Information filtering based on user behavior analysis and best match text retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Experiences with selecting search engines using metasearch
ACM Transactions on Information Systems (TOIS)
Inferring Web communities from link topology
Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems
Improving automatic query expansion
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
User interactions with everyday applications as context for just-in-time information access
Proceedings of the 5th international conference on Intelligent user interfaces
Generic summaries for indexing in information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Communications of the ACM
Information Retrieval
Communications of the ACM
Context and Page Analysis for Improved Web Search
IEEE Internet Computing
Long-Term Learning for Web Search Engines
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Exploiting query history for document ranking in interactive information retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
Exploiting Query Repetition and Regularity in an Adaptive Community-Based Web Search Engine
User Modeling and User-Adapted Interaction
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Personalized Search Based on User Search Histories
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Implicit user modeling for personalized search
Proceedings of the 14th ACM international conference on Information and knowledge management
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
A live-user evaluation of collaborative web search
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
An analysis of query similarity in collaborative web search
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Web search personalization with ontological user profiles
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Emergence of consensus and shared vocabularies in collaborative tagging systems
ACM Transactions on the Web (TWEB)
Towards a reputation-based model of social web search
Proceedings of the 15th international conference on Intelligent user interfaces
Mining Query Logs: Turning Search Usage Data into Knowledge
Foundations and Trends in Information Retrieval
Social summarization in collaborative web search
Information Processing and Management: an International Journal
Extraction, characterization and utility of prototypical communication groups in the blogosphere
ACM Transactions on Information Systems (TOIS)
Hi-index | 0.00 |
We describe and evaluate an approach to capturing and re-using search expertise within a community of like minded searchers, such as the employees of a company or organisation. Within knowledge based industries, search expertise - the ability to quickly and accurately locate information according to a specific information need - is an important corporate asset and in our approach we attempt to capture this knowledge by mining the title and snippet texts of results that have been selected by community members in response to their queries. Our assumption is that the snippet text of a result must play a role in helping users to judge the initial relevance of that result and that the snippet terms of selected results must contain especially informative terms about the goals and preferences of the searchers. In other words, results are selected because the user recognises certain combinations of terms in their snippets which are related to their information needs. Our approach seeks to build a community-based snippet index that reflects the evolving interests of a group of searchers. This index is then used to re-rank the results returned by some underlying search engine by boosting the ranking of key results that have been frequently selected for similar queries by community members in the past.