Usefulness and applications of data mining in extracting information from different perspectives

Abstract

Discusses the concept of data mining that has emerged as a technique of discovering new meaning in data implicit in a large data warehouse, in order to facilitate better strategies and smart decisions. The standard tasks involved in data mining process are explained. Such pattern-seeking techniques usually performed with a wide range of related areas (viz. statistics, neural networks, genetic algorithms, machine learning, pattern recognition, knowledge-based systems, etc.) are described. Draws attention to useful applications of data mining in varying degrees and illustrates the benefit of this powerful technology with several instances of providing solutions to challenging problems. Also focuses on bibliomining opportunities to be useful to information retrieval, semantic analysis of unstructured texts, web-usage mining and to make proactive as well as knowledge-driven decision across library services; that help researchers in linking information for novel discovery and insight. The discussion illuminates the wrong things that happen with data mining applications and cautionary tales for avoiding serious consequences. Suggests use of data mining in combination with other techniques of evaluation, exploiting large data warehouses by skilled specialists, and advises for ethical uses without privacy invasion.