RECOMMENDER SYSTEMS AND METHODS FOR PRICING AND EVALUATION OF FINE ART WORKS

摘要

Recommender systems and methods for the pricing and evaluation of fine art works. Fine art work market regulation using a crowd of recommender systems and methods built from relevant data and knowledge that is extracted from the Web. Advanced data mining techniques are used to construct a crowd of recommender systems for making recommendations about the pricing and evaluation of fine art works using the wisdom of selected members. The Semantic Web is a source of data and knowledge about artists and the associated fine art works. Relevant information is found and indexed using crawlers and deep Web crawlers. Advanced data mining techniques, including text mining, sentiment analysis, and guided folksonomy, are used to mine for knowledge and construct the recommender systems for the pricing of the fine art works. The wisdom of the constructed crowd is also used for identifying artists who can be recommended for promotion.