ContactMap: Organizing communication in a social desktop
ACM Transactions on Computer-Human Interaction (TOCHI)
Using Egocentric Networks to Understand Communication
IEEE Internet Computing
Social matching: A framework and research agenda
ACM Transactions on Computer-Human Interaction (TOCHI)
What do people recall about their documents?: implications for desktop search tools
Proceedings of the 12th international conference on Intelligent user interfaces
SmallBlue: People Mining for Expertise Search
IEEE MultiMedia
Do you know?: recommending people to invite into your social network
Proceedings of the 14th international conference on Intelligent user interfaces
Expert recommender systems in practice: evaluating semi-automatic profile generation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Groups without tears: mining social topologies from email
Proceedings of the 16th international conference on Intelligent user interfaces
Proceedings of the 16th international conference on Intelligent user interfaces
"Ten things i want to know about you": unveiling friends' attribute relevance
Proceedings of the 30th European Conference on Cognitive Ergonomics
CatStream: categorising tweets for user profiling and stream filtering
Proceedings of the 2013 international conference on Intelligent user interfaces
Proceedings of the 24th ACM Conference on Hypertext and Social Media
SoBot: facilitating conversation using social media data and a social agent
Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computing
| Hi-index | 0.00 |
REACH is an intelligent, people-finding system that helps users to find someone in their social directory, especially those whom they do not fully remember or barely know. It analyzes a user's communication and social networking data to automatically extract all the contacts and derive multiple facets to characterize each contact in relation to the user. It then employs a personalized, faceted search to retrieve and present a ranked list of matched contacts based on their properties. A preliminary evaluation shows the effectiveness of our approach.