“Is this document relevant?…probably”: a survey of probabilistic models in information retrieval
ACM Computing Surveys (CSUR)
Extended Boolean information retrieval
Communications of the ACM
Document Ranking and the Vector-Space Model
IEEE Software
A Rough Set-Aided System for Sorting WWW Bookmarks
WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
Automatic Topic Identification Using Ontology Hierarchy
CICLing '01 Proceedings of the Second International Conference on Computational Linguistics and Intelligent Text Processing
A Rough Set-Based Hybrid Method to Text Categorization
WISE '01 Proceedings of the Second International Conference on Web Information Systems Engineering (WISE'01) Volume 1 - Volume 1
A hybrid approach for searching in the semantic web
Proceedings of the 13th international conference on World Wide Web
A rough-fuzzy document grading system for customized text information retrieval
Information Processing and Management: an International Journal
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Proceedings of the seventeenth conference on Hypertext and hypermedia
Exploring social annotations for information retrieval
Proceedings of the 17th international conference on World Wide Web
Applying Social Annotations to Retrieve and Re-rank Web Resources
ICIME '09 Proceedings of the 2009 International Conference on Information Management and Engineering
An extended document frequency metric for feature selection in text categorization
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
An ontology-based information retrieval model
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
Rough set analysis of relational structures
Information Sciences: an International Journal
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Social networking is becoming necessity of the current generation due to its usefulness in searching the user's interest related people around the world, gathering information on different topics, and for many more purposes. In social network, there is abundant information available on different domains by means of variety of users but it is difficult to find the user preference based information.Also it is very much possible that relevant information is available in different forms at the end of other users connected in the same network. In this paper, we are proposing a computationally efficient rough set based method for ranking of the documents. The proposed method first expands the user query using WordNet and domain Ontologies and then retrieves documents containing relevant information. The distinctive point of the proposed algorithm is to give more emphasis on the concept combination based on concept presence and its position instead of term frequencies to retrieve relevant information. We have experimented over a set of standard questions collected from TREC, Wordbook, WorldFactBook and retrieved documents using Google and our proposed method. We observed significant improvement in the ranking of retrieved documents.