An ontology-based retrieval system using semantic indexing

Kara, Soner; Alan, Ozgur; Sabuncu, Orkunt; Akpinar, Samet; Cicekli, Nihan Kesim; Alpaslan, Ferda Nur

doi:10.1109/icdew.2010.5452700

Cited by 52 publications

(62 citation statements)

References 15 publications

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“…We do this thing manually using Protégé just for demonstration purposes only. This process can be made automatically by building a crawler that reads the source code and builds the OWL file correspondent to it [8]. The crawler will receive as input the raw source code and will return as output the OWL file corresponding to the built ontology.…”

Section: Fig 3 Individualsmentioning

confidence: 99%

Source Code Plagiarism Detection Method Using Prot�g� Built Ontologies

Smeureanu¹,

Iancu²

2013

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Section: Fig 3 Individualsmentioning

confidence: 99%

Source Code Plagiarism Detection Method Using Prot�g� Built Ontologies

Smeureanu¹,

Iancu²

2013

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“…A scalable alternative to query construction from simple queries is semantic indexing, in which semantic data in RDF 2 knowledge bases is indexed in a structured way and directly available to be searched with simple queries such as keyword-based query. In information retrieval domain, Kara et al (2012) presented an ontology-based information extraction and retrieval system in the soccer domain, in their work, a keyword-based retrieval approach using semantic indexing was proposed.…”

Section: Dr Retrievalmentioning

confidence: 99%

“…However, most of them cannot take full advantage of the semantics embedded in DR so that the retrieved results are far from desired. Although there are a few tools which represent DR using ontology, they are not easy to be used by the end-users because retrieving DR with rich semantics needs formal query languages and formulating a query using such languages normally requires the knowledge of domain ontology as well as the syntax of the language (Kara et al 2012).…”

Section: Introductionmentioning

confidence: 99%

An approach for design rationale retrieval using ontology-aided indexing

Qin

Gao

et al. 2014

Journal of Engineering Design

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Design rationale is an important category of design knowledge. Effective reuse of design rationale depends on its successful retrieval. In this paper, an approach for design rationale retrieval using ontology-aided indexing is presented. First, a design rationale ontology is designed based on the extended IBIS-based design rationale representation in order to effectively utilize the semantics embedded in DR. Then, an ontology-aided indexing method is proposed to build indexes for design rationale records to index the semantic concepts and relationships in DR. Furthermore, three kinds of query modes are developed to support flexible querying, among which natural language input query and DR record based query have much more semantics and thus lead to better retrieval results. Finally, a prototype system is implemented. The experimental results show the effectiveness of the proposed approach.

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“…Ontology can give consistency checking to the separated data in the IE framework. Kara [22] displayed a ontology based data extraction and recovery framework which utilizes ontology for consistency checking. The yield of a customary…”

Section: F Ontology Based Information Extractionmentioning

confidence: 99%

Ontology-Based Approaches for Data Mining: A Survey

2017

IJRTER

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Abstract-Data Mining alludes to the information mining assignments that deliberately consolidate area learning, particularly formal semantics, into the procedure. Numerous exploration endeavors have validated the advantages of fusing area learning in information mining and in the meantime, the expansion of information building has enhanced the group of space learning, particularly formal semantics and Semantic Web ontology. Ontology is an explicit specification of conceptualization and a formal approach to characterize the semantics of information and data. The formal structure of ontology makes it a nature approach to encode area information for the information mining utilization. Keywords -information mining; ontology; data mining I. INTRODUCTION Data mining, otherwise called knowledge discovery from database (KDD), is the methodology of nontrivial extraction of verifiable, beforehand obscure, and possibly valuable data from information [1]. With the recent advances in data mining strategies lead to numerous momentous upsets in information investigation and big data. Data mining likewise joins methods from insights, computerized reasoning, machine learning, database framework, and numerous different controls to examine substantial information sets. Semantic Data Mining alludes to data mining errands that deliberately fuse space learning, particularly formal semantics, into the methodology. Past semantic data mining exploration has bore witness to the positive impact of space learning on data mining. Amid the seeking and pattern generating procedure, area learning can function as an arrangement of former information of requirements to help decrease hunt space and aide the inquiry way [2], [3].To make utilization of area information in the data mining process, the first step must record for speaking to and building the learning by models that the PC can further get to and process. The multiplication of knowledge engineering (KE) has astoundingly improved the group of space learning with strategies that fabricate and utilization area information in a formal manner [4]. Ontology is one of effective knowledge engineering advances, which is the unequivocal determination of a conceptualization [5], [6]. Ontology is created to determine a specific area. Such a ontology, regularly known as space ontology, formally determines the ideas and connections in that area. The encoded formal semantics in ontologies is essentially utilized for viably imparting and reusing of learning and information. Research in the region of the Semantic Web [7] has prompted truly develop benchmarks for demonstrating and arranging area information. At present, Semantic Web ontologies turn into a key innovation for wise learning handling, giving a system to offering calculated models about an area. The Web Ontology Language (OWL) [8], which has developed as the true standard for characterizing Semantic Web ontologies, is broadly utilized for this reason. The Semantic Web advancements that speak to space learning including organized gathering of ...

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An ontology-based retrieval system using semantic indexing

Cited by 52 publications

References 15 publications

Source Code Plagiarism Detection Method Using Prot�g� Built Ontologies

Source Code Plagiarism Detection Method Using Prot�g� Built Ontologies

An approach for design rationale retrieval using ontology-aided indexing

Ontology-Based Approaches for Data Mining: A Survey

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