A method for collaborative recommendation in document retrieval systems

Abstract

The most common problem in the context of recommendation systems is "cold start" problem which occurs when new product is recommended or a new user becomes to the system. A great part of systems do not personalize a user until they gather sufficient information. In this paper a novel method for recommending a profile for a new user based only on knowledge about a few demographic data is proposed. The method merges a content-based approach with collaborative recommendation. The main objective was to show that based on knowledge about other similar users, the system can classify a new user based on subset of demographic data and recommend him a non-empty profile. Using the proposed profile, the user will obtain personalized documents. A methodology of experimental evaluation was presented and simulations were performed. The preliminary experiments have shown that the most important demographic attributes are gender, age, favorite browser and level of education. © 2013 Springer-Verlag.