Computational Technology Resources - CCP

J. McKechnie

Construction Informatics Research Centre, University of Newcastle upon Tyne, England

doi:10.4203/ccp.61.5.1

J. McKechnie, "Towards Intelligent Information Retrieval for the Construction Industry", in B. Kumar, B.H.V. Topping, (Editors), "Novel Design and Information Technology Applications for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 83-91, 1999. doi:10.4203/ccp.61.5.1

Abstract

In this paper we review current approaches to the improvement of information retrieval systems by means of statistical, artificial intelligence (AI) and information visualisation techniques. We bias our survey in favour of approaches that scale to the needs of practical information retrieval (IR) systems and in particular focus attention on the requirements and potential for IR systems in the construction industry. Most discussions of IR are domain independent, but we intentionally target construction professionals in the belief that by considering a specific class of users, we can provide tools that better fit the needs, habits and working environments of those users.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 61 NOVEL DESIGN AND INFORMATION TECHNOLOGY APPLICATIONS FOR CIVIL AND STRUCTURAL ENGINEERING Edited by: B. Kumar and B.H.V. Topping Paper V.1 Towards Intelligent Information Retrieval for the Construction Industry J. McKechnie Construction Informatics Research Centre, University of Newcastle upon Tyne, England doi:10.4203/ccp.61.5.1 purchase the full-text of this paper Full Bibliographic Reference for this paper J. McKechnie, "Towards Intelligent Information Retrieval for the Construction Industry", in B. Kumar, B.H.V. Topping, (Editors), "Novel Design and Information Technology Applications for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 83-91, 1999. doi:10.4203/ccp.61.5.1 Abstract In this paper we review current approaches to the improvement of information retrieval systems by means of statistical, artificial intelligence (AI) and information visualisation techniques. We bias our survey in favour of approaches that scale to the needs of practical information retrieval (IR) systems and in particular focus attention on the requirements and potential for IR systems in the construction industry. Most discussions of IR are domain independent, but we intentionally target construction professionals in the belief that by considering a specific class of users, we can provide tools that better fit the needs, habits and working environments of those users. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £66 +P&P)
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