In data mining, the classical association rule mining techniques deal with binary attributes; however, real-world data have a variety of attributes (numerical, categorical, Boolean). To deal with the variety of data attributes, the classical association rule mining technique was extended to numerical association rule mining. Initially, the concept of numerical association rule mining started with the discretization method, and later, many other methods, e.g., optimization, distribution are proposed in state-of-the-art. Different authors have presented various algorithms for each numerical association rule mining method; therefore, it is hard to select a suitable algorithm for a numerical association rule mining task. In this article, we present a systematic assessment of various numerical association rule mining methods and we provide a meta-study of thirty numerical association rule mining algorithms. We investigate how far the discretization techniques have been used in the numerical association rule mining methods. Keywords Knowledge discovery in databases • Data mining • Association rule mining • Numerical association rule mining • Quantitative association rule mining This work has been partially conducted in the project "ICT programme" which was supported by the European Union through the European Social Fund. This article is part of the topical collection "Future Data and Security Engineering 2020" guest edited by Tran Khanh Dang.

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Content based image retrieval from large database has become an area of wide interest nowadays in many applications. Content-based image retrieval (CBIR) technique use image content to search and retrieve digital images. Content-based image retrieval (CBIR) is an important research area for manipulating large amount of image databases. In this paper the analysis work is done for finding the spatial features and collects them into a frame to view all the spatial features and the scope of implementing these features into the image retrieval. The commercial image search engines available as on date are: QBIC, VisualSeek, Virage, Netra, PicSOM, FIRE, AltaVista, etc. Region-Based Image Retrieval (RBIR) is a promising extension of CBIR.The shape and spatial features are quite simple to derive and effective, and can be extracted in real time. Our analysis is able to propose a system that has the advantage of increasing the retrieval accuracy and decreasing the retrieval time.

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