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AMKM
2003
Springer
14 years 18 days ago
Agentized, Contextualized Filters for Information Management
Every time a user engaged in work reads or writes, the user spontaneously generates new information needs: to understand the text he or she is reading or to supply more substance ...
David A. Evans, Gregory Grefenstette, Yan Qu, Jame...
SIGIR
2009
ACM
14 years 1 months ago
Combining audio content and social context for semantic music discovery
When attempting to annotate music, it is important to consider both acoustic content and social context. This paper explores techniques for collecting and combining multiple sourc...
Douglas Turnbull, Luke Barrington, Gert R. G. Lanc...
ICUIMC
2009
ACM
14 years 1 months ago
PicAChoo: a tool for customizable feature extraction utilizing characteristics of textual data
Although documents have hundreds of thousands of unique words, only a small number of words are significantly useful for intelligent services. For this reason, feature extraction ...
Jaeseok Myung, Jung-Yeon Yang, Sang-goo Lee
SIGIR
2004
ACM
14 years 23 days ago
Focused named entity recognition using machine learning
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
Li Zhang, Yue Pan, Tong Zhang
IUI
2000
ACM
13 years 11 months ago
User interactions with everyday applications as context for just-in-time information access
Our central claim is that user interactions with everyday productivity applications (e.g., word processors, Web browsers, etc.) provide rich contextual information that can be lev...
Jay Budzik, Kristian J. Hammond