REGRET: reputation in gregarious societies
Proceedings of the fifth international conference on Autonomous agents
An outranking approach for rank aggregation in information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Opinion mining from noisy text data
Proceedings of the second workshop on Analytics for noisy unstructured text data
WaterCooler: exploring an organization through enterprise social media
Proceedings of the ACM 2009 international conference on Supporting group work
Matching reviews to objects using a language model
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
What do people ask their social networks, and why?: a survey study of status message q&a behavior
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The relationship between website quality, trust and price premiums at online auctions
Electronic Commerce Research
From federated to aggregated search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
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The term online reputation addresses trust relationships amongst agents in dynamic open systems. These can appear as ratings, recommendations, referrals and feedback. Several reputation models and rating aggregation algorithms have been proposed. However, finding a trusted entity on the web is still an issue as all reputation systems work individually. The aim of this project is to introduce a global reputation system that aggregates people's opinions from different resources (e.g. e-commerce websites, and review) with the help federated search techniques. A sentiment analysis approach is subsequently used to extract high quality opinions and inform how to increase trust in the search result.