Publish subscribe system based on ontology and XML filtering

Saigaonkar, Swati; Rao, Madhuri; Mantha, S. S.

doi:10.1109/iccrd.2011.5763993

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…Early Pub/Sub systems were mostly topic-based (e.g., a user might be interested in sports or entertainment as publication topics). Modern Pub/Sub systems [42,49,56,62,66] provide a richer, content-based subscription language, with predicates over the content of each incoming publication. Our BAD platform goes beyond this functionality in two ways: First, whether or not newly arrived data is of interest to a user can be based on not only its content, but on its relationships to other data.…”

Section: Publish/subscribe Systemsmentioning

confidence: 99%

“…Past work on active databases [36,48,47,67,73] was never built to scale to modern data sizes and arrival rates. Recently, various systems have been built to actively analyze and distribute incoming data; these include Publish/Subscribe systems [42,49,61,62,66,77] and Streaming Query engines [3,32,33,45,55]. However, these approaches have achieved a compromise by accepting functional constraints in order to scale (e.g, limiting queries to a recent window of data, or supporting a specific class of queries).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

BAD to the Bone: Big Active Data at its Core

Jacobs,

Wang,

Carey

et al. 2020

Preprint

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Virtually all of today's Big Data systems are passive in nature, responding to queries posted by their users. Instead, we are working to shift Big Data platforms from passive to active. In our view, a Big Active Data (BAD) system should continuously and reliably capture Big Data while enabling timely and automatic delivery of relevant information to a large pool of interested users, as well as supporting retrospective analyses of historical information. While various scalable streaming query engines have been created, their active behavior is limited to a (relatively) small window of the incoming data.To this end we have created a BAD platform that combines ideas and capabilities from both Big Data and Active Data (e.g., Publish/Subscribe, Streaming Engines). It supports complex subscriptions that consider not only newly arrived items but also their relationships to past, stored data. Further, it can provide actionable notifications by enriching the subscription results with other useful data. Our platform extends an existing open-source Big Data Management System,

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Section: Publish/subscribe Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

BAD to the Bone: Big Active Data at its Core

Jacobs,

Wang,

Carey

et al. 2020

Preprint

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“…But none of them do semantic filtering. System which focused on XML filtering based on Ontology [5] do exists but structural information was ignored.…”

Section: Introductionmentioning

confidence: 99%

A Structural XPath Query Expansion Approach Based on XML Schema in Publish Subscribe System

Pei

Gao

Liu

et al. 2014

AMM

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XML based publish/subscribe systems are on tremendous rise during recent years. In order to get interested documents, the subscribers submit an XPath Query. In such applications, there is often a mismatch between how publishers describe entities and how different subscribers express their interests. Lots of researches focus on filtering mechanisms, exists such as XFilter, YFilter, Afilter etc, but most of these mechanisms do not use the structural property of XML. This paper proposes an approach which dose XPath query expansion based on structural information. Firstly check query node in OWL classes and return semantically related data performing semantic normalized. Secondly, perform structural expansion depend on the XSD which set constraint on content published. Experiment results show that our approach performs well across a range of XPath queries and documents.

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