‎In this paper‎, ‎we propose a new one-step iterative process for a‎ ‎countable family of quasi-nonexpansive multi-valued mappings in a‎ ‎CAT(0) space‎. ‎We also prove strong and $Delta$-convergence theorems‎ ‎of the proposed iterative process under some control conditions‎. ‎Our‎ ‎main results extend and generalize many results in the literature.

Concern about national security has increased after the 26/11 Mumbai attack. In this paper we look at the use of missing value and clustering algorithm for a data mining approach to help predict the crimes patterns and fast up the process of solving crime. We will concentrate on MV algorithm and Apriori algorithm with some enhancements to aid in the process of filling the missing value and iden...

In this paper, we are an overview of already presents frequent item set mining algorithms. In these days frequent item set mining algorithm is very popular but in the frequent item set mining computationally expensive task. Here we described different process which use for item set mining, We also compare different concept and algorithm which used for generation of frequent item set mining From...

Fuzzy C-means (FCM) is an important clustering algorithm with broad applications such as retail market data analysis, network monitoring, web usage mining, and stock prediction. Especially, parameters in FCM have influence on results. However, a lot of did not solve the problem, that is, how to set parameters. In this study, we present kind method for computing values according role process. Ne...

Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. One major problem is the high memory dependency: gigantic data structures built are assumed to fit in main memory; in addition, the recursive mining process to mine these structures is also too voracious in memory resources. This paper proposes a new association rule-mining algorith...

In an inter-organizational setting the manual construction of process models is challenging because the different people involved have to put together their partial knowledge about the overall process. Process mining, an automated technique to discover and analyze process models, can facilitate the construction of inter-organizational process models. This paper presents a technique to merge the...

Tensors are multi-dimensional mathematical objects that allow to model complex relationships and perform decompositions for analytical purpose. They used in a wide range of data mining applications. In social network analysis, tensor give interesting insights by taking into consideration multiple characteristics data. However, the power-law distribution such forces decomposition reveal only str...

Data sanitization is a process that is used to promote the sharing of transactional databases among organizations and businesses, it alleviates concerns for individuals and organizations regarding the disclosure of sensitive patterns. It transforms the source database into a released database so that counterparts cannot discover the sensitive patterns and so data confidentiality is preserved ag...

|The data exploration task can be divided into three interrelated subtasks: (i) feature selection, (ii) discovery, and (iii) interpretation. This paper describes an unsupervised discovery method with biases geared toward partitioning objects into clusters that improve interpretability. The algorithm, ITERATE, employs: (i) a data ordering scheme and (ii) an iterative redistribution operator to p...