Sat, 26 Jul 2008 00:32:35 BST CiteULike: brusilovskys Liu http://www.citeulike.org/user/brusilovsky/author/Liu CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/brusilovsky/article/1853879 <i>(2007), pp. 300-309.</i> Time-dependent event hierarchy construction Gabriel Jeffrey Yu Huan Liu Philip Yu doi:10.1145/1281192.1281227 (2007), pp. 300-309. 2007-11-02T01:59:42-00:00 2007 300 309 ACM datamining news http://www.citeulike.org/user/brusilovsky/article/1988966 <i>IEEE Intelligent Systems, Vol. 18, No. 2. (March 2003), pp. 52-57.</i><br /><br />In human-computer interaction, user interface events and frequencies can be recorded and organized into episodes. By computing episode frequencies and implication relations, we can automatically derive application-specific episode associations and therefore enable an application interface to adaptively provide just-in-time assistance to a user. The authors identify five issues related to designing an adaptive user interface: interaction tracking, episodes identification, user pattern recognition, user intention prediction, and user profile update. In particular, they demonstrate how to identify episodes and associate them with an interface that can act on a user's behalf to interact with an application based on certain recognized plans. To adapt to different users' needs, the interface can personalize its assistance by learning user profiles. For example, by detecting and analyzing users' behavior patterns in using Microsoft Word, the interface can automatically assist users in several Word tasks. The authors' Word interface provides episode associations at two levels: text-level (phrase association) and paragraph-level (formatting automation). They conducted two pilot experiments to evaluate the interface's performance. The suggestions it provided and its ease of use were well received by users, and the interface can to a certain extent increase the productivity of type-setting. An Adaptive User Interface Based On Personalized Learning Jiming Liu Chi Wong Ka Hui doi:10.1109/MIS.2003.1193657 IEEE Intelligent Systems, Vol. 18, No. 2. (March 2003), pp. 52-57. 2007-11-26T22:39:59-00:00 2003 IEEE Intelligent Systems 1541-1672 18 2 52 57 IEEE Educational Activities Department adaptive-interface http://www.citeulike.org/user/brusilovsky/article/1291662 <i>(2007), pp. 541-550.</i> Compare&contrast: using the web to discover comparable cases for news stories Jiahui Liu Earl Wagner Larry Birnbaum doi:10.1145/1242572.1242646 (2007), pp. 541-550. 2007-05-12T20:50:15-00:00 2007 541 550 ACM Press named-entity news http://www.citeulike.org/user/brusilovsky/article/1217951 <i>IEEE Transactions on Knowledge and Data Engineering, Vol. 16, No. 1. (January 2004), pp. 28-40.</i><br /><br />Current Web search engines are built to serve all users, independent of the special needs of any individual user. Personalization of Web search is to carry out retrieval for each user incorporating his/her interests. We propose a novel technique to learn user profiles from users' search histories. The user profiles are then used to improve retrieval effectiveness in Web search. A user profile and a general profile are learned from the user's search history and a category hierarchy, respectively. These two profiles are combined to map a user query into a set of categories which represent the user's search intention and serve as a context to disambiguate the words in the user's query. Web search is conducted based on both the user query and the set of categories. Several profile learning and category mapping algorithms and a fusion algorithm are provided and evaluated. Experimental results indicate that our technique to personalize Web search is both effective and efficient. Personalized Web Search For Improving Retrieval Effectiveness Fang Liu Clement Yu Weiyi Meng doi:10.1109/TKDE.2004.1264820 IEEE Transactions on Knowledge and Data Engineering, Vol. 16, No. 1. (January 2004), pp. 28-40. 2007-04-09T14:33:44-00:00 2004 IEEE Transactions on Knowledge and Data Engineering 1041-4347 16 1 28 40 IEEE Educational Activities Department adaptive-search en user-profile http://www.citeulike.org/user/brusilovsky/article/380030 <i>(2002), pp. 558-565.</i> Personalized web search by mapping user queries to categories Fang Liu Clement Yu Weiyi Meng doi:10.1145/584792.584884 (2002), pp. 558-565. 2005-11-04T05:31:43-00:00 2002 558 565 ACM Press adaptive-search adaptive-web user-profile http://www.citeulike.org/user/brusilovsky/article/674974 <i>(2005)</i><br /><br />As the competition of Web search market increases, there is a high demand for personalized Web search to conduct retrieval incorporating Web users' information needs. This paper focuses on utilizing clickthrough data to improve Web search. Since millions of searches are conducted everyday, a search engine accumulates a large volume of clickthrough data, which records who submits queries and which pages he/she clicks on. The clickthrough data is highly sparse and contains di#erent types of... Cubesvd: A novel approach to personalized web search J Sun H Zeng H Liu Y Lu Z Chen (2005) 2006-05-30T14:00:18-00:00 2005 adaptive-search adaptive-web user-profile