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Opems: Online Peer-To-Peer Expertise Matching System, Sharifullah Khan, S.M. Nabeel
Opems: Online Peer-To-Peer Expertise Matching System, Sharifullah Khan, S.M. Nabeel
International Conference on Information and Communication Technologies
Internet is a vital source to disseminate and share information to the masses. This has made information available in abundance on the Web. However, finding relevant information is difficult if not impossible. This difficulty is bilateral between information providers and seekers in terms of information presentation and accessibility respectively. This paper proposed an online Peer-to-Peer Expertise Matching system. The approach provides a highly scalable and self-organizing system and helps individuals in presenting and accessing the information in a consistent format on the Web. This makes the sharing of information among the autonomous organizations successful.
Improving Document Representation By Accumulating Relevance Feedback : The Relevance Feedback Accumulation (Rfa) Algorithm, Razvan Stefan Bot
Improving Document Representation By Accumulating Relevance Feedback : The Relevance Feedback Accumulation (Rfa) Algorithm, Razvan Stefan Bot
Dissertations
Document representation (indexing) techniques are dominated by variants of the term-frequency analysis approach, based on the assumption that the more occurrences a term has throughout a document the more important the term is in that document. Inherent drawbacks associated with this approach include: poor index quality, high document representation size and the word mismatch problem. To tackle these drawbacks, a document representation improvement method called the Relevance Feedback Accumulation (RFA) algorithm is presented. The algorithm provides a mechanism to continuously accumulate relevance assessments over time and across users. It also provides a document representation modification function, or document representation learning …