Convergence and Security 201210.1007/978-94-007-5860-5_128(1067-1074)Online publication date: 11-Dec-2012

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