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Keynote: The Use Of Meta-Heuristic Algorithms For Data Mining, Dr. Beatrize De La Iglesia, A. Reynolds
Keynote: The Use Of Meta-Heuristic Algorithms For Data Mining, Dr. Beatrize De La Iglesia, A. Reynolds
International Conference on Information and Communication Technologies
In this paper we explore the application of powerful optimisers known as metaheuristic algorithms to problems within the data mining domain. We introduce some well-known data mining problems, and show how they can be formulated as optimisation problems. We then review the use of metaheuristics in this context. In particular, we focus on the task of partial classification and show how multi-objective metaheuristics have produced results that are comparable to the best known techniques but more scalable to large databases. We conclude by reinforcing the importance of research on the areas of metaheuristics for optimisation and data mining. The combination …
A Dynamic Weight Assignment Approach For Ir Systems, M. Shoaib, Prof Dr. Abad Ali Shah, A. Vashishta
A Dynamic Weight Assignment Approach For Ir Systems, M. Shoaib, Prof Dr. Abad Ali Shah, A. Vashishta
International Conference on Information and Communication Technologies
Weights are assigned to the extracted keywords for partial matching and computing ranking in an IR system. Weight assignment technique is suggested by the IR model that is used for an IR system. Currently suggested weight assignment techniques are static which means that once weight is assigned a keyword it remains unchanged during life-span of an IR system. In this paper, we suggest a dynamic weight assignment technique. This technique can be used by any IR model that supports partial matching.
Using Agents For Unification Of Information Extraction And Data Mining, Sharjeel Imtiaz, Azmat Hussain, Dr. Sikandar Hiyat
Using Agents For Unification Of Information Extraction And Data Mining, Sharjeel Imtiaz, Azmat Hussain, Dr. Sikandar Hiyat
International Conference on Information and Communication Technologies
Early work for unification of information extraction and data mining is motivational and problem stated work. This paper proposes a solution framework for unification using intelligent agents. A Relation manager agent extracted feature with cross feedback approach and also provide a Unified Undirected graphical handle. An RPM agent an approach to minimize loop back proposes pooling and model utilization with common parameter for both text and entity level abstractions.