DISCOVERY OF ACCESS PATTERNS TO WEBSITE AND TRACING THE USERS' PATH BY DATA MINING ALGORITHMS (ASSOCIATION RULES): CASE STUDY OF UTS SEARCH ENGINE

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

HAYATI Z.; SADEGHI MOJARRAD M.; JAFARI N.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: LIBRARY AND INFORMATION SCIENCE Year:2010 | Volume:13 | Issue:1 (49) Page(s): 251-283

Download Full-Text

Persian Verion

View:

1,061

Download:

Cites:

Information Journal Paper

Title

DISCOVERY OF ACCESS PATTERNS TO WEBSITE AND TRACING THE USERS' PATH BY DATA MINING ALGORITHMS (ASSOCIATION RULES): CASE STUDY OF UTS SEARCH ENGINE

Author(s)

HAYATI Z. | SADEGHI MOJARRAD M. | JAFARI N. | Issue Writer Certificate

Keywords

DATA MININGQ2

ASSOCIATION RULESQ3

E-COMMERCEQ2

ACCESS PATTERNSQ3

WEBSITESQ3

Abstract

The survey employs deep log analysis techniques, a more sophisticated form of transaction log analysis, and DATA MINING algorithms (Association Rules) to demonstrate what usage data can unfold about information seeking behavior of Information center of UTS University in Australia. To meet this goal, we work with the raw server log data which had been gathered on the server. The information seeking behavior of nearly several millions of users is analyzed in respect to the extent to which they penetrate the site, the number of visits made, as well as the type of items and content they viewed or downloaded and when they connected to the web site. The users are broken down by their field of study, geographical location, type of databases they used, the number of items viewed in a session and type of products downloaded. This Article will offer a good knowledge about how IT managers can make their decision to subscribe Databases or change their policy in a better way.

Cites

No record.

References

No record.

Cite

APA: Copy

HAYATI, Z., SADEGHI MOJARRAD, M., & JAFARI, N.. (2010). DISCOVERY OF ACCESS PATTERNS TO WEBSITE AND TRACING THE USERS' PATH BY DATA MINING ALGORITHMS (ASSOCIATION RULES): CASE STUDY OF UTS SEARCH ENGINE. LIBRARY AND INFORMATION SCIENCE, 13(1 (49)), 251-283. SID. https://sid.ir/paper/102538/en

Vancouver: Copy

HAYATI Z., SADEGHI MOJARRAD M., JAFARI N.. DISCOVERY OF ACCESS PATTERNS TO WEBSITE AND TRACING THE USERS' PATH BY DATA MINING ALGORITHMS (ASSOCIATION RULES): CASE STUDY OF UTS SEARCH ENGINE. LIBRARY AND INFORMATION SCIENCE[Internet]. 2010;13(1 (49)):251-283. Available from: https://sid.ir/paper/102538/en

IEEE: Copy

Z. HAYATI, M. SADEGHI MOJARRAD, and N. JAFARI, “DISCOVERY OF ACCESS PATTERNS TO WEBSITE AND TRACING THE USERS' PATH BY DATA MINING ALGORITHMS (ASSOCIATION RULES): CASE STUDY OF UTS SEARCH ENGINE,” LIBRARY AND INFORMATION SCIENCE, vol. 13, no. 1 (49), pp. 251–283, 2010, [Online]. Available: https://sid.ir/paper/102538/en

Related Journal Papers