Personalized recommendati on Personalization is defined as " the ability to provide content and services tailored to individuals based on knowledge about their preferences and behavior"or the use of technology and customer information to tailor electronic commerce interactions between a business and each individual customer Internet recommendation systems(Internet recommender systems)in electronic commerce is to reduce irrelevant content and provide users with more pertinent information or product A recommendation system is a computer-based system that uses profiles built from past usage behavior to provide relevant recommendations
Personalized recommendation ◼ Personalization is defined as “the ability to provide content and services tailored to individuals based on knowledge about their preferences and behavior” or “the use of technology and customer information to tailor electronic commerce interactions between a business and each individual customer” ◼ Internet recommendation systems (Internet recommender systems) in electronic commerce is to reduce irrelevant content and provide users with more pertinent information or product. ◼ A recommendation system is a computer-based system that uses profiles built from past usage behavior to provide relevant recommendations
Information filtering and recommendation rule-based filtering content-based filtering and collaborative filtering Rule-based filtering uses pre-specified if-then rules to select relevant inf formation for recommendation Content-based filtering uses keywords or other product related attributes to make recommendations Collaborative fil tering uses preferences of similar users in the same reference group as a basis for recommendation
Information filtering and recommendation ◼ rule-based filtering, content-based filtering, and collaborative filtering. ◼ Rule-based filtering uses pre-specified if-then rules to select relevant information for recommendation. ◼ Content-based filtering uses keywords or other productrelated attributes to make recommendations. ◼ Collaborative filtering uses preferences of similar users in the same reference group as a basis for recommendation
Typical personalization process understanding customers through profile building delivering personalized offering based on the knowledge about the product and the customer measuring personalization impact
Typical personalization process ◼ understanding customers through profile building ◼ delivering personalized offering based on the knowledge about the product and the customer ◼ measuring personalization impact
Inadequate information in IR One possible solution for overcoming the problem is to expand the query by adding more semantic information to better describe the concepts. relevance feedbacks and knowledge structure are used to add appropriate terms to expand the queries Relevance feedbacks are information on the items selected by the user from the output of previous queries
Inadequate information in IR ◼ One possible solution for overcoming the problem is to expand the query by adding more semantic information to better describe the concepts. Relevance feedbacks and knowledge structure are used to add appropriate terms to expand the queries. ◼ Relevance feedbacks are information on the items selected by the user from the output of previous queries
Spreading Activation Model In the Spreading Activation(SA) Model, concepts are expanded based on the semantics in the process of identifying customer profile and matching items and the model has been applied to expand queries
Spreading Activation Model ◼ In the Spreading Activation (SA) Model, concepts are expanded based on the semantics in the process of identifying customer profile and matching items and the model has been applied to expand queries