Handling User Cold-Start Problem for Group Recommender System Using Social Behaviour Wise Group Detection Method

摘要: With the accessibility to information, users often face problem of selecting one item (a product or a service) from huge search space. This is known as information overload. Therefore help them in searching items on internet we propose recommender system which recommends social networking site considering group members opinion. An important issue for RS that has greatly captured attention researchers new user cold-star problem, occurs when there been registered and no prior rating this found table. In paper, will be recommended having similar interest liking. Thus, proposed implements advanced recommendation model satisfy multiple ways. Recommendation done two ways, individual recommendation. Individual contain preference wise profile behavior So, both well there. So recommendation, automatic detection method i.e. wise. Social used avoid cold-start also reduce overhead increase accuracy. The experimental results indicate achieves better accuracy computation time than relevant methods. any case get per his likings.