Knowledge Discovery in Temporal Databases

نویسنده

  • Mohamad H. Saraee
چکیده

The essence of data mining is the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. Existing data mining tools consider snapshots of data and therefore unable to handle the complexity of a dynamic environment, such as financial applications which contain a huge amount of data that changes over time. The knowledge discovered has limited value since the temporal nature of data is not taken into account but only the current or latest snapshot. In this paper, we present our framework for data mining in temporal databases. We believe that the next-generation database systems and in particular those that accommodate temporal features are most appropriate platform for knowledge discovery.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Temporal Databases and Frequent Pattern Mining Techniques

Data mining is the process of exploring and analyzing data from different perspective, using automatic or semiautomatic techniques to extract knowledge or useful information and discover correlations or meaningful patterns and rules from large databases. One of the most vital characteristic missed by the traditional data mining systems is their capability to record and process time-varying aspe...

متن کامل

Knowledge Discovery Process Supporting Organizational Learning

This paper stresses the contribution of the process of knowledge discovery in databases for the effective creation and sharing of organizational knowledge. The focus on the process of knowledge discovery has been mainly technological. The paper attempts to enrich that perspective by stressing the insights gained by integrating the knowledge discovery process in the social process of knowledge c...

متن کامل

Data Mining in Temporal Databases

In this paper we describe our approach to data mining in temporal databases by introducing Easy Miner, a data mining system developed at UMIST. This system implements a wide spectrum of data mining functions, including generalisation, relevance analysis, classification and discovery of association rules. By integrating these interesting data mining techniques, the system provides a user friendl...

متن کامل

Discovery of Data Evolution Regularities in Large Databases

A large volume of concrete data may change over time in a database. It is important to catch the general trend of such changes and nd data evolution (changing) regularities in databases in many applications. Because of the large volume of data, data evolution regularity cannot be simply expressed by enumeration of actual data. Machine learning technology should be adopted to extract such regula...

متن کامل

Mining Geo-Referenced Databases: A Way to Improve Decision-Making

Knowledge discovery in databases is a process that aims at the discovery of associations within data sets. The analysis of geo-referenced data demands a particular approach in this process. This chapter presents a new approach to the process of knowledge discovery, in which qualitative geographic identifiers give the positional aspects of geographic data. Those identifiers are manipulated using...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1995