Name
Abstract | ||
|---|---|---|
Personal information needs depend on long-term interests and on current and future situations (contexts): people are mainly interested in weather forecasts for future destinations, and in toy advertisements when a child's birthday approaches. As computer capabilities for being aware of users' contexts grow, the users' willingness to set manually rules for context-based information retrieval will decrease. Thus computers must learn to associate user contexts with information needs in order to collect and present information proactively. This work presents experiments with training a SVM (Support Vector Machines) classifier to learn user information needs from calendar information. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11735106_64 | ECIR |
Keywords | Field | DocType |
present information proactively,support vector machines,user information need,personal information need,information need,associate user context,calendar information,future destination,future situation,context-based information retrieval,information retrieval,weather forecasting,support vector machine | Mobile computing,Information system,World Wide Web,Information needs,Information retrieval,Computer science,Expert system,Group information management,User information,Personally identifiable information,Artificial intelligence,Knowledge base | Conference |
Volume | ISSN | ISBN |
3936 | 0302-9743 | 3-540-33347-9 |
Citations | PageRank | References |
1 | 0.35 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Elena Vildjiounaite | 1 | 347 | 32.45 |
| Vesa Kyllönen | 2 | 118 | 17.94 |