Abstract :
With the advent of the World Wide Web, it has captured and accumulated ´Word-of-Mouth (WoM)´ such as reviews, comments, user ratings, and etc., about cultural contents including movies. We paid attention to WoMpsilas role as cultural metadata. ´Recommendation systems´ are services which recommend users new items such as news articles, books, music, and movies they would like. We developed a simple and low-cost movie recommendation system harnessing vast cultural metadata, about movies, existing on the Web. Then we evaluated the system, and analyzed its strength. As a result, we could be aware of the potential of cultural metadata.
Keywords :
Internet; cinematography; humanities; information filtering; information filters; Word-of-Mouth; World Wide Web; cultural metadata; movie recommendation system; Artificial intelligence; Blogs; Books; Collaboration; Cultural differences; Filtering; Motion pictures; Web and internet services; Web sites; World Wide Web; cultural metadata; movie recommendation;
