Association mining has been one of the most intensively researched areas of data mining. However, direct uptake of the resulting technologies has been relatively low. This paper examines some of the reasons why the dominant paradigms in association mining have not lived up to their promise, and argues that a powerful alternative is provided by top-k techniques coupled with appropriate statistic...

Opinion Mining is a promising discipline, defined as an intersection of information retrieval and computational linguistic techniques to deal with the opinions expressed in a document. The field aims at solving the problems related to opinions about products, Politian in newsgroup posts, review sites, comments on Facebook posts and twitter etc. This paper is about to covers the techniques, appl...

Data mining is the process of extracting hidden patterns from data. With data ever increasing in volume, its mining into usable information is becoming increasingly important. Data mining approaches are commonly used in a wide range of profiling services, including marketing, fraud detection, and scientific discovery. e FLAIRS Data Mining special track is devoted to data mining with the aim of...

Case-based reasoning (CBR) systems often refer to diverse data mining functionalities and algorithms. This article locates examples, many from health sciences domains, mapping data mining functionalities to CBR tasks and steps, such as case mining, memory organization, case base reduction, generalized case mining, indexing, and weight mining. Data mining in CBR focuses greatly on incremental mi...

Data Mining is the process of locating potentially practical, interesting and previously unknown patterns from a big volume of data. It plays an important role in result orientation. Data mining can be used in each and every aspect of life. The same is similarly significant in other areas including sales/ marketing, revenue services, sports, health care and insurance etc. The said paper implies...

In this paper a new methodology to detect users accessing terrorist related.In this paper we have focused a variety of techniques, approaches and different areas of the. Are helpful and marked as the important field of data mining Technologies. Website: www.ilk.uvt.nlantalbtextminingLingProfColingDef.pdf.Abstract. In this paper, the concept of data mining was summarized and its significance tow...

Reclaimed mine soils (RMS) which develop on post-mining sites play significant role in Carbon sequestration in new ecosystems, especially in local range on areas disturbed by human activity. This study presents the potential for Carbon sequestration in RMS developing on 3 post surface mining areas in Poland (Central Europe) reforested with Scots pine (Pinus sylvestris L). Research was conducted...

Background &Aim: The results from the analysis of COVID-19 literature by employing text-mining techniques are of particular importance for researchers, policymakers, and planners of medical sciences at the national and international levels, avoiding parallel research and waste of time and budget. The paper explore emerging topics and the trend of scientific words at the national and internation...

The recent advancement in data mining technology to analyze vast amount of data has played an important role in several areas of Business processing. Data mining also opens new threats to privacy and information security if not done or used properly. The main problem is that to hide sensitive information, including personal information, fact or even patterns which are generated by any algorithm...

Data storing and retrieving has been important since decades in the world of information. It makes this process prolific, when the retrieved information becomes smartly meaningful. Data mining is this new flavor. In the recent years data mining is a wide spread and active area of research. Its meaningfulness has gained momentum due to its vast area of applications. One of the popular and potent...