Application of Labelled K Means Clustering for GIS Contract Automation

  • Muhammad Shaheen Foundation University Islamabad, Pakistan
Keywords: Geographic information system, Back Propagation Neural Network, Clustering, Technical contracts, Contract, BPNN

Abstract

K Means Clustering is an unsupervised classification technique which is suitable for the dataset which do not have any class labels. The absence of labels constrained its application on different text data sets. Labelled K Means clustering generate labels for the clusters obtained from K Means Clustering which makes this technique more decisive for text data sets. A novel application of Labeled K Means Clustering for automation of technical part of GIS contracts is given in this paper. Geographic Information System (GIS) contract which is signed between GIS service provider and a client requires an efficient tracking system during all its vital phases (development, operation and maintenance).  At present, the tracking is done in a non-discrete manner through manual inspection.  Manual tracking is inevitable because (1) no indicators have so far been developed for evaluation by an automatic tracking system, (2) No automated system exists to evaluate the performance of GIS service provider and the client on the basis of performance indicators and (3) there is no centralized mechanism for penalizing negligence of either party.  This paper proposes (1). a method to regulate the technical part of the GIS contract by suggesting a simple and wizard-based Graphical user interface. (2). Conversion of existing manually prepared contracts into electronic contracts through lexeme-based congregation which is done through labelled K Means Clustering. These converted clusters are then stored into centralized database. Back Propagation Neural Network (BPNN) is used to train the system on performance indicators defined for compliance by both contracting parties

Author Biography

Muhammad Shaheen, Foundation University Islamabad, Pakistan

Prof. Dr. Muhammad Shaheen, Ph.D., Professor (Computer Science) HOD (SE) FURC, Foundation University Islamabad, Pakistan was born in Haripur, Pakistan in 1980. He received Bachelors and Mastersdegree in computer science from University of Peshawar in 2000 and 2002 respectively, and the M.Phil degree from Foundation University Islamabad in 2007. He got his Ph.D degree in computer science from University of Engineering & Technology Lahore Pakistan in 2011. He got gold medals in recognition of his performance in M.Sc and M.Phil. In 2003, he joined SidatHyderMorshed Associates Islamabad as computer programmer and in 2004 became Sr. computer programmer. He joined Sui Northern Gas Pipelines Ltd., in the year 2006 where he served as GIS Manager in corporate planning & development department of the company till 2011. He served as Associate Professor (Computer Science) at FAST NUCES Peshawar. Since then he has been serving as Head of Department (Software Engineering) at Foundation University Islamabad. His current research interests include data mining, remote sensing, software metrics, databases, artificial intelligence, industrial problem solving and operations research. Dr. Shaheen has a broader experience of research and development in various domains of computer science. He worked on different projects in the country. He published number of research papers in journals and conferences of international repute. He has also been serving in board of reviewers of different international research journals and conferences. He is a member of SEI, WCE National Academy of science and Informing Science Institute.

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Published
2019-06-30
How to Cite
Shaheen, M. (2019, June 30). Application of Labelled K Means Clustering for GIS Contract Automation. JOURNAL OF ENGINEERING AND APPLIED SCIENCES, 38(1). https://doi.org/https://doi.org/10.25211/jeas.v38i1.2900