Applying web usage mining techniques to discover potential browsing problems of users

I-Hsien Ting; Chris Kimble; Daniel Kudenko

Applying web usage mining techniques to discover potential browsing problems of users

I-Hsien Ting, Chris Kimble, Daniel Kudenko

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, a web usage mining based approach is proposed to discover potential browsing problems. Two web usage mining techniques in the approach are introduced, including Automatic Pattern Discovery (APD) and Co-occurrence Pattern Mining with Distance Measurement (CPMDM). A combination method is also discussed to show how potential browsing problems can be identified

Original language	English
Title of host publication	7th IEEE International Conference on Advanced Learning Technologies, Proceedings
Editors	JM Spector, DG Sampson, T Okamoto, X Kinshuk, SA Cerri, M Ueno, A Kashihara
Place of Publication	LOS ALAMITOS
Publisher	IEEE Computer Society
Pages	929-930
Number of pages	2
ISBN (Print)	978-0-7695-2916-5
Publication status	Published - 2007
Event	7th IEEE International Conference on Advanced Learning Technologies - Niigata Duration: 18 Jul 2007 → 20 Jul 2007

Conference

Conference	7th IEEE International Conference on Advanced Learning Technologies
City	Niigata
Period	18/07/07 → 20/07/07

Cite this

@inproceedings{8d3132155df545f3ae9beeeec9a47c83,

title = "Applying web usage mining techniques to discover potential browsing problems of users",

abstract = "In this paper, a web usage mining based approach is proposed to discover potential browsing problems. Two web usage mining techniques in the approach are introduced, including Automatic Pattern Discovery (APD) and Co-occurrence Pattern Mining with Distance Measurement (CPMDM). A combination method is also discussed to show how potential browsing problems can be identified",

author = "I-Hsien Ting and Chris Kimble and Daniel Kudenko",

year = "2007",

language = "English",

isbn = "978-0-7695-2916-5",

pages = "929--930",

editor = "JM Spector and DG Sampson and T Okamoto and X Kinshuk and SA Cerri and M Ueno and A Kashihara",

booktitle = "7th IEEE International Conference on Advanced Learning Technologies, Proceedings",

publisher = "IEEE Computer Society",

address = "United States",

note = "7th IEEE International Conference on Advanced Learning Technologies ; Conference date: 18-07-2007 Through 20-07-2007",

}

Ting, I-H, Kimble, C & Kudenko, D 2007, Applying web usage mining techniques to discover potential browsing problems of users. in JM Spector, DG Sampson, T Okamoto, X Kinshuk, SA Cerri, M Ueno & A Kashihara (eds), 7th IEEE International Conference on Advanced Learning Technologies, Proceedings. IEEE Computer Society, LOS ALAMITOS, pp. 929-930, 7th IEEE International Conference on Advanced Learning Technologies, Niigata, 18/07/07.

Applying web usage mining techniques to discover potential browsing problems of users. / Ting, I-Hsien; Kimble, Chris; Kudenko, Daniel.
7th IEEE International Conference on Advanced Learning Technologies, Proceedings. ed. / JM Spector; DG Sampson; T Okamoto; X Kinshuk; SA Cerri; M Ueno; A Kashihara. LOS ALAMITOS: IEEE Computer Society, 2007. p. 929-930.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Applying web usage mining techniques to discover potential browsing problems of users

AU - Ting, I-Hsien

AU - Kimble, Chris

AU - Kudenko, Daniel

PY - 2007

Y1 - 2007

N2 - In this paper, a web usage mining based approach is proposed to discover potential browsing problems. Two web usage mining techniques in the approach are introduced, including Automatic Pattern Discovery (APD) and Co-occurrence Pattern Mining with Distance Measurement (CPMDM). A combination method is also discussed to show how potential browsing problems can be identified

AB - In this paper, a web usage mining based approach is proposed to discover potential browsing problems. Two web usage mining techniques in the approach are introduced, including Automatic Pattern Discovery (APD) and Co-occurrence Pattern Mining with Distance Measurement (CPMDM). A combination method is also discussed to show how potential browsing problems can be identified

M3 - Conference contribution

SN - 978-0-7695-2916-5

SP - 929

EP - 930

BT - 7th IEEE International Conference on Advanced Learning Technologies, Proceedings

A2 - Spector, JM

A2 - Sampson, DG

A2 - Okamoto, T

A2 - Kinshuk, X

A2 - Cerri, SA

A2 - Ueno, M

A2 - Kashihara, A

PB - IEEE Computer Society

CY - LOS ALAMITOS

T2 - 7th IEEE International Conference on Advanced Learning Technologies

Y2 - 18 July 2007 through 20 July 2007

ER -