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Article
Publication date: 21 August 2017

Xiaoming Zhang, Huilin Chen, Yanqin Ruan, Dongyu Pan and Chongchong Zhao

With the rapid development of materials informatics and the Semantic Web, the semantic-driven solution has emerged to improve traditional query technology, which is hard…

Abstract

Purpose

With the rapid development of materials informatics and the Semantic Web, the semantic-driven solution has emerged to improve traditional query technology, which is hard to discover implicit knowledge from materials data. However, it is a nontrivial thing for materials scientists to construct a semantic query, and the query results are usually presented in RDF/XML format which is not convenient for users to understand. This paper aims to propose an approach to construct semantic query and visualize the query results for metallic materials domain.

Design/methodology/approach

The authors design a query builder to generate SPARQL query statements automatically based on domain ontology and query conditions inputted by users. Moreover, a semantic visualization model is defined based on the materials science tetrahedron to support the visualization of query results in an intuitive, dynamic and interactive way.

Findings

Based on the Semantic Web technology, the authors design an automatic semantic query builder to help domain experts write the normative semantic query statements quickly and simply, as well as a prototype (named MatViz) is developed to visually show query results, which could help experts discover implicit knowledge from materials data. Moreover, the experiments demonstrate that the proposed system in this paper can rapidly and effectively return visualized query results over the metallic materials data set.

Originality/value

This paper mainly discusses an approach to support semantic query and visualization of metallic materials data. The implementation of MatViz will be a meaningful work for the research of metal materials data integration.

Details

International Journal of Web Information Systems, vol. 13 no. 3
Type: Research Article
ISSN: 1744-0084

Keywords

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Article
Publication date: 2 February 2015

Georgia Solomou and Dimitrios Koutsomitropoulos

Successful learning infrastructures and repositories often depend on well-organized content collections for effective dissemination, maintenance and preservation of…

Abstract

Purpose

Successful learning infrastructures and repositories often depend on well-organized content collections for effective dissemination, maintenance and preservation of resources. By combining semantic descriptions already lying or implicit within their descriptive metadata, reasoning-based or semantic searching of these collections can be enabled and produce novel possibilities for content browsing and retrieval. The specifics and necessities of such an approach, however, make it hard to assess and measure its effectiveness. The paper aims to discuss these issues.

Design/methodology/approach

Therefore in this paper the authors introduce a concrete methodology toward a pragmatic evaluation of semantic searching in such scenarios, which is exemplified through the semantic search plugin the authors have developed for the popular DSpace repository system.

Findings

The results reveal that this approach can be appealing to expert as well as novice users alike, improve the effectiveness of content discovery and enable new retrieval possibilities in comparison to traditional, keyword-based search.

Originality/value

This paper presents applied research efforts to employ semantic searching techniques on digital repositories and to construct a novel methodology for evaluating the outcomes against various perspectives. Although this is original in itself, value lies also within the concrete and measurable results presented, accompanied by an analysis, that would be helpful to assess similar (i.e. semantic query answering and searching) techniques in the particular scenario of digital repositories and libraries and to evaluate corresponding investments. To the knowledge there has been hardly any other evaluation effort in the literature for this particular case; that is, to assess the merit and usage of advanced semantic technologies in digital repositories.

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Article
Publication date: 13 April 2015

Ahmet Uyar and Farouk Musa Aliyu

The purpose of this paper is to better understand three main aspects of semantic web search engines of Google Knowledge Graph and Bing Satori. The authors investigated…

Abstract

Purpose

The purpose of this paper is to better understand three main aspects of semantic web search engines of Google Knowledge Graph and Bing Satori. The authors investigated: coverage of entity types, the extent of their support for list search services and the capabilities of their natural language query interfaces.

Design/methodology/approach

The authors manually submitted selected queries to these two semantic web search engines and evaluated the returned results. To test the coverage of entity types, the authors selected the entity types from Freebase database. To test the capabilities of natural language query interfaces, the authors used a manually developed query data set about US geography.

Findings

The results indicate that both semantic search engines cover only the very common entity types. In addition, the list search service is provided for a small percentage of entity types. Moreover, both search engines support queries with very limited complexity and with limited set of recognised terms.

Research limitations/implications

Both companies are continually working to improve their semantic web search engines. Therefore, the findings show their capabilities at the time of conducting this research.

Practical implications

The results show that in the near future the authors can expect both semantic search engines to expand their entity databases and improve their natural language interfaces.

Originality/value

As far as the authors know, this is the first study evaluating any aspect of newly developing semantic web search engines. It shows the current capabilities and limitations of these semantic web search engines. It provides directions to researchers by pointing out the main problems for semantic web search engines.

Details

Online Information Review, vol. 39 no. 2
Type: Research Article
ISSN: 1468-4527

Keywords

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Article
Publication date: 30 August 2011

Hannes Mühleisen, Tilman Walther and Robert Tolksdorf

The purpose of this paper is to show the potential of self‐organized semantic storage services. The semantic web has provided a vision of how to build the applications of…

Abstract

Purpose

The purpose of this paper is to show the potential of self‐organized semantic storage services. The semantic web has provided a vision of how to build the applications of the future. A software component dedicated to the storage and retrieval of semantic information is an important but generic part of these applications. Apart from mere functionality, these storage components also have to provide good performance regarding the non‐functional requirements scalability, adaptability and robustness. Distributing the task of storing and querying semantic information onto multiple computers is a way of achieving this performance. However, the distribution of a task onto a set of computers connected using a communication network is not trivial. One solution is self‐organized technologies, where no central entity coordinates the system's operation.

Design/methodology/approach

Based on the available literature on large‐scale semantic storage systems, the paper analyzes the underlying distribution algorithm, with special focus on the properties of semantic information and corresponding queries. The paper compares the approaches and identify their shortcomings.

Findings

All analyzed approaches and their underlying technologies were unable to distribute large amounts of semantic information and queries in a generic way while still being able to react on changing network infrastructure. Nonetheless, as each concept represented a unique trade‐off between these goals, the paper points out how self‐organization is crucial to perform well at least in a subset of them.

Originality/value

The contribution of this paper is a literature review aimed at showing the potential of self‐organized semantic storage services. A case is made for self‐organization in a distributed storage system as the key to excellence in the relevant non‐functional requirements: scalability, adaptability and robustness.

Details

International Journal of Web Information Systems, vol. 7 no. 3
Type: Research Article
ISSN: 1744-0084

Keywords

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Article
Publication date: 1 July 2006

Douglas Tudhope, Ceri Binding, Dorothee Blocks and Daniel Cunliffe

The purpose of this paper is to explore query expansion via conceptual distance in thesaurus indexed collections

Abstract

Purpose

The purpose of this paper is to explore query expansion via conceptual distance in thesaurus indexed collections

Design/methodology/approach

An extract of the National Museum of Science and Industry's collections database, indexed with the Getty Art and Architecture Thesaurus (AAT), was the dataset for the research. The system architecture and algorithms for semantic closeness and the matching function are outlined. Standalone and web interfaces are described and formative qualitative user studies are discussed. One user session is discussed in detail, together with a scenario based on a related public inquiry. Findings are set in context of the literature on thesaurus‐based query expansion. This paper discusses the potential of query expansion techniques using the semantic relationships in a faceted thesaurus.

Findings

Thesaurus‐assisted retrieval systems have potential for multi‐concept descriptors, permitting very precise queries and indexing. However, indexer and searcher may differ in terminology judgments and there may not be any exactly matching results. The integration of semantic closeness in the matching function permits ranked results for multi‐concept queries in thesaurus‐indexed applications. An in‐memory representation of the thesaurus semantic network allows a combination of automatic and interactive control of expansion and control of expansion on individual query terms.

Originality/value

The application of semantic expansion to browsing may be useful in interface options where thesaurus structure is hidden.

Details

Journal of Documentation, vol. 62 no. 4
Type: Research Article
ISSN: 0022-0418

Keywords

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Article
Publication date: 19 June 2017

Keng Hoon Gan and Keat Keong Phang

When accessing structured contents in XML form, information requests are formulated in the form of special query languages such as NEXI, Xquery, etc. However, it is not…

Abstract

Purpose

When accessing structured contents in XML form, information requests are formulated in the form of special query languages such as NEXI, Xquery, etc. However, it is not easy for end users to compose such information requests using these special queries because of their complexities. Hence, the purpose of this paper is to automate the construction of such queries from common query like keywords or form-based queries.

Design/methodology/approach

In this paper, the authors address the problem of constructing queries for XML retrieval by proposing a semantic-syntax query model that can be used to construct different types of structured queries. First, a generic query structure known as semantic query structure is designed to store query contents given by user. Then, generation of a target language is carried out by mapping the contents in semantic query structure to query syntax templates stored in knowledge base.

Findings

Evaluations were carried out based on how well information needs are captured and transformed into a target query language. In summary, the proposed model is able to express information needs specified using query like NEXI. Xquery records a lower percentage because of its language complexity. The authors also achieve satisfactory query construction rate with an example-based method, i.e. 86 per cent (for NEXI IMDB topics) and 87 per cent (NEXI Wiki topics), respectively, compare to benchmark of 78 per cent by Sumita and Iida in language translation.

Originality/value

The proposed semantic-syntax query model allows flexibility of accommodating new query language by separating the semantic of query from its syntax.

Details

International Journal of Web Information Systems, vol. 13 no. 2
Type: Research Article
ISSN: 1744-0084

Keywords

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Article
Publication date: 27 November 2020

Mingwei Tang, Jiangping Chen, Haihua Chen, Zhenyuan Xu, Yueyao Wang, Mengting Xie and Jiangwei Lin

The purpose of this paper is to provide an integrated semantic information retrieval (IR) solution based on an ontology-improved vector space model for situations where a…

Abstract

Purpose

The purpose of this paper is to provide an integrated semantic information retrieval (IR) solution based on an ontology-improved vector space model for situations where a digital collection is established or curated. It aims to create a retrieval approach which could return the results by meanings rather than by keywords.

Design/methodology/approach

In this paper, the authors propose a semantic term frequency algorithm to create a semantic vector space model (SeVSM) based on ontology. To support the calculation, a multi-branches tree model is created to represent the ontology and a set of algorithms is developed to operate it. Then, a semantic ontology-based IR system based on the SeVSM model is designed and developed to verify the effectiveness of the proposed model.

Findings

The experimental study using 30 queries from 15 different domains confirms the effectiveness of the SeVSM and the usability of the proposed system. The results demonstrate that the proposed model and system can be a significant exploration to enhance IR in specific domains, such as a digital library and e-commerce.

Originality/value

This research not only creates a semantic retrieval model, but also provides the application approach via designing and developing a semantic retrieval system based on the model. Comparing with most of the current related research, the proposed research studies the whole process of realizing a semantic retrieval.

Details

The Electronic Library , vol. 38 no. 5/6
Type: Research Article
ISSN: 0264-0473

Keywords

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Article
Publication date: 6 November 2017

Yanti Idaya Aspura M.K. and Shahrul Azman Mohd Noah

The purpose of this study is to reduce the semantic distance by proposing a model for integrating indexes of textual and visual features via a multi-modality ontology and…

Abstract

Purpose

The purpose of this study is to reduce the semantic distance by proposing a model for integrating indexes of textual and visual features via a multi-modality ontology and the use of DBpedia to improve the comprehensiveness of the ontology to enhance semantic retrieval.

Design/methodology/approach

A multi-modality ontology-based approach was developed to integrate high-level concepts and low-level features, as well as integrate the ontology base with DBpedia to enrich the knowledge resource. A complete ontology model was also developed to represent the domain of sport news, with image caption keywords and image features. Precision and recall were used as metrics to evaluate the effectiveness of the multi-modality approach, and the outputs were compared with those obtained using a single-modality approach (i.e. textual ontology and visual ontology).

Findings

The results based on ten queries show a superior performance of the multi-modality ontology-based IMR system integrated with DBpedia in retrieving correct images in accordance with user queries. The system achieved 100 per cent precision for six of the queries and greater than 80 per cent precision for the other four queries. The text-based system only achieved 100 per cent precision for one query; all other queries yielded precision rates less than 0.500.

Research limitations/implications

This study only focused on BBC Sport News collection in the year 2009.

Practical implications

The paper includes implications for the development of ontology-based retrieval on image collection.

Originality value

This study demonstrates the strength of using a multi-modality ontology integrated with DBpedia for image retrieval to overcome the deficiencies of text-based and ontology-based systems. The result validates semantic text-based with multi-modality ontology and DBpedia as a useful model to reduce the semantic distance.

Details

The Electronic Library, vol. 35 no. 6
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 7 April 2015

Ebrahim Karan, Javier Irizarry and John Haymaker

This paper aims to develop a framework to represent semantic web query results as Industry Foundation Class (IFC) building models. The subject of interoperability has…

Abstract

Purpose

This paper aims to develop a framework to represent semantic web query results as Industry Foundation Class (IFC) building models. The subject of interoperability has received considerable attention in the construction literature in recent years. Given the distributed, semantically heterogeneous data sources, the problem is to retrieve information accurately and with minimal human intervention by considering their semantic descriptions.

Design/methodology/approach

This paper provides a framework to translate semantic web query results into the XML representations of IFC schema and data. Using the concepts and relationships in an IFC schema, the authors first develop an ontology to specify an equivalent IFC entity in the query results. Then, a mapping structure is defined and used to translate and fill all query results into an ifcXML document. For query processing, the proposed framework implements a set of predefined query mappings between the source schema and a corresponding IFC output schema. The resulting ifcXML document is validated with an XML schema validating parser and then loaded into a building information modeling (BIM) authoring tool.

Findings

The research findings indicate that semantic web technology can be used, accurately and with minimal human intervention, to maintain semantic-level information when transforming information between web-based and BIM formats. The developed framework for representing IFC-compatible outputs allows BIM users to query and access building data at any time over the web from data providers.

Originality/value

Currently, the results of semantic web queries are not supported by BIM authoring tools. Thus, the proposed framework utilizes the capabilities of semantic web and query technologies to transform the query results to an XML representation of IFC data.

Details

Construction Innovation, vol. 15 no. 2
Type: Research Article
ISSN: 1471-4175

Keywords

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Article
Publication date: 6 July 2021

Shwe Sin Phyo

With the wealth of information available on the World Wide Web, it is difficult for anyone from a general user to the researcher to easily fulfill their information need…

Abstract

Purpose

With the wealth of information available on the World Wide Web, it is difficult for anyone from a general user to the researcher to easily fulfill their information need. The main challenge is to categorize the documents systematically and also take into account more valuable data such as semantic information. The purpose of this paper is to develop a concept-based search system that leverages the external knowledge resources as the background knowledge for getting the accurate and efficient meaningful search results.

Design/methodology/approach

The paper introduces the approach which is based on formal concept analysis (FCA) with the semantic information to support the document management in information retrieval (IR). To describe the semantic information of the documents, the system uses the popular knowledge resources WordNet and Wikipedia. By using FCA, the system creates the concept lattice as the concept hierarchy of the document and proposes the navigation algorithm for retrieving the hierarchy based on the user query.

Findings

The semantic information of the document is based on the two external popular knowledge resources; the authors find that it will be more efficient to deal with the semantic mismatch problems of user need.

Originality/value

The navigation algorithm proposed in this research is applied to the scientific articles of the National Science Foundation (NSF). The proposed system can enhance the integration and exploration of the scientific articles for the advancement of the Scientific and Engineering Research Community.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

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