Discovering user behavior patterns in personalized interface agents

Jiming LIU, Kelvin C K WONG, Ka Keung Hui

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

3 Citations (Scopus)

Abstract

In human-computer interaction, user interface events can be recorded and organized into sequences of episodes. By computing their implication networks, episode frequencies, and some heuristic measures of interestingness, we can readily derive some application-specific episode association rules. In order to demonstrate the proposal method, we have developed a personalized interface agent that can take into consideration interface events in analyzing user goals. It can then delegate on behalf of the user to interact with the software based on the recognized plans. In order to adapt to different users’ needs, the agent can personalize its assistance by learning user profiles. Currently, we have used the Microsoft Word as a test case. By detecting and analyzing the patterns of user behavior in using Word, the agent can automatically assist the users in certain Word tasks. The pattern association can be achieved at several levels, i.e., text-level (phrase association), paragraphlevel (formatting association), and document-level (style and source association).

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning - IDEAL 2000
Subtitle of host publicationData Mining, Financial Engineering, and Intelligent Agents - 2nd International Conference, Proceedings
EditorsKwong Sak Leung, Lai-Wan Chan, Helen Meng
PublisherSpringer Verlag
Pages398-403
Number of pages6
ISBN (Print)3540414509, 9783540414506
DOIs
Publication statusPublished - 2000
Event2nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2000 - Shatin, N.T., Hong Kong
Duration: 13 Dec 200015 Dec 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1983
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2000
Country/TerritoryHong Kong
CityShatin, N.T.
Period13/12/0015/12/00

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

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