Machine learning an artificial intelligence approach volume II
Machine learning an artificial intelligence approach volume II
Interfacing thought: cognitive aspects of human-computer interaction
Automatic feedback using past queries: social searching?
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
REGRET: reputation in gregarious societies
Proceedings of the fifth international conference on Autonomous agents
Proceedings of the 11th international conference on World Wide Web
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Learning from Data: Concepts, Theory, and Methods
Learning from Data: Concepts, Theory, and Methods
Communications of the ACM
A reputation-based approach for choosing reliable resources in peer-to-peer networks
Proceedings of the 9th ACM conference on Computer and communications security
A Social Mechanism of Reputation Management in Electronic Communities
CIA '00 Proceedings of the 4th International Workshop on Cooperative Information Agents IV, The Future of Information Agents in Cyberspace
Detecting deception in reputation management
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Collaborative Reputation Mechanisms in Electronic Marketplaces
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Personalized Web Search For Improving Retrieval Effectiveness
IEEE Transactions on Knowledge and Data Engineering
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
Behavior-based web page evaluation
Proceedings of the 15th international conference on World Wide Web
Methods for comparing rankings of search engine results
Computer Networks: The International Journal of Computer and Telecommunications Networking - Web dynamics
A study of results overlap and uniqueness among major web search engines
Information Processing and Management: an International Journal
Certified reputation: how an agent can trust a stranger
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Adaptive Web Search: Evolving a Program That Finds Information
IEEE Intelligent Systems
Web searcher interaction with the Dogpile.com metasearch engine
Journal of the American Society for Information Science and Technology
SMAP '07 Proceedings of the Second International Workshop on Semantic Media Adaptation and Personalization
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Evaluating reputation in multi-agents systems
AAMAS'02 Proceedings of the 2002 international conference on Trust, reputation, and security: theories and practice
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The aim of this paper is, in accordance with efficient web search service operation objectives, to propose enhancements to the sophistication of the functionality that can be offered by search engine services. A meta-search third-party result ranking mechanism is proposed, which is capable of adapting over the continuous changes that occur on the web, providing in parallel personalized information acquisition considering the user's navigation behaviour. Transparency is achieved for both personalization and web evolution adaptation mechanisms, requiring virtually none effort from the user's part. In essence, the proposed meta search engine rates, re-organises and combines the results acquired from search services for a specific user information resource request in accordance with a weighted combination of a performance related factor (tightly related to the ranking of the web result as given by the search engine service) and a reliability related factor (corresponding to the user satisfaction stemming from the specific web result that he/she browses), while the performance of each search engine with respect to adequately adapting to the web evolution is taken into account. For the evaluation of the web results reliability, a collaborative reputation mechanism is utilized, which helps estimating their quality and predicting their future usability, taking into account their past performance in consistently satisfying user expectations. A set of results indicative of the efficiency of our proposed scheme is provided. The Internet search services used were Google, MSN and Yahoo!