J. Srivastava

Publications
Influence

Web usage mining: discovery and applications of usage patterns from Web data

J. Srivastava, R. Cooley, M. Deshpande, P. Tan
Computer Science
SKDD
2000

Web usage mining is the application of data mining techniques to discover usage patterns from Web data, in order to understand and better serve the needs of Web-based applications. Expand

2,541
138
PDF

Data Preparation for Mining World Wide Web Browsing Patterns

R. Cooley, B. Mobasher, J. Srivastava
Computer Science
Knowledge and Information Systems
1 February 1999

The World Wide Web (WWW) continues to grow at an astounding rate in both the sheer volume of traffic and the size and complexity of Web sites. Expand

1,526
97
PDF

Selecting the right interestingness measure for association patterns

P. Tan, V. Kumar, J. Srivastava
Computer Science, Mathematics
KDD
23 July 2002

We show that each measure has different properties which make them useful for some application domains, but not for others. Expand

Automatic personalization based on Web usage mining

B. Mobasher, R. Cooley, J. Srivastava
Computer Science
CACM
1 August 2000

The ease and speed with which business transactions can be carried out over the Web have been a key driving force in the rapid growth of electronic commerce. Expand

1,450
58
PDF

Web mining: information and pattern discovery on the World Wide Web

R. Cooley, B. Mobasher, J. Srivastava
Computer Science
Proceedings Ninth IEEE International Conference…
3 November 1997

We define Web mining and present an overview of the various research issues, techniques, and development efforts related to it. Expand

1,461
56
PDF

Selecting the right objective measure for association analysis

P. Tan, V. Kumar, J. Srivastava
Computer Science
Inf. Syst.
1 June 2004

A comparative study of these properties is made using twenty-one measures that were originally developed in diverse fields such as statistics, social science, machine learning, and data mining. Expand

A Comparative Study of Anomaly Detection Schemes in Network Intrusion Detection

A. Lazarevic, Levent Ertöz, V. Kumar, Aysel Ozgur, J. Srivastava
Computer Science
SDM
2003

A comparative study of several anomaly detection schemes for detecting network intrusions in both DARPA’98 and real network data. Expand

Event detection from time series data

Valery Guralnik, J. Srivastava
Computer Science
KDD '99
1 August 1999

In the past few years there has been increased interest in using data-mining techniques to extract interesting patterns from time series data generated by sensors monitoring temporally varying phenomenon. Expand

Adaptive binary splitting for efficient RFID tag anti-collision

Jihoon Myung, W. Lee, J. Srivastava
Computer Science
IEEE Communications Letters
19 June 2006

We develop a novel tag anti-collision scheme called adaptive binary splitting (ABS). Expand

Impact of social influence in e-commerce decision making

Y. Kim, J. Srivastava
Business, Computer Science
ICEC
19 August 2007

We present an overview of the impact of social influence in E-commerce decision making to provide guidance to researchers and companies who have an interest in related issues. Expand

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