Personalized Web Page Recommendation Based on Preference Footprint to Browsed Pages

Abstract

SUMMARYIn this paper, a new scheme for personalized web page recommendation using multi-user search engine query information is proposed. Our contribution is a scheme that improves the accuracy of personalization for various types of contents (e.g., documents, images and music) without increasing user burden. The proposed scheme combines "preference footprints" for browsed pages with collaborative filtering. We acquire user interest using words that are relevant to queries submitted by users, attach all user interests to a page as a footprint when it is browsed, and evaluate the relevance of web pages in relation to words in footprints. The performance of the scheme is evaluated experimentally. The results indicate that the proposed scheme improves the precision and recall of previous schemes by 1%-24% and 80%-107%, respectively.

An intelligent inventive system for personalised webpage recommendation based on ontology semantics

“…Agents are used to transform a query into much more meaningful query to achieve results with maximum search efficiency. Serizawa et al (2016) have proposed a new strategy for webpage recommendation using a multi-user query. The strategy exhibits personalisation whose accuracy is increased by using a preference footprints strategy imbibing collaborative filtering.…”