Distributed Data Mining (DDM) is a branch of the field of data mining that offers a framework to mine distributed data paying careful attention to the distributed data and computing resources. In the DDM literature, one of two assumptions is commonly adopted as to how data is distributed across sites: homogeneously and heterogeneously. Both

Jun 1, 2023 · We propose a public opinion association rules analysis architecture. We design an incremental association rules mining framework to deal with both inserted and deleted data. We explain how our framework resolves redundant computation and describe its …

Efficient parallelization of association rule mining is particularly important for scalability. Some of the data and task parallel algorithms for both distributed and shared memory systems are reviewed in this chapter.

Parallel and distributed computing is a useful approach for enhancing the data mining process. The aim of this research is to present a systematic review of parallel association rule mining (PARM) and distributed association rule mining (DARM) approaches.

In this paper an Optimized Distributed Association Rule mining algorithm for geographically distributed data is used in parallel and distributed environment so that it reduces communication costs. Association rule mining (ARM) has become one of the core data mining tasks and has attracted tremendous interest among data mining researchers.

We presented an efficient distributed and parallel incremental algorithm to deal with this problem. In particular, we presented techniques to minimize the response time to a query for the global set of frequent itemsets, as well as to find high-contrast frequent itemsets.

Mar 31, 2020 · In this paper, a framework is proposed for incremental parallel interesting association rule mining algorithm for Big Data. The proposed framework incorporates interestingness measures...

Aug 1, 2018 · This paper will combine MapReduce and incremental data, and then develop and design incremental association rules based on MapReduce and combine the mathematical theory to design the mining...

Finding a Perfect Matching: The Parallel Algorithm Ideas Not parallelizable: G may have many perfect matchings, the processors must be coordinated to search for the same matching! IDEA: isolate a perfect matching and then employ the algorithm HOW? assign random weights and look for the minimum weight matching

Sep 5, 2019 · we are considering all parallel algorithms and their cor responding parent algorithms, performance criteria including their year of publication. Relationship hierarchy of all the parallel ...