Applying Web Usage and Structural Mining for Web-Page Recommendations: A Survey
Anura Khede, Jagdish Raikwal · 2015
Web-Page recommendation is of outstanding significance in today's dynamic world of internet. Intelligent web systems discover useful data using web mining techniques so as to do effective web- page recommendation. The proposed model is based on domain knowledge and integrates web usage and structure mining for enriched connectivity-based recommendations. It is basically a semantic enhanced web page recommendation which is based on semantic network (Knowledge map) creation of a website. This network represents domain terms, Web-pages and the relations between them. Each web page has associated PageID which helps to calculate PageHits and the analysis of links between the pages helps to calculate PageRank. The hybridization of two algorithms leads to efficient results. The entire topology of the website can be restructured after analysing user's behaviour(hit counts) through web logs which provides fast response to user, saves memory dimensions of servers and hence reduces HTTP requests and provides optimum utilization of bandwidth.