Recommender system Recommender systems or recommendation systems (sometimes replacing "system" with a synonym such as platform or engine) are a subclass of information filtering system that seek to predict the 'rating' or 'preference' that user would give to an item.[1][2] Recommender systems have become extremely common in recent years, and are applied in a variety of applications. The most popular ones are probably movies, music, news, books, research articles, search queries, social tags, and products in general. However, there are also recommender systems for experts, jokes, restaurants, financial services, life insurance, persons (online dating), and twitter followers .[3] Overview[edit] The differences between collaborative and content-based filtering can be demonstrated by comparing two popular music recommender systems - Last.fm and Pandora Radio. Each type of system has its own strengths and weaknesses. Recommender system is an active research area in the data mining and machine learning areas.
Adaptive Semantics Inc. New York Times - Linked Open Data ContextIn - Semantic Advertising Recommendation’s Engine based on Spread Activation algorithm « Álvaro Brange’s Blog. September 7, 2010 Suggestion graph made with test application Hi, Since last year that I haven’t added any post on my blog, but I would like add new posts. Here is the abstract: Nowadays people are reproducing the social network from your real life into a virtual space in which are represented the same social structures and relations of friendship, work, academic partners, and “love- relationships”. Read full document Regards, Álvaro Like this: Like Loading... IBM Sentiment Analysis A technique to detect favorable and unfavorable opinions toward specific subjects (such as organizations and their products) within large numbers of documents offers enormous opportunities for various applications. It would provide powerful functionality for competitive analysis, marketing analysis, and detection of unfavorable rumors for risk management. Our sentiment analysis approach is to extract sentiments associated with polarities of positive or negative for specific subjects from a document, instead of classifying the whole document into positive or negative. The essential issues in sentiment analysis are to identify how sentiments are expressed in texts and whether the expressions indicate positive (favorable) or negative (unfavorable) opinions toward the subject. In order to improve the accuracy of the sentiment analysis, it is important to properly identify the semantic relationships between the sentiment expressions and the subject.
Elsevier Sponsors 2010 Semantic Web Challenge NEW YORK, November 16, 2010 /PRNewswire-FirstCall/ -- - Winners Announced at International Semantic Web Conference Elsevier announced the winners of the 2010 Semantic Web Challenge. The semantic web is an exciting new direction in Artificial Intelligence, aiming to add meaning to information on a web-size scale. Over the last eight years, the Challenge has attracted more than 140 entries. Organized this year by Christian Bizer from the Freie Universitat Berlin, Germany, and Diana Maynard from the University of Sheffield, UK, the Semantic Web Challenge consists of two categories: "Open Track" and "Billion Triples Track." The winners of the 2010 Open Track challenge were the team from Stanford University comprising of Clement Jonquet, Paea LePendu, Sean M. The second prize in the open track was awarded to the team from Rensselaer Polytechnic Institute comprising of Dominic DiFranzo, Li Ding, John S. NCBO Resource Index: Ontology - Based Search and Mining of Biomedical Resources Paper:
Twine - Organize, Share, Discover Information Around Your Intere BOOKS TOOLBOX: 50+ Sites for Book Lovers Lulu, a book publishing site, is in the news this week. But there are many more sites for book reviews, self-publishing and exchange. Here are more than 50 of our favorites. Disclosure: Lulu currently has an ad campaign running on Mashable. Book Reviews Amazon.com - Search from thousands of books, buy them online and read excellent reviews. Booksprice.com - Users can search and compare prices of new and old books from all major stores. Bookswellread.com - Users can share reviews of some of their favorite books with others. Titlez - Users can perform a comparative analysis of a book or group of books with other books in the market. Whatshouldireadnext.com - Users enter their favorite book and they are a recommended a new book based on analysis of the reading preferences of other registered users. Book Communities aNobii - A great way to create book listings, interact with people and express thoughts. Booksconnect.com - A site which connects book lovers, writers and resellers. Publishing Others
LarKC: the Large Knowledge Collider