Application of Labelled K Means Clustering for GIS Contract Automation
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
Longley, p., Michael, F., Goodchild, D., & Maguire, D., & Rhind, D, (2011), Geographic Information System and Science, 3rd Ed, New York, USA.
Local Government Association, (2013), "Making Saving from Contract Management”, A report by Local Government Association London.
Shaheen, M., Aslam, M., Shahbaz, M., Khan, j., & Shaheen, N., (2011)b, "An Intelligent Mechanism for GIS contracts automation", in World Congress on Engineering and Computer Science, International Conference on Data Mining and Knowledge Engineering, USA.
Contractor performance management strategy. Website of The Scottish Parliament," 2018. [Online]. Website: http://www.parliament.scot/abouttheparliament/65849.aspx. Accessed on: Oct 18, 2018.
Kotsiantis, S., & Pintelas, P., (2004), "Recent advances in clustering: A brief survey", WSEAS Trans. Inform. ScAppl, pp. 73-81.
Coates, A., Carpenter, B., Case, C., Satheesh, S., Suresh, B., Wang t., J. Wu, D., & Y. Ng, A., (2011), "Text detection and character recognition in scene images with unsupervised feature learning", in International Conference on Document Analysis and Recognition.
Jain, A., Murty, M., & Flynn P., (1999), "Data Clustering: A Review", ACM ComputSurv: 31, pp. 264-323.
Jing, L., Ji-hang, C., & Jing-yuhan, S., & Fei, H., (2012), "Brief introduction of backpropagation neural network algorithm and its improvements," AdvIntell Soft Comput; 69, pp. 553-558.
Tan, Y., & Theon, W., (2000), "DocLog: An electronic contract representation language", in 11th International Workshop on Database and Expert System Applications; London, UK.
Perrin, O., & Godart, C., (2004), "An approach to implement contracts as trusted intermediaries", in First IEEE International Workshop on Electronic Contracting.
Pong, M., & SignGate, E., (2001), "Electronic contract signing gateway", in 25th Annual International Computer Software and Applications Conference.
Griffel, F., Boger, M., Weinreich, H., Lamersdorf, W., & Merz, M., (1998), "Electronic contracting with COSMOS – how to establish, negotiate and execute electronic contracts on the Internet", in International Enterprise Distributed Object Computing Workshop.
Kwok, T., & Nguyen, T., (2006), "An enterprise electronic contract management system using dual XML and secure PDF documents", in 10th IEEE Intl Enterprise Distributed Object Computing Conference Workshops.
Dignum, V., Meyer, J., & Weigand, H., (2002), "Towards an organizational-oriented model for agent societies using contracts", in First International Joint Conference on Autonomous Agents and Multiagent Systems, ACM.
Pacheco, O., Carmo, J., (2003) "A role based model of normative specification of organized collective agency and agents interaction", Auton Agents &MultiagentSyst, p. 145–184.
C. Dellarocas, (2001), "Negotiated shared context and social control in open multi-agent systems", R. Conte and C. Dellarocas, ed, Social Order in MAS. Kluwer.
Abdel, B., & Salle, M., (2002), "Integrated Contract Management, 9th workshop of HP Openview University Association", pp. 4-13.
FangChih, L., Tzu-Ying, L., & Yeng-Hun, L., (2009), "Maps and GIS Digitization Procedure Guides", International Collaboration and Promotion of Taiwan E-Learning and Digital Archives Program, pp. 18-42.
Shaheen, M., Shahbaz, M., & Guergachi, A., (2013), "Context based positive and negative spatio temporal association rule mining", Knowl-Based Syst 2013, pp. 261-273.
Shaheen, M., & Khan, Z., (2015), "A method of data Mining for selection of site for wind turbines", Renew SustEnerg Rev 2015.
Shaheen, M., Shahbaz, M., Guergachi, A., & Khan, Z., (2010), "Data mining applications in hydrocarbon exploration", ArtifIntell Rev, pp. 1-18.
Shaheen, M., Shahbaz, M., Guergachi, A., Khan, Z., (2011) b "Mining sustainability indicators to classify hydrocarbon development", Knowl-Based Syst, p. 1159–1168. b
Shaheen, M., Iqbal, S., & Basit, F., (2013) b "Labeled Clustering: A unique method to label unsupervised classes", 8th International Conference on Internet and Secured Transaction, pp. 210-214