Semantic Computing and Knowledge Building

A special issue of Future Internet (ISSN 1999-5903).

Deadline for manuscript submissions: closed (15 January 2016) | Viewed by 8138

Special Issue Editors

Department of Civil Engineering, Center for Civil Informatics, University of Toronto, Toronto M5S 1A4, Canada
Interests: semantic systems; knowledge management; social network analysis; smart cities
Department of Construction Management, Center for Integrated and Smart BIM (CISBIM), Tianjin University, Tianjin 300072, China
Interests: building information modelling; knowledge management; semantic systems; social network; e-business and e-government

Special Issue Information

Dear Colleagues,

Semantic computing and systems cover the top-down approach of ontology development, as well as the bottom-up approach of natural language processing. Such tools were mainly developed and used by researchers and professionals. Lately, the proliferation of web usage has caused a shift in the practices and theory of semantic computing. In contrast to the controlled environments of ontology, networks of unstructured information sources are created and linked online daily. Knowledge is now what we collectively believe it to be—not only a formalized ontology by professionals. This is what is referred to as the extended mind thesis. Consequently, this has caused a shift in the design of informatics systems, from rule-based approaches, to statistical or mining-based approaches. Knowledge is now dynamic—its construct changes every day. Our role is not just to formalize it, based on innate understanding of a domain, but to discover it from the extended sources online and verify its validity.

This Special Issue will include papers that focus on the following topics:

  1. Implications of the extended mind thesis on knowledge management tools
  2. Using data mining tools to extract knowledge from online sources
  3. Enriching ontologies with new knowledge constructs from online sources
  4. Computation models to merge ontologies and link them to natural language tools
  5. Applications of semantic modeling and systems to validate online knowledge sources
  6. Discovery and handling of mismatches in knowledge sources
  7. Domain-specific cases for implementing semantic tools in knowledge management

Prof. Tamer E. El-Diraby
Prof. Jinyue Zhang
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Ontology
  • Natural language processing
  • Data mining
  • Knowledge extraction
  • Knowledge validation
  • Extended mind thesis
  • Semantic modeling
  • Knowledge applications

Published Papers (1 paper)

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Research

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Article
Ontology-Based Representation and Reasoning in Building Construction Cost Estimation in China
by Xin Liu, Zhongfu Li and Shaohua Jiang
Future Internet 2016, 8(3), 39; https://doi.org/10.3390/fi8030039 - 03 Aug 2016
Cited by 10 | Viewed by 7783
Abstract
Cost estimation is one of the most critical tasks for building construction project management. The existing building construction cost estimation methods of many countries, including China, require information from several sources, including material, labor, and equipment, and tend to be manual, time-consuming, and [...] Read more.
Cost estimation is one of the most critical tasks for building construction project management. The existing building construction cost estimation methods of many countries, including China, require information from several sources, including material, labor, and equipment, and tend to be manual, time-consuming, and error-prone. To solve these problems, a building construction cost estimation model based on ontology representation and reasoning is established, which includes three major components, i.e., concept model ontology, work item ontology, and construction condition ontology. Using this model, the cost estimation information is modeled into OWL axioms and SWRL rules that leverage the semantically rich ontology representation to reason about cost estimation. Based on OWL axioms and SWRL rules, the cost estimation information can be translated into a set of concept models, work items, and construction conditions associated with the specific construction conditions. The proposed method is demonstrated in Protégé 3.4.8 through case studies based on the Measurement Specifications of Building Construction and Decoration Engineering taken from GB 50500-2013 (the Chinese national mandatory specifications). Finally, this research discusses the limitations of the proposed method and future research directions. The proposed method can help a building construction cost estimator extract information more easily and quickly. Full article
(This article belongs to the Special Issue Semantic Computing and Knowledge Building)
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