Optimal multi-step k-nearest neighbor search
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Evaluating Top-k Selection Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Ontology Based Personalized Search
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic ranking of database query results
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Query dependent ranking using K-nearest neighbor
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Answering approximate queries over autonomous web databases
Proceedings of the 18th international conference on World wide web
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Progressive Keyword Search in Relational Databases
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Patterns of query reformulation during Web searching
Journal of the American Society for Information Science and Technology
Effective Top-k Keyword Search in Relational Databases Considering Query Semantics
Advances in Web and Network Technologies, and Information Management
Providing Relevant Answers for Queries over E-Commerce Web Databases
AMT '09 Proceedings of the 5th International Conference on Active Media Technology
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The growing importance and need of data processing for information extraction is vital for Web databases. Due to the sheer size and volume of databases, retrieval of relevant information as needed by users has become a cumbersome process. Information seekers are faced by information overloading - too many result sets are returned for their queries. Moreover, too few or no results are returned if a specific query is asked. This paper proposes a ranking algorithm that gives higher preference to a user's current search and also utilizes profile information in order to obtain the relevant results for a user's query.