Non-expert users find complex to gain richer insights into the increasingly amount of available data. Advanced data analysis techniques, such as data mining, are difficult to apply due to the fact that (i) a great number of data mining algorithms can be applied to solve the same problem, and (ii) correctly applying data mining techniques always requires dealing with the data quality of sources....

In this survey paper, we discuss biomedical ontologies and major text mining techniques applied to biomedicine and healthcare. Biomedical ontologies such as UMLS are currently being adopted in text mining approaches because they provide domain knowledge for text mining approaches. In addition, biomedical ontologies enable us to resolve many linguistic problems when text mining approaches handle...

Mining information from data: A presentday gold rush. Data Mining is a multidisciplinary field which supports knowledge workers who try to extract information in our “data rich, information poor” environment. Its name stems from the idea of mining knowledge from large amounts of data. The tools it provides assist us in the discovery of relevant information through a wide range of data analysis ...

Text mining or knowledge discovery is that sub process of data mining, which is widely being used to discover hidden patterns and significant information from the huge amount of unstructured written material. The proliferation of clouds, research and technologies are responsible for the creation of vast volumes of data. This kind of data cannot be used until or unless specific information or pa...

Knowledge discovery is a process of non trivial extraction of previously unknown and presently useful information. The rapid advancement of the technology resulted in the increasing rate of data distributions. The data generated from mobile applications, sensor applications, network monitoring, traffic management, weblogs etc. can be referred as a data stream. The data streams are massive in na...

Data Mining techniques plays a vital role like extraction of required knowledge, finding unsuspected information to make strategic decision in a novel way which in term understandable by domain experts. A generalized frame work is proposed by considering non – domain experts during mining process for better understanding, making better decision and better finding new patters in case of selectin...

Relational data mining is the study of methods for knowledge discovery in databases when the database contains information about several types of objects. This, of course, is usually the case when the database has more than one table. Hence, there is little doubt as to the relevance of the area. Relational data mining has its roots in inductive logic programming, an area in the intersection of ...

-In layman terms Data-mining can be related to human cognitive mind where based on previous knowledge and experience we can relate things happening around us or sometimes even predict the future. Data mining is a process of searching data from a pool of data like database, web-servers, cloud based servers etc. and provide a pattern or relationships among those data to produce desired informatio...

In direct marketing large amounts of customer data are collected that might have some complex, non linear relation to customer behavior. Data mining techniques can ooer insight in these relations. In this paper we give a basic introduction in the application of data mining to direct marketing. Best practices for data selection, algorithm selection and evaluation of results are described and ill...