@inproceedings{057d226392a141e79db5c308f16c8335,
title = "Incorporating usage information into average-clicks algorithm",
abstract = "A number of methods exists that measure the distance between two web pages. Average-Clicks is a new measure of distance between web pages which fits user's intuition of distance better than the traditional measure of clicks between two pages. Average-Clicks however assumes that the probability of the user following any link on a web page is the same and gives equal weights to each of the out-going links. In our method {"}Usage Aware Average-Clicks{"} we have taken the user's browsing behavior into account and assigned different weights to different links on a particular page based on how frequently users follow a particular link. Thus, Usage Aware Average-Clicks is an extension to the Average-Clicks Algorithm where the static web link structure graph is combined with the dynamic Usage Graph (built using the information available from the web logs) to assign different weights to links on a web page and hence capture the user's intuition of distance more accurately. A new distance metric has been designed using this methodology and used to improve the efficiency of a web recommendation engine.",
keywords = "Link analysis, Recommendation engines, Web mining, Web usage analysis",
author = "Kalyan Beemanapalli and Ramya Rangarajan and Jaideep Srivastava",
year = "2007",
doi = "10.1007/978-3-540-77485-3\_2",
language = "English (US)",
isbn = "354077484X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "21--35",
booktitle = "Advances in Web Mining and Web Usage Analysis - 8th International Workshop on Knowledge Discovery on the Web, WebKDD 2006, Revised Papers",
note = "8th International Workshop on Knowledge Discovery on the Web, WebKDD 2006 ; Conference date: 20-08-2006 Through 20-08-2006",
}