X-web: A data model for managing personal contents based on user experiences

Taketoshi Ushiama, Toyohide Watanabe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose the X-Web (eXperience-Web) data model, which supports users to manage various types of personal contents in a unified manner based on their contextual information. The X-Web data model consists of three kinds of modeling units: contents, experiences, and persons, and the context of personal contents are expressed as experiences. Units are classified into containers, and a ranking function is defined between two containers. Combinations of ranking functions can represent various requirements for searching and recommending personal contents.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings
Pages798-805
Number of pages8
Volume5178 LNAI
EditionPART 2
DOIs
Publication statusPublished - 2008
Event12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008 - Zagreb, Croatia
Duration: Sep 3 2008Sep 5 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5178 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
CountryCroatia
CityZagreb
Period9/3/089/5/08

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Ushiama, T., & Watanabe, T. (2008). X-web: A data model for managing personal contents based on user experiences. In Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings (PART 2 ed., Vol. 5178 LNAI, pp. 798-805). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5178 LNAI, No. PART 2). https://doi.org/10.1007/978-3-540-85565-1-99