FOMatch: A Fuzzy Ontology-Based Semantic Matching Algorithm of Publish/Subscribe Systems

Zhang, Weiwei; Ma, Jiangang; Ye, Dan

doi:10.1109/cimca.2008.111

Cited by 5 publications

(5 citation statements)

References 8 publications

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“…The matching model in S-TOPSS is Boolean and scoring as a result of matching was not considered. FOMatch [29] proposes the use of fuzzy ontologies that all interacting parties agree upon. FOMatch is the closest to the work presented in this paper but it does not remove explicit semantic coupling from the system and does not free the user from using pre-defined vocabularies.…”

Section: Related Work Approximate Event Matchingmentioning

confidence: 99%

“…All of these works do not use semantic relatedness of events as a factor for ranking. FOMatch [29] considers scoring based on semantic matching and evaluation was conducted using thresholds, however a precisionrecall tradeoff was not investigated.…”

Section: Event Rankingmentioning

confidence: 99%

“…Work focusing on event interoperability such as S-TOPSS [24], FOMatch [29] or the Open Geospatial Consortium's Sensor Web Enablement (SWE) [6] target semantic heterogeneity using common vocabularies/ontologies or other kinds of representation of domains in order to address large scale event heterogeneity. However, tying participants to definitions of domains adds a higher-level explicit dependency between them.…”

Section: Current Approachesmentioning

confidence: 99%

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Approximate semantic matching of heterogeneous events

Hasan

Ó’Riain

Curry

2012

Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems

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Event-based systems have loose coupling within space, time and synchronization, providing a scalable infrastructure for information exchange and distributed workflows. However, event-based systems are tightly coupled, via event subscriptions and patterns, to the semantics of the underlying event schema and values. The high degree of semantic heterogeneity of events in large and open deployments such as smart cities and the sensor web makes it difficult to develop and maintain event-based systems. In order to address semantic coupling within event-based systems, we propose vocabulary free subscriptions together with the use of approximate semantic matching of events. This paper examines the requirement of event semantic decoupling and discusses approximate semantic event matching and the consequences it implies for event processing systems. We introduce a semantic event matcher and evaluate the suitability of an approximate hybrid matcher based on both thesauri-based and distributional semantics-based similarity and relatedness measures. The matcher is evaluated over a structured representation of Wikipedia and Freebase events. Initial evaluations show that the approach matches events with a maximal combined precision-recall F 1 score of 75.89% on average in all experiments with a subscription set of 7 subscriptions. The evaluation shows how a hybrid approach to semantic event matching outperforms a single similarity measure approach.

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Section: Related Work Approximate Event Matchingmentioning

confidence: 99%

Section: Event Rankingmentioning

confidence: 99%

Section: Current Approachesmentioning

confidence: 99%

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Approximate semantic matching of heterogeneous events

Hasan

Ó’Riain

Curry

2012

Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems

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“…In [ 27 ], the authors used ontologies to understand the semantics of events, then correlated and mapped multiple events using relational operators based on subscriptions. In [ 28 ], fuzzy ontology was used, where, again, the events are represented using attribute-value pairs, but the authors add type to their representation.…”

Section: Literature Reviewmentioning

confidence: 99%

An Effective Semantic Event Matching System in the Internet of Things (IoT) Environment

Alhakbani

Hassan

Ykhlef

2017

Sensors

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IoT sensors use the publish/subscribe model for communication to benefit from its decoupled nature with respect to space, time, and synchronization. Because of the heterogeneity of communicating parties, semantic decoupling is added as a fourth dimension. The added semantic decoupling complicates the matching process and reduces its efficiency. Our proposed algorithm clusters subscriptions and events according to topic and performs the matching process within these clusters, which increases the throughput by reducing the matching time from the range of 16–18 ms to 2–4 ms. Moreover, the accuracy of matching is improved when subscriptions must be fully approximated, as demonstrated by an over 40% increase in F-score results. This work shows the benefit of clustering, as well as the improvement in the matching accuracy and efficiency achieved using this approach.

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“…Besides, replicating events with new concepts has the downside of overwhelming the system with a large amount of events. FOMatch [29] proposes the use of fuzzy agreed-upon ontologies. However, it does not free the user from using pre-defined vocabularies.…”

Section: Semantic Event Processingmentioning

confidence: 99%

Thematic event processing

Hasan

Curry

2014

Proceedings of the 15th International Middleware Conference on - Middleware '14

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Event-based systems follow a decoupled mode of interaction between event producers and consumers in space, time, and synchronization to enable scalability within distributed systems. We recognize a fourth dimension of coupling due to the need for mutual agreements on terms that describe event types, attributes, and values. Semantic coupling is challenging in large-scale, open, and heterogeneous environments such as the Internet of Things (IoT). It requires event producers and consumers to agree on event semantics and can limit scalability due to the difficulties in establishing such agreements. In this paper we propose a new thematic event processing approach based on enhancing events and subscriptions with terms representing their themes to clarify their domains and meanings in addition to their payload. Experiments conducted using large heterogeneous sets of smart-city and energy management events suggest up to 85% of matching accuracy at a rate of 500 events/sec of throughput. This represents around 15% improvement in accuracy and 150% in throughput over non-thematic approaches. This suggests the viability of thematic event processing to scale to environments such as the IoT.

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FOMatch: A Fuzzy Ontology-Based Semantic Matching Algorithm of Publish/Subscribe Systems

Cited by 5 publications

References 8 publications

Approximate semantic matching of heterogeneous events

Approximate semantic matching of heterogeneous events

An Effective Semantic Event Matching System in the Internet of Things (IoT) Environment

Thematic event processing

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