Word morph and topological structures: A graph generating algorithm

Abstract

An algorithm of generating graph structures for the ordering of datasets is proposed. It operates with the key concept of ''sphere neighborhood'' and generates the graph structured ordering of datasets, provided the elements of such sets can be related by some similarity relation. The algorithm always allows determining the shortest path between two nodes in a constructive way. It is demonstrated by an application to the famous Word Morph game and in addition to the ordering of logfiles with respect to the detection of errors. Therefore, the algorithm can be very useful for the dealing with Big Data problems.

A MapReduce‐Based Parallel Frequent Pattern Growth Algorithm for Spatiotemporal Association Analysis of Mobile Trajectory Big Data

“…In the era of data technology (DT) with "Internet +" and "big data ×," large-scale data has been growing rapidly with 5Vs characteristics (i.e., Volume, Velocity, Variety, Value, and Veracity) [1][2][3][4][5][6][7]. Actually, big data usually consists of massive small files in various practical applications such as mobile trajectory data, financial and investment data, business transaction data, and health trajectory data [8].…”