Material Hub: A Semantic Search Engine with Rule Reasoning

Ma, Sen; Wen, Zhao; Zhang, Shikun; Zhang, Hang

doi:10.1109/compsacw.2012.17

Cited by 2 publications

(2 citation statements)

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“…A representação semântica nos buscadores se refere ao uso de ontologias para descrever domínios do conhecimento. As ontologias permitem que as informações sejam modeladas por meio de conceitos, propriedades, relações e axiomas, possibilitando assim que raciocinadores realizem inferências sobre as informações na base de dados (Ma et al, 2012). A representação do conhecimento de um domínio é o primeiro passo para que os buscadores Web tenham acesso aos demais benefícios das ontologias.…”

Section: Representaçãounclassified

“…Enquanto o OWL permite a definição de restrições básicas, o SWRL permite uma maior flexibilidade por meio da criação de regras mais complexas. Por exemplo, Ma et al (2012) utilizam o SWRL para combinar diferentes propriedades em uma mesma regra. Neste trabalho, quando uma consulta de usuário assume uma forma similar a uma regra com restrições, é possível que o sistema identifique e carregue automaticamente a regra correspondente em SWRL e a aplique no processo de inferência.…”

Section: Inferênciaunclassified

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Aplicação de Tecnologias da Web Semântica em Motores de Busca na Internet

Rozsa

Viera

Dutra

2019

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databases, and in the elaboration of queries and the comprehension of the users' needs. We also identified different semantic search engines, usually aimed at specific purposes, rather than generic searches. It was thus verified that SW technologies are used for researchers oriented towards specific contexts, and that researchers with a general purpose use semantic approaches, but not based in the Semantic Web.

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Section: Representaçãounclassified

Section: Inferênciaunclassified

Aplicação de Tecnologias da Web Semântica em Motores de Busca na Internet

Rozsa

Viera

Dutra

2019

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Ontology-based Learning Object Searching Technique with Granular Feature Extraction

Paramartha

Santoso

Hasibuan

2014

Proceedings of the 16th International Conference on Information Integration and Web-Based Applications &Amp; Services

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The development of e-learning cannot be separated from the creation of learning objects which are always improving and more diverse. In this study, we propose a technique to perform learning object searching that use a granular learning object concept using ontology representation. The concept of granular learning objects is done by separating the materials with their sub-materials. A semantic web-based search engine is also used to explore existing learning objects. The result of the research shows that the implementation of granular leaning object ontology, and semantic web-based search engine, can improve searching performance by 29,7% better than search engine which uses document indexbased searching technique. The search results do not only show the general description of a learning object, but can also show the sub-materials and the relationships among those materials. An information in the form of pictures and their descriptions about the retrieved learning object can also be displayed.

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Material Hub: A Semantic Search Engine with Rule Reasoning

Cited by 2 publications

References 5 publications

Aplicação de Tecnologias da Web Semântica em Motores de Busca na Internet

Aplicação de Tecnologias da Web Semântica em Motores de Busca na Internet

Ontology-based Learning Object Searching Technique with Granular Feature Extraction

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