METHODS AND SYSTEMS FOR MINING WEBSITES
First Claim
Patent Images
1. A method for mining websites, comprising:
- obtaining web usage data of user sessions of a website, wherein said website has a hierarchical structure with granular levels and has mapping from each webpage of the website to the hierarchical structure;
mapping the user sessions to the hierarchical structure of the website resulting in hierarchical user sessions;
initiating metrics to determine similarity in the hierarchical user sessions; and
clustering similar hierarchical user sessions into groups.
3 Assignments
0 Petitions
Accused Products
Abstract
Mining of websites that in one embodiment includes obtaining web usage data of user sessions of a website, wherein the website has a hierarchical structure with granular levels and has mapping from each webpage of the website into the hierarchical structure, mapping the user sessions to the hierarchical structure of the website resulting in hierarchical user sessions, initiating an edit distance metrics to determine similarity in the hierarchical user sessions, and clustering similar hierarchical user sessions into groups.
-
Citations
24 Claims
-
1. A method for mining websites, comprising:
-
obtaining web usage data of user sessions of a website, wherein said website has a hierarchical structure with granular levels and has mapping from each webpage of the website to the hierarchical structure; mapping the user sessions to the hierarchical structure of the website resulting in hierarchical user sessions; initiating metrics to determine similarity in the hierarchical user sessions; and clustering similar hierarchical user sessions into groups. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
-
-
13. A method for segmenting website users, comprising:
-
obtaining web usage data of said users of a website, wherein said website has a hierarchical structure with granular levels and has mapping from each webpage of the website to the hierarchical structure; characterizing said users to determine user vectors of the users; clustering said users into groups based upon similarity in user interest; determining centroids of the groups using the user vectors of each of the groups wherein the centroid represents interest vectors of the groups; and determining closeness between the groups or atleast one user and atleast one group. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
-
Specification