Knowledge management scalars over the past decades have developed a verity of techniques that tackle the problem of organizing and managing data, information and knowledge in our society. These techniques were used to manage knowledge on papers and intellectual knowledge as well some digital and binary ones. This research is aimed at evaluating existing Measure of Semantic Relatedness functions. The area that this study is intended for is Multimedia and its corresponding sub-domains. This research takes an analytical approach toward figuring out the level of efficiency for MSR functions if they are to be applied in the domain of multimedia. More than 100 papers and articles on various sub-domains of multimedia were analyzed in order to identify a batch of words for each sub-domain which are most frequent and therefore more likely to be related to the domain of interest. Two set of back to back survey questionnaires were distributed among 89 lecturers of multimedia university. The results of the surveys were further analyzed to figure out the nature if relationship between the relatedness scores generated by MSR functions and those created by human opinion.
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Danoosh is a researcher in the field of Knowledge Engineering and Semantic Web. He holds a Bachelor degree in telecommunication engineering. He has also received a Master's degree in Knowledge Management from Multimedia University. His primary research interest is knowledge engineering and management for the Web of future.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Knowledge management scalars over the past decades have developed a verity of techniques that tackle the problem of organizing and managing data, information and knowledge in our society. These techniques were used to manage knowledge on papers and intellectual knowledge as well some digital and binary ones. This research is aimed at evaluating existing Measure of Semantic Relatedness functions. The area that this study is intended for is Multimedia and its corresponding sub-domains. This research takes an analytical approach toward figuring out the level of efficiency for MSR functions if they are to be applied in the domain of multimedia. More than 100 papers and articles on various sub-domains of multimedia were analyzed in order to identify a batch of words for each sub-domain which are most frequent and therefore more likely to be related to the domain of interest. Two set of back to back survey questionnaires were distributed among 89 lecturers of multimedia university. The results of the surveys were further analyzed to figure out the nature if relationship between the relatedness scores generated by MSR functions and those created by human opinion. 164 pp. Englisch. Bestandsnummer des Verkäufers 9783659367182
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Davoodi DanooshDanoosh is a researcher in the field of Knowledge Engineering and Semantic Web. He holds a Bachelor degree in telecommunication engineering. He has also received a Master s degree in Knowledge Management from Multimedi. Bestandsnummer des Verkäufers 5151490
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Taschenbuch. Zustand: Neu. Knowledge Engineering and Measure of Semantic Relatedness | Evaluation in the Domain of Multimedia | Danoosh Davoodi | Taschenbuch | 164 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659367182 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 106014202
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Knowledge management scalars over the past decades have developed a verity of techniques that tackle the problem of organizing and managing data, information and knowledge in our society. These techniques were used to manage knowledge on papers and intellectual knowledge as well some digital and binary ones. This research is aimed at evaluating existing Measure of Semantic Relatedness functions. The area that this study is intended for is Multimedia and its corresponding sub-domains. This research takes an analytical approach toward figuring out the level of efficiency for MSR functions if they are to be applied in the domain of multimedia. More than 100 papers and articles on various sub-domains of multimedia were analyzed in order to identify a batch of words for each sub-domain which are most frequent and therefore more likely to be related to the domain of interest. Two set of back to back survey questionnaires were distributed among 89 lecturers of multimedia university. The results of the surveys were further analyzed to figure out the nature if relationship between the relatedness scores generated by MSR functions and those created by human opinion.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 164 pp. Englisch. Bestandsnummer des Verkäufers 9783659367182
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Knowledge management scalars over the past decades have developed a verity of techniques that tackle the problem of organizing and managing data, information and knowledge in our society. These techniques were used to manage knowledge on papers and intellectual knowledge as well some digital and binary ones. This research is aimed at evaluating existing Measure of Semantic Relatedness functions. The area that this study is intended for is Multimedia and its corresponding sub-domains. This research takes an analytical approach toward figuring out the level of efficiency for MSR functions if they are to be applied in the domain of multimedia. More than 100 papers and articles on various sub-domains of multimedia were analyzed in order to identify a batch of words for each sub-domain which are most frequent and therefore more likely to be related to the domain of interest. Two set of back to back survey questionnaires were distributed among 89 lecturers of multimedia university. The results of the surveys were further analyzed to figure out the nature if relationship between the relatedness scores generated by MSR functions and those created by human opinion. Bestandsnummer des Verkäufers 9783659367182
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