SwetoDblp ontology of Computer Science publications

Aleman-Meza, Boanerges; Hakimpour, Farshad; Arpinar, I. Budak; Sheth, Amit P.

doi:10.1016/j.websem.2007.03.001

Cited by 60 publications

(37 citation statements)

References 6 publications

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“…In this study, we use the SwetoDBLP dataset [1], an RDF version of the DBLP dataset. The time interval considered is one year (since DBLP does not contain information related to finer time intervals).…”

Section: Interests Retention Modelsmentioning

confidence: 99%

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User-centric query refinement and processing using granularity-based strategies

et al. 2010

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Under the context of large-scale scientific literatures, this paper provides a usercentric approach for refining and processing incomplete or vague query based on cognitiveand 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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Section: Interests Retention Modelsmentioning

confidence: 99%

“…We carried out some experiments using the SwetoDBLP dataset, an RDF (Resource Description Framework) 1 version of the DBLP Computer Science Bibliography dataset [1]. These results show that the proposed approach can reduce and refine the whole process of querying on large-scale data and provide better results.…”

Section: Introductionmentioning

confidence: 97%

User-centric query refinement and processing using granularity-based strategies

et al. 2010

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“…They are required to search for "intelligence" in the DBLP Search Support Engine 4 that we developed based on the SwetoDBLP dataset (Aleman-Meza et al 2007). Three lists of query results are provided to each of them.…”

Section: Evaluation Of Interests-based Reasearchmentioning

confidence: 99%