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 Web Mining - Link Analysis - Web Usage Analysis - Recommendation Engines