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Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering
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Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Flink: Semantic Web technology for the extraction and analysis of social networks
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Experience management: foundations, development methodology, and internet-based applications
Experience management: foundations, development methodology, and internet-based applications
The SEASALT architecture and its realization within the docQuery project
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Web Semantics: Science, Services and Agents on the World Wide Web
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ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Automatic organization of human task goals for web-scale problem solving knowledge
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In this paper we describe the task of automated mining for solutions to highly specific problems. We do so under the premise of mapping the split view on context, introduced by Brézillon and Pomerol, onto three different levels of abstraction of a problem domain. This is done to integrate the notion of activity or focus and its influence on the context into the mining for a solution. We assume that a problem's context describes key characteristics to be decisive criteria in the mining process to mine successful solutions for it. We further detail on the process of a chain of sub problems and their foci adding up to a meta problem solution and how this can used to mine for such solutions. Through a guiding example we introduce basic steps of the solution mining process and common aspects we deem interesting to be analysed closer in upcoming research on solution mining. We further examine the possible integration of these newly established outlines for automatic solution mining for highly specific problems into a SEASALTexp, a currently developed architecture for explanation-aware extraction and case-based processing of experiences from Internet communities. We thereby gained first insights in issues occurring while trying to integrate automatic solution mining.