Applied Semantic Web Technologies by Vijayan Sugumaran, Jon Atle Gulla

By Vijayan Sugumaran, Jon Atle Gulla

The quick development of semantic net applied sciences, in addition to the truth that they're at quite a few degrees of adulthood, has left many practitioners pressured in regards to the present kingdom of those applied sciences. concentrating on the main mature applied sciences, utilized Semantic internet applied sciences integrates thought with case reviews to demonstrate the background, present nation, and destiny course of the semantic internet. It continues an emphasis on real-world functions and examines the technical and sensible concerns regarding using semantic applied sciences in clever info administration.

The ebook begins with an creation to the fundamentals—reviewing ontology fundamentals, ontology languages, and examine on the topic of ontology alignment, mediation, and mapping. subsequent, it covers ontology engineering concerns and provides a collaborative ontology engineering device that's an extension of the Semantic MediaWiki. Unveiling a singular method of facts and information engineering, the textual content:

* Introduces state-of-the-art taxonomy-aware algorithms
* Examines semantics-based provider composition in shipping logistics
* bargains ontology alignment instruments that use info visualization techniques
* Explains how one can improve the illustration of entity semantics in an ontology
* Addresses demanding situations in tackling the content material production bottleneck

Using case experiences, the booklet offers authoritative insights and highlights invaluable classes realized by means of the authors—information platforms veterans with many years of expertise. They clarify how you can create social ontologies and current examples of the applying of semantic applied sciences in development automation, logistics, ontology-driven enterprise procedure intelligence, choice making, and effort potency in clever houses.

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7 Reasoning Reasoning is the process of inferring new information from an ontology and its instance base. It may be performed on demand or by materialization (Kiryakov et al. 2004). Retrieval by query answering is an example of the former, often implemented by a backward chaining strategy in which the system is charged to establish only the information satisfying the request. Materialization means that inference is performed and the results stored for further usage (also known as forward chaining).

2006) presented an approach to e-learning personalization based on an ontology. A student model is integrated with an ontology, enabling a personalized system to guide a student’s learning process. org/]—This development is for communities and includes home pages of people, links among them, and objects they create and activities they pursue. Coverage treats a person as 1 concept with 10 properties. html]—This ontology is for scientific portals. Coverage (main concept) is by person (agent or organization), publication, and conference and includes 68 classes, 21 data properties, and 57 object properties.

1991). DL forms a decidable subset of first order logic. This decidability is very convenient for reasoning about ontology. , the absence of variables (Bruijn, 2003). This limited expressiveness, however, ensures decidability and improves tractability. DL provides many reasoning services that allow the construction of classification hierarchies and the checking of consistency of the descriptions. These reasoning services can then be used by applications that prefer to use the knowledge represented in the ontology.

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