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Full-Text Articles in Databases and Information Systems
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.
Visualization Of Retrieved Positive Data Using Blending Function, Muhammad Shoaib, Habib -Ur- Rehman, Dr. Abad Ali Shah
Visualization Of Retrieved Positive Data Using Blending Function, Muhammad Shoaib, Habib -Ur- Rehman, Dr. Abad Ali Shah
International Conference on Information and Communication Technologies
Data visualization is an important technique used in data mining. We present the retrieved data into visual format to discover features and trends inherent to the data. Some features of the data to be retrieved are already known to us. Visualization should preserve these known features inherent to the data. Positivity is one such known feature that is inherent to most of the scientific and business data sets. For example, mass, volume and percentage concentration are meaningful only when they are positive values. However certain visualization techniques do not guarantee to preserve this feature while constructing visualization of retrieved data …
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 …
Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin
Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin
Research Collection School Of Computing and Information Systems
Relevance feedback has been shown as an important tool to boost the retrieval performance in content-based image retrieval. In the past decade, various algorithms have been proposed to formulate relevance feedback in contentbased image retrieval. Traditional relevance feedback techniques mainly carry out the learning tasks by focusing lowlevel visual features of image content with little consideration on log information of user feedback. However, from a long-term learning perspective, the user feedback log is one of the most important resources to bridge the semantic gap problem in image retrieval. In this paper we propose a novel technique to integrate the log …