81 search results - page 10 / 17 » Improving Case-Based Recommendations Using Implicit Feedback |
CHI
2011
ACM
12 years 11 months ago
2011
ACM
Understanding how people interact with search engines is important in improving search quality. Web search engines typically analyze queries and clicked results, but these actions...
AAAI
2006
13 years 9 months ago
2006
As robots become a mass consumer product, they will need to learn new skills by interacting with typical human users. Past approaches have adapted reinforcement learning (RL) to a...
EWCBR
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. We propose that traditional case-based recommender systems can be improved by informing them with context data describing the user's environment. We outline existing...
CORR
2006
Springer
13 years 7 months ago
2006
Springer
Clickthrough data is a particularly inexpensive and plentiful resource to obtain implicit relevance feedback for improving and personalizing search engines. However, it is well kn...
SIGIR
2004
ACM
14 years 27 days ago
2004
ACM
We investigate how users interact with the results page of a WWW search engine using eye-tracking. The goal is to gain into how users browse the presented abstracts and how they s...