Improving Mobile Web Navigation Using N-Grams Prediction Models

被引：1

作者：

Fu, Yongjian ^{[1
,2
,3
]}

Paul, Hironmoy ^{[1
,4
]}

Shetty, Namita ^{[1
]}

机构：

[1] Cleveland State Univ, Cleveland, OH 44115 USA

[2] ACM SIGKDD, New York, NY 10121 USA

[3] SIGSOFT, New York, NY 10121 USA

[4] Zhone Technol Inc, San Jose, CA 94621 USA

来源：

INTERNATIONAL JOURNAL OF INTELLIGENT INFORMATION TECHNOLOGIES | 2007年 / 3卷 / 02期

关键词：

adaptive Web site; dynamic Web page; mobile Web navigation; N-gram; Web usage mining;

D O I：

10.4018/jiit.2007040104

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this article, we propose to use N-gram models for improving Web navigation for mobile users. N-gram models are built from Web server logs to learn navigation patterns of mobile users. They are used as prediction models in an existing algorithm which improves mobile Web navigation by recommending shortcuts. Our experiments on two real data sets show that N-gram models are as effective as other more complex models in improving mobile Web navigation.

引用

页码：51 / 64

页数：14

共 12 条

[1]

Anderson C. R., 2001, P IJCAI 01 WORKSH SE

[2]

DESHPANDE M, 2000, 00056 U MINN

[3]

Frias- Martinez E., 2002, P WORKSH WEB MIN US

[4]

Fu Y., 1999, INT WORKSH WEB US AN

[5]

KOUTRI M, 2002, P 4 INT WORKSH COMP

[6] Automatic personalization based on Web usage mining - Web usage mining can help improve the scalability, accuracy, and flexibility of recommender systems. [J].

Mobasher, B ;

Cooley, R ;

Srivastava, J .

COMMUNICATIONS OF THE ACM, 2000, 43 (08) :142-151

[7]

Mobasher B., 1999, KNOWL INF SYST, V1, P5

[8]

PERKOWITZ M, 1997, P IJCAI 97 WORKSH NA

[9] Link prediction and path analysis using Markov chains [J].

Sarukkai, RR .

COMPUTER NETWORKS, 2000, 33 (1-6) :377-386

[10]

Shahabi C., 1997, WORKSH RES ISS DAT E

← 1 2 →