%0 Journal Article %1 claypool00 %A Claypool, Mark %A Claypool, Mark %A Le, Phong %A Le, Phong %A Waseda, Makoto %A Waseda, Makoto %A Brown, David %A Brown, David %B In Intelligent User Interfaces %D 2000 %I ACM Press %K implicit recommender_systems %P 33--40 %T Implicit Interest Indicators %X Recommender systems provide personalized suggestions about items that users will find interesting. Typically, recommender systems require a user interface that can "intelligently " determine the interest of a user and use this information to make suggestions. The common solution, "explicit ratings", where users tell the system what they think about a piece of information, is well-understood and fairly precise. However, having to stop to enter explicit ratings can alter normal patterns of browsing and reading. A more "intelligent" method is to use implicit ratings, where a rating is obtained by a method other than obtaining it directly from the user. These implicit interest indicators have obvious advantages, including removing the cost of the user rating, and that every user interaction with the system can contribute to an implicit rating. Current recommender systems mostly do not use implicit ratings, nor is the ability of implicit ratings to predict actual user interest well-unders...

@article{claypool00, abstract = {Recommender systems provide personalized suggestions about items that users will find interesting. Typically, recommender systems require a user interface that can "intelligently " determine the interest of a user and use this information to make suggestions. The common solution, "explicit ratings", where users tell the system what they think about a piece of information, is well-understood and fairly precise. However, having to stop to enter explicit ratings can alter normal patterns of browsing and reading. A more "intelligent" method is to use implicit ratings, where a rating is obtained by a method other than obtaining it directly from the user. These implicit interest indicators have obvious advantages, including removing the cost of the user rating, and that every user interaction with the system can contribute to an implicit rating. Current recommender systems mostly do not use implicit ratings, nor is the ability of implicit ratings to predict actual user interest well-unders...}, added-at = {2009-06-22T17:28:38.000+0200}, author = {Claypool, Mark and Claypool, Mark and Le, Phong and Le, Phong and Waseda, Makoto and Waseda, Makoto and Brown, David and Brown, David}, biburl = {https://www.bibsonomy.org/bibtex/29bba49c50726bb7705cc2a4bcbe68548/lefteris8}, booktitle = {In Intelligent User Interfaces}, interhash = {511f83f6ec87a6f3148646c0789014b1}, intrahash = {9bba49c50726bb7705cc2a4bcbe68548}, keywords = {implicit recommender_systems}, pages = {33--40}, publisher = {ACM Press}, timestamp = {2009-06-22T17:28:39.000+0200}, title = {Implicit Interest Indicators}, year = 2000 }