Paper Info
Title
Hierarchical Topic Modeling Based on the Combination of Formal Concept Analysis and Singular Value Decomposition.
Abstract
One of the ways to describe the content of internet sources is known as topic modeling, which tries to uncover the hidden thematic structures in document collections. Topic modeling applied to social networks can be useful for analysis in case of crisis situations, elections, launching a new product on the market etc. It becomes popular research area in recent years and represents the methods to browse, search and summarize large amount of the textual data. The main aim of this paper is to describe a new way for topic modeling based on the usage of Formal Concept Analysis combined with reduction by Singular Value Decomposition of the input data matrix. In difference to other common used method for topic modeling our proposed method is able to generate topic hierarchy, which offer more detail analysis of topics within the collection. Our approach is experimentally tested on the selected dataset of Twitter network contributions.
Year
DOI
Venue
2016
10.1007/978-3-319-43982-2_31
MULTIMEDIA AND NETWORK INFORMATION SYSTEMS, MISSI 2016
Keywords
DocType
Volume
Topic modeling,Formal concept analysis,One-sided concept lattices,Singular value decomposition
Conference
506
ISSN
Citations 
PageRank 
2194-5357
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Miroslav Smatana101.69
Peter Butka2418.44