Real-word entities can be mapped to unique entity identifiers through an Entity Name System (ENS), to systematically support the re-use of these identifiers and disambiguate references to real world entities in the Web. An entity subscription service informs subscribed users of changes in the descriptive data of an entity, which is a set of attribute name-value pairs. We study the design, implementation and application of an adaptable push-policy subscription service, within a large-scale ENS. The subscription system aims to deliver ranked descriptions of the changes on entities, following user preferences through a feedback-driven adaptation process. The adaptation is based on both the content and the type of each entity change. We evaluate the learning curve of the system and the utility of the content-type discrimination. The experiments demonstrate good results, especially in the system's content-aware adaptation aspect.

Adaptivity in Entity Subscription Services

Giannakopoulos, George;Palpanas, Themistoklis
2009-01-01

Abstract

Real-word entities can be mapped to unique entity identifiers through an Entity Name System (ENS), to systematically support the re-use of these identifiers and disambiguate references to real world entities in the Web. An entity subscription service informs subscribed users of changes in the descriptive data of an entity, which is a set of attribute name-value pairs. We study the design, implementation and application of an adaptable push-policy subscription service, within a large-scale ENS. The subscription system aims to deliver ranked descriptions of the changes on entities, following user preferences through a feedback-driven adaptation process. The adaptation is based on both the content and the type of each entity change. We evaluate the learning curve of the system and the utility of the content-type discrimination. The experiments demonstrate good results, especially in the system's content-aware adaptation aspect.
2009
2009. Computation World. Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns
New York, USA
ACM NY
9780769538624
Giannakopoulos, George; Palpanas, Themistoklis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/76214
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