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Article
Publication date: 11 July 2019

M. Priya and Aswani Kumar Ch.

The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras is…

273

Abstract

Purpose

The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras is noticeably very high. With the availability of these ontologies, the needed information can be smoothly attained, but the presence of comparably varied ontologies nurtures the dispute of rework and merging of data. The assessment of the existing ontologies exposes the existence of the superfluous information; hence, ontology merging is the only solution. The existing ontology merging methods focus only on highly relevant classes and instances, whereas somewhat relevant classes and instances have been simply dropped. Those somewhat relevant classes and instances may also be useful or relevant to the given domain. In this paper, we propose a new method called hybrid semantic similarity measure (HSSM)-based ontology merging using formal concept analysis (FCA) and semantic similarity measure.

Design/methodology/approach

The HSSM categorizes the relevancy into three classes, namely highly relevant, moderate relevant and least relevant classes and instances. To achieve high efficiency in merging, HSSM performs both FCA part and the semantic similarity part.

Findings

The experimental results proved that the HSSM produced better results compared with existing algorithms in terms of similarity distance and time. An inconsistency check can also be done for the dissimilar classes and instances within an ontology. The output ontology will have set of highly relevant and moderate classes and instances as well as few least relevant classes and instances that will eventually lead to exhaustive ontology for the particular domain.

Practical implications

In this paper, a HSSM method is proposed and used to merge the academic social network ontologies; this is observed to be an extremely powerful methodology compared with other former studies. This HSSM approach can be applied for various domain ontologies and it may deliver a novel vision to the researchers.

Originality/value

The HSSM is not applied for merging the ontologies in any former studies up to the knowledge of authors.

Details

Library Hi Tech, vol. 38 no. 2
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 23 August 2011

Ch. Aswani Kumar

The purpose of this paper is to introduce a new hybrid method for reducing dimensionality of high dimensional data.

357

Abstract

Purpose

The purpose of this paper is to introduce a new hybrid method for reducing dimensionality of high dimensional data.

Design/methodology/approach

Literature on dimensionality reduction (DR) witnesses the research efforts that combine random projections (RP) and singular value decomposition (SVD) so as to derive the benefit of both of these methods. However, SVD is well known for its computational complexity. Clustering under the notion of concept decomposition is proved to be less computationally complex than SVD and useful for DR. The method proposed in this paper combines RP and fuzzy k‐means clustering (FKM) for reducing dimensionality of the data.

Findings

The proposed RP‐FKM is computationally less complex than SVD, RP‐SVD. On the image data, the proposed RP‐FKM has produced less amount of distortion when compared with RP. The proposed RP‐FKM provides better text retrieval results when compared with conventional RP and performs similar to RP‐SVD. For the text retrieval task, superiority of SVD over other DR methods noted here is in good agreement with the analysis reported by Moravec.

Originality/value

The hybrid method proposed in this paper, combining RP and FKM, is new. Experimental results indicate that the proposed method is useful for reducing dimensionality of high‐dimensional data such as images, text, etc.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 4 no. 3
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 22 January 2025

Mudofir Mudofir, Septin Puji Astuti, Nurwulan Purnasari, Sabariyanto Sabariyanto, Komali Yenneti and Deinsam Dan Ogan

The purpose of this research is to analyse the development and implementation of waste-to-energy (WtE) power plants as a strategy to manage municipal solid waste (MSW) in…

14

Abstract

Purpose

The purpose of this research is to analyse the development and implementation of waste-to-energy (WtE) power plants as a strategy to manage municipal solid waste (MSW) in Indonesia. It aims to identify key determinants for the successful adoption of WtE technology in developing countries, focusing on the Benowo WtE power plant, Indonesia’s first large-scale WtE project.

Design/methodology/approach

This study reviews the development of the Benowo WtE power plant, examining political, regulatory and financial factors influencing its implementation. It analyses the roles of national and local government institutions, highlighting critical elements for the successful deployment of WtE projects in a developing country context.

Findings

The review shows that the success of WtE projects in Indonesia is significantly influenced by strong local government commitment, supported by political, financial and regulatory backing from the national government. The Benowo WtE power plant’s development demonstrates that with adequate support, WtE can be a viable solution for managing MSW and generating energy in developing countries. The study also identifies barriers to broader WtE adoption in similar contexts.

Research limitations/implications

The study is limited to 12 WtE projects in Indonesia, with in-depth analysis focused on a single case, potentially overlooking challenges and opportunities in other regions. Furthermore, the study does not include an economic analysis, such as a feasibility assessment. Future research could expand to multiple WtE projects and incorporate primary data collection to provide more comprehensive findings, including feasibility studies of each project.

Practical implications

The findings provide practical guidance for policymakers and stakeholders in developing countries, identifying critical areas for successful WtE deployment and offering a blueprint based on the Benowo WtE power plant.

Social implications

Implementing WtE projects can improve waste management, reduce pollution, enhance public health, create jobs and stimulate local economies. The study underscores the importance of government and community collaboration in addressing environmental challenges and fostering shared responsibility.

Originality/value

This research offers novel insights into WtE technology development in a developing country, specifically focusing on Indonesia’s first large-scale WtE power plant. By analysing the Benowo WtE power plant, the study provides valuable lessons and strategies for other developing nations aiming to adopt WtE solutions for MSW management, emphasising the critical role of government support.

Details

International Journal of Energy Sector Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-6220

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