Applying web usage mining for adaptive intranet navigation

• Authors: Sharhida Zawani Saad;Udo Kruschwitz
• Venue: IRFC'11 Proceedings of the Second international conference on Multidisciplinary information retrieval facility
• Year: 2011

Much progress has recently been made in assisting a user in the search process, be it Web search where the big search engines have now all incorporated more interactive features or be it online shopping where customers are commonly recommended items that appear to match the customer's interest. While assisted Web search relies very much on implicit information such as the users' search behaviour, recommender systems typically rely on explicit information, expressed for example by a customer purchasing an item. Surprisingly little progress has however been made in making navigation of a Web site more adaptive. Web sites can be difficult to navigate as they tend to be rather static and a new user has no idea what documents are most relevant to his or her need. We try to assist a new user by exploiting the navigation behaviour of previous users. On a university Web site for example, the target users change constantly. In a company the change might not be that dramatic, nevertheless new employees join the company and others retire. What we propose is to make the Web site more adaptive by introducing links and suggestions to commonly visited pages without changing the actual Web site. We simply add a layer on top of the existing site that makes recommendations regarding links found on the page or pages that are further away but have been typical landing pages whenever a user visited the current Web page. This paper reports on a task-based evaluation that demonstrates that the idea is very effective. Introducing suggestions as outlined above was found to be not just preferred by the users of our study but allowed them also to get to the results more quickly.