期刊
KNOWLEDGE AND INFORMATION SYSTEMS
卷 27, 期 3, 页码 419-450出版社
SPRINGER LONDON LTD
DOI: 10.1007/s10115-010-0298-8
关键词
User interests retention; Unifying search and reasoning; Granularity; Starting point; Multi-level completeness; Multi-level specificity; Multiple perspectives
资金
- European Commission [FP7-215535]
Under the context of large-scale scientific literatures, this paper provides a user-centric approach for refining and processing incomplete or vague query based on cognitive- and granularity-based strategies. From the viewpoints of user interests retention and granular information processing, we examine various strategies for user-centric unification of search and reasoning. Inspired by the basic level for human problem-solving in cognitive science, we refine a query based on retained user interests. We bring the multi-level, multi-perspective strategies from human problem-solving to large-scale search and reasoning. The power/exponential law-based interests retention modeling, network statistics-based data selection, and ontology-supervised hierarchical reasoning are developed to implement these strategies. As an illustration, we investigate some case studies based on a large-scale scientific literature dataset, DBLP. The experimental results show that the proposed strategies are potentially effective.
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