Towards Optimization and Validation of Different Datamining Models to Support Knowledge Retrieval

Information Technology

Advancements in technologies various new area have emerged. There are various fields like science, engineering, health, business which collect huge amount of data every day. The necessity for effective procedures for information and knowledge location, selection, and retrieval among users has been made even more acute by the internet's rapid development and uptake. Data mining is an important and new area in technologies which manages and extracts the required information. Data mining also known as knowledge discovery in database (KDD) involves extracting interesting, explanatory, and useful information form raw data. This is main reason why the data mining is growing rapidly. This work shows the process of data mining and review its applications such as educational data Mining (EDM), finance, life science and medicine, how it can aid those who make decisions in choosing wisely. The degree and effectiveness of knowledge retrieval are considerably increased by realizing knowledge retrieval through a variety of ways, levels, and multi-modes. Our classification throughout this paper focuses exclusively on research that has been carried out in the recent period. With this classification, the focus is to show the various steps taken in the process of data mining and we present an easy or concise view of the different models that have been optimized for combining knowledge search with data mining technologies.

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