Akimov A. A.

Penza State University, Russia

AUTOMATION OF ACTIVITY OF THE DEPARTMENT

Many universities have already introduced or are developing information systems that automate document circulation and management of the university. For example, some universities [1] used a system based on specialized development of major companies such as Oracle Corporation. In addition, there are a number of systems created by large Russian companies [1].

All of the above systems of automation of the university [1] are based on a modular architecture, and, as a rule, as one of the module acts as a component that provides automation of the department of the university. Such systems should be used throughout the university. If the university does not establish a centralized automation system control by the department to buy it is almost impossible. Also due to the fact that such systems are aimed at the introduction of the university as a whole, they lack some features that are important for the activity of the department: the possibility of a reporting, both on the calendar, and on the school year, analyzing and forecasting activities of the department etc.

In this regard, in the Penza State University, department of ”Computer-aided design” was developed information system, allowing to obtain relevant data on the operation of department, analyzing and forecasting scenarios that provides the automation of the department [2].

Currently, the main management processes of the department are carried out on the basis of document management, records management instructions regulated the university. Structure and rules of the organization and conducting archives of documents are defined. However, the use of these data as a statistical contour of management requires being able to process and accessing in real time. This leads to the use of OLAP technology to effectively manage the system and to enhance its transparency.

When using OLAP (Online Analytical Processing) the information is aggregated and presented in the form of a multidimensional cube whose sides correspond to the different analytical sections (aspects on which the analysis of the data set). The main advantage of using OLAP - a significant increase in speed of response to user requests [2].

To ensure the predictive capabilities of the system uses a technology called Data Mining. The goal of data mining is to extract knowledge from a data set in a human-understandable structure and involves database and data management, data preprocessing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of found structure, visualization and online updating [3]. At the moment, the system uses the following methods of Data Mining: an algorithm of time series, classification, clustering, and association rule learning. Application of Time Series algorithm allows prediction of the number of publications to be published by the department staff in the next year. Classification can be attributed to the existing object attributes of the known groups. The rules for classification can be obtained by examining the signs are already classified objects in one group or another. Clustering is the task of assigning a set of objects into groups (called clusters) so that the objects in the same cluster are more similar (in some sense or another) to each other than to those in other clusters. By means of search of associative rules high probabilities of communications between various events come to light. Details of the methods are described in the [4].

This system operated on a web server Internet Information Server (IIS) running under Windows Server. To use the software modules required Microsoft SQL Server, with the presence of Analysis Services. The server part of the system is implemented in the programming language C #, and ASP .NET MVC framework. To work correctly, the client application requires a browser that meets the requirements: support for standard HTML 4.0, support for JavaScript.

Thanks to its open architecture, the system can integrate with other systems that are used to document, as in other departments, and in the university as a whole. The use of components that can be viewed as a complex, and independently, allows the fabrication of various output documents. The possibility of long-term storage of information, which allows the use of information held for 5-7 years in compiling the report the department for certification of university.

Bibliography

1. Бершадский А.М. Информационная среда мониторинга деятельности кафедры / А.М. Бершадский, И.П. Бурукина, А.А. Акимов // Информационная среда вуза XXI века: материалы IV Международной научно-практической конференции. — Петрозаводск, 2010.— С.47-50.

2. Бершадский А.М. Информационная система кафедрального документооборота / А.М. Бершадский, И.П. Бурукина // Телематика'2009: Труды XVI Всероссийской научно-методической конференции, т. 1. — СПб.: СПбГУ ИТМО, 2009. —С.149-150.

3. Data Mining Curriculum: A Proposal (Version 1.0).— URL: http://www.sigkdd.org/curriculum/CURMay06.pdf

4. Барсегян А.А. Методы и модели анализа данных: OLAP и Data Mining /А.А. Барсегян, М.С. Куприянов, В.В. Степаненко, И.И. Холод. — СПб.: БХВ-Петербург.— 2004.