https://archives.christuniversity.in/files/original/ed12641196017cba35f8f691a892368b.pdf 8a9c50e2ffbe909b6631dfbab5c822e8 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource MPHIL Mphil Mphil Thesis Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An Autonomic Systems approach to Online Retail Systems Creator An entity primarily responsible for making the resource Kurian Devasia Date A point or period of time associated with an event in the lifecycle of the resource 2010 Source A related resource from which the described resource is derived Computer Science Description An account of the resource In 2003, IBM released a document presenting its vision of autonomic computing. In this article, the author observes that the ever increasing complexity of computing systems will cross the borders of human capabilities, leading to systems that are too complex to be administrated by human beings. System administrators will no longer be able to install, configure, maintain and optimize these computing systems of the future. The solution to this problem is developing a technology that allows computing systems to manage themselves. This solution is referred to as autonomic computing. In today??s economic scenario, Online Retail Systems are gaining prominence and day by day increasing in size, leading to complexities difficult to be managed by human beings. E-Commerce Shops with thousands of articles are becoming the rule of the day. With hundreds of articles being added everyday, the administration required for efficient management of these articles, especially display selection, rejection etc are becoming a mind boggling task for human beings to manage. Parallel developments in study of buying behaviors based on various techniques like data mining, decision trees, neural networks etc are gaining significant practical ground, which also increases the complexity to be managed. The basic idea is lay foundation for creation of autonomic systems based on the outputs from behavioral study, inventory management, etc to autonomically handle management of display, inventory predictions etc. The efficiencies achieved should in turn result in higher revenue as well as profits. In short, the study intends to explore the feasibility of applying autonomic techniques for efficient display organization in online retail contexts by borrowing the intelligence from techniques evolving from data mining, artificial intelligence. This paper will address the development of a taxonomy, a model framework for ??autonomic online retail?? systems and the application of related standards. It will also delve into the theoretical background of specific techniques, which can be applied in this scenario. A basic model of the framework is also implemented. The complete implementation of the framework and measurement of the efficiency gains and other effects will be continued in the doctoral research. The design of the framework and also the measurement framework is being discussed in this document.