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- 108 creator saisai-gong.
- 108 creator wei-hu.
- 108 creator yuzhong-qu.
- 108 type InProceedings.
- 108 label "Leveraging Distributed Human Computation and Consensus Partition for Entity Coreference".
- 108 sameAs 108.
- 108 abstract "Entity coreference is important to Linked Data integration. User involvement is considered as a valuable source of human knowledge that helps identify coreferent entities. However, the quality of user involvement is not always satisfying, which significantly diminishes the coreference accuracy. In this paper, we propose a new approach called coCoref, which leverages distributed human computation and consensus partition for entity coreference. Consensus partition is used to aggregate all distributed user-judged coreference results and resolve their disagreements. To alleviate user involvement, ensemble learning is performed on the consensus partition to automatically identify coreferent entities that users have not judged. We integrate coCoref into an online Linked Data browsing system, so that users can participate in entity coreference with their daily Web activities. Our empirical evaluation shows that coCoref largely improves the accuracy of user-judged coreference results, and reduces user involvement by automatically identifying a large number of coreferent entities.".
- 108 hasAuthorList authorList.
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- 108 keyword "consensus partition".
- 108 keyword "distributed human computation".
- 108 keyword "ensemble learning".
- 108 keyword "entity coreference".
- 108 title "Leveraging Distributed Human Computation and Consensus Partition for Entity Coreference".
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- 118 creator abraham-bernstein.
- 118 creator shen-gao.
- 118 creator thomas-scharrenbach.
- 118 type InProceedings.
- 118 label "The CLOCK Data-Aware Eviction Approach: Towards Processing Linked Data Streams with Limited Resources".
- 118 sameAs 118.
- 118 abstract "Processing streams rather than static files of Linked Data has gained increasing importance in the web of data. When processing data streams system builders are faced with the conundrum of guaranteeing a constant maximum response time with limited resources and, possibly, no prior information on the data arrival frequency. One approach to address this issue is to delete data from a cache during processing – a process we call eviction. The goal of this paper is to show that data-driven eviction outperforms today’s dominant data-agnostic approaches such as first-in-first-out or random deletion. Specifically, we first introduce a method called Clock that evicts data from a join cache based on the likelihood estimate of contributing to a join in the future. Second, using the well-established SR-Bench benchmark as well as a data set from the IPTV domain, we show that Clock outperforms data-agnostic approaches indicating its usefulness for resource limited linked data stream processing.".
- 118 hasAuthorList authorList.
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- 118 keyword "Eviction".
- 118 keyword "Limited resources".
- 118 keyword "Linked data stream processing".
- 118 title "The CLOCK Data-Aware Eviction Approach: Towards Processing Linked Data Streams with Limited Resources".
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- 124 creator enrico-motta.
- 124 creator paul-mulholland.
- 124 creator paul-warren.
- 124 creator trevor-collins.
- 124 type InProceedings.
- 124 label "The usability of Description Logics: Understanding the cognitive difficulties presented by Description Logics".
- 124 sameAs 124.
- 124 abstract "Description Logics have been extensively studied from the viewpoint of decidability and computational tractability. Less attention has been given to their usability and the cognitive difficulties they present, in particular for those who are not specialists in logic. This paper reports on a study into the difficulties associated with the most commonly used Description Logic features. Psychological theories are used to take account of these. Whilst most of the features presented no difficulty to participants, the comprehension of some was affected by commonly occurring misconceptions. The paper proposes explanations and remedies for some of these difficulties. In addition, the time to confirm stated inferences was found to depend both on the maximum complexity of the relations involved and the number of steps in the argument.".
- 124 hasAuthorList authorList.
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- 124 keyword "Cognition".
- 124 keyword "Description Logic usability".
- 124 keyword "Empirical study".
- 124 keyword "Human reasoning".
- 124 title "The usability of Description Logics: Understanding the cognitive difficulties presented by Description Logics".
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- item-1 hasContent paul-warren.
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- 127 creator enrico-motta.