Search for dissertations about: "dissertation on data collection"
Showing result 1 - 5 of 165 swedish dissertations containing the words dissertation on data collection.
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1. On social interaction metrics : social network crawling based on interestingness
Abstract : With the high use of online social networks we are entering the era of big data. With limited resources it is important to evaluate and prioritize interesting data. This thesis addresses the following aspects of social network analysis: efficient data collection, social interaction evaluation and user privacy concerns. READ MORE
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2. Distributed and federated learning of support vector machines and applications
Abstract : Machine Learning (ML) has achieved remarkable success in solving classification, regression, and related problems over the past decade. In particular the exponential growth of digital data, makes using ML inevitable and necessary to exploit the wealth of information hidden inside the data. READ MORE
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3. Bringing Game Analytics to Indie Game Publishing : Method and Tool Support for Indie Mobile Game Publishing
Abstract : With the continuous development of the game industry, the research in the game field is also deepening. Many interdisciplinary knowledge areas and theories have been used to promote the development of the game industry. Business Intelligence (BI) has been applied in game development for game design and game optimization. READ MORE
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4. Task-based Information Seeking and Retrieval in the Patent Domain: Processes and Relationships
Abstract : Information-intensive work tasks in professional settings usually involve dynamic and increasingly complex information handling tasks that include the gathering, assessment, assimilation, and creation of information. Understanding the factors affecting information handling processes, and their interaction, is important and forms the objective of this thesis. READ MORE
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5. High-Performance Computing For Support Vector Machines
Abstract : Machine learning algorithms are very successful in solving classification and regression problems, however the immense amount of data created by digitalization slows down the training and predicting processes, if solvable at all. High-Performance Computing(HPC) and particularly parallel computing are promising tools for improving the performance of machine learning algorithms in terms of time. READ MORE