Open AccessTopological Data Analysis of Two Cases: Text Classification and Business Customer Relationship Management
Author(s) -
Yue Bi
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1550/3/032081
Subject(s) - topological data analysis , computer science , visualization , set (abstract data type) , topology (electrical circuits) , field (mathematics) , data set , data mining , data visualization , data science , artificial intelligence , mathematics , algorithm , pure mathematics , combinatorics , programming language
Topological Data Analysis (TDA) is a rising and burgeoning field of data science, which provides a set of new topological and geometric tools to extract relevant features out of complex high-dimensional data. In this paper, we mainly study two papers: Topological Data Analysis of Time Series Data for B2B Customer Relationship Management [1]; An Introduction to a New Text Classification and Visualization for Natural Language Processing Using Topological Data Analysis [2]. We briefly introduce the topological concepts involved in the two cases, then compare and analyze the corresponding topological solutions. Accordingly, we summarize the advantages of TDA and finally draw a conclusion with some improvements to optimize them.