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uml diagrams for alumni - sujitstar - 10-06-2017 A recent trend in society is social networking, a powerful tool for people to meet and interact based on common interests. Data mining is another powerful tool used to understand the vast amounts of data that are produced by social interactions, in order to enhance the services being provided, and for marketing. University alumni systems exist to promote active and ongoing relationships between graduates and their alma mater. This research proposes to incorporate selected features of social networking and data mining into alumni systems. Such an alumni system is termed a smart alumni system (SAS). There are two major contributions of this research, a framework for smart alumni systems, and a proof-of-concept prototype implementation of an SAS subset. The SAS framework expands stakeholder roles beyond alumni to include current students, faculty, staff, and guests. The framework supports social networking style interactions within and across stakeholder types, for activities such as mentoring, fund-raising, curriculum development, etc. In the SAS framework, the primary purpose of data mining is to provide recommendations for establishing associations between stakeholders; a secondary purpose is analyzing results from university and departmental surveys. The proof-of-concept smart alumni system prototype has been implemented as a webbased web system. The prototype implements stakeholder roles for students, faculty and alumni, and supports social networking features of friends, groups and messaging. Basic data mining algorithms are used to provide a ranked list of recommendations for stakeholder relationships for friends or groups. 1 1. INTRODUCTION Alumni are one of the most important assets to any university. They are the people who represent the university in the real world. Many alumni networks were initially started from regional groups of alumni brought together for university fundraising activities. Later, these networks slowly gained added importance in the development of the universities because of their enormous outreach potential that benefits the university and helps current students in their career paths. The alumni groups have been in existence for decades and they are constantly changing with time. There have been very big changes in the recent years with the development of the internet and social networking that forces the alumni system to undergo huge changes. Therefore, it is really important for universities to focus on the alumni networks and find ways to enhance their growth and development. A new intelligent system called Smart Alumni System (SAS) proposed in this thesis offers an inter-mix of traditional alumni systems and social networking sites. A brief study on both systems is undertaken and the important features of these systems are incorporated into the new proposed system. Then the concept of data mining is used to pre-process large and complex datasets in extracting non-obvious patterns of correlations by removing unrelated data (noise) to discover hidden non-obvious patterns that represent valuable knowledge discoveries. It is a process of observing patterns in the data and summarizing the findings in terms of usable information. When carrying out the data mining operations on the system, some essential associations are revealed which should be studied in the development of more useful university alumni systems. This system 2 informs the university of the main areas to seek donations, improve interactions and determine from which parts of the world people are more interested to join the university. This thesis describes SAS and explains the important features and the results of data mining in detail. uml diagrams for alumni - luv2satya - 10-06-2017 Pls give me about Uml diagrams for student alumni portal and ER diagram. |