Fuzzy category and fuzzy interest for web user understanding

Si Hun Lee; Jee Hyong Lee; Keon Myung Lee; Hee Yong Youn

doi:10.1007/11424925_120

Fuzzy category and fuzzy interest for web user understanding

Si Hun Lee
, Jee Hyong Lee
, Keon Myung Lee
, Hee Yong Youn

Department of Computer Science and Engineering

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

Web usage mining is a research field for searching potentially useful and valuable information from web log file. Web log file is a simple list of pages that users refer. Therefore, it is not easy to analyze user's current interest field from web log file. This paper presents web usage mining method for finding users' current interest based on Fuzzy category. We consider not only how many times a user visits pages but also when he visits. We describe a user's current interest with a fuzzy interest degree to categories. Based on fuzzy categories and fuzzy interest degrees, we also propose a method for understanding web users. For this, we define the category vector space. We also present experiment results which shows how our method helps to understand web users.

Original language	English
Pages (from-to)	1149-1158
Number of pages	10
Journal	Lecture Notes in Computer Science
Volume	3483
Issue number	IV
DOIs	https://doi.org/10.1007/11424925_120
State	Published - 2005
Event	International Conference on Computational Science and Its Applications - ICCSA 2005 - , Singapore Duration: 9 May 2005 → 12 May 2005

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10.1007/11424925_120

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@article{10d3e34e86ef4c15ac38c0f69de4d164,

title = "Fuzzy category and fuzzy interest for web user understanding",

abstract = "Web usage mining is a research field for searching potentially useful and valuable information from web log file. Web log file is a simple list of pages that users refer. Therefore, it is not easy to analyze user's current interest field from web log file. This paper presents web usage mining method for finding users' current interest based on Fuzzy category. We consider not only how many times a user visits pages but also when he visits. We describe a user's current interest with a fuzzy interest degree to categories. Based on fuzzy categories and fuzzy interest degrees, we also propose a method for understanding web users. For this, we define the category vector space. We also present experiment results which shows how our method helps to understand web users.",

author = "Lee, \{Si Hun\} and Lee, \{Jee Hyong\} and Lee, \{Keon Myung\} and Youn, \{Hee Yong\}",

year = "2005",

doi = "10.1007/11424925\_120",

language = "English",

volume = "3483",

pages = "1149--1158",

journal = "Lecture Notes in Computer Science",

issn = "0302-9743",

publisher = "Springer Science and Business Media Deutschland GmbH",

number = "IV",

note = "International Conference on Computational Science and Its Applications - ICCSA 2005 ; Conference date: 09-05-2005 Through 12-05-2005",

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TY - JOUR

T1 - Fuzzy category and fuzzy interest for web user understanding

AU - Lee, Si Hun

AU - Lee, Jee Hyong

AU - Lee, Keon Myung

AU - Youn, Hee Yong

PY - 2005

Y1 - 2005

N2 - Web usage mining is a research field for searching potentially useful and valuable information from web log file. Web log file is a simple list of pages that users refer. Therefore, it is not easy to analyze user's current interest field from web log file. This paper presents web usage mining method for finding users' current interest based on Fuzzy category. We consider not only how many times a user visits pages but also when he visits. We describe a user's current interest with a fuzzy interest degree to categories. Based on fuzzy categories and fuzzy interest degrees, we also propose a method for understanding web users. For this, we define the category vector space. We also present experiment results which shows how our method helps to understand web users.

AB - Web usage mining is a research field for searching potentially useful and valuable information from web log file. Web log file is a simple list of pages that users refer. Therefore, it is not easy to analyze user's current interest field from web log file. This paper presents web usage mining method for finding users' current interest based on Fuzzy category. We consider not only how many times a user visits pages but also when he visits. We describe a user's current interest with a fuzzy interest degree to categories. Based on fuzzy categories and fuzzy interest degrees, we also propose a method for understanding web users. For this, we define the category vector space. We also present experiment results which shows how our method helps to understand web users.

UR - https://www.scopus.com/pages/publications/24944447966

U2 - 10.1007/11424925_120

DO - 10.1007/11424925_120

M3 - Conference article

AN - SCOPUS:24944447966

SN - 0302-9743

VL - 3483

SP - 1149

EP - 1158

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

IS - IV

T2 - International Conference on Computational Science and Its Applications - ICCSA 2005

Y2 - 9 May 2005 through 12 May 2005

ER -

Fuzzy category and fuzzy interest for web user understanding

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