Text-Mining, Structured Queries, and Knowledge Management on Web Document Corpora

2014 ◽  
Vol 43 (3) ◽  
pp. 48-54 ◽  
Author(s):  
Hamid Mousavi ◽  
Maurizio Atzori ◽  
Shi Gao ◽  
Carlo Zaniolo
Keyword(s):  
Knowledge Management ◽  
Text Mining ◽  
Web Document

Current Issues and Future Analysis in Text Mining for Information Security Applications

2010 ◽  
pp. 694-707
Author(s):  
Shuting Xu
Keyword(s):  
Knowledge Management ◽  
Text Mining ◽  
Limited Attention ◽  
Future Trends ◽  
Information Systems Security ◽  
Security Issues ◽  
Security Applications ◽  
Systems Security ◽  
Technological Developments ◽  
Privacy Issues

Text mining is an instrumental technology that today’s organizations can employ to extract information and further evolve and create valuable knowledge for more effective knowledge management. It is also an important tool in the arena of information systems security (ISS). While a plethora of text mining research has been conducted in search of revamped technological developments, relatively limited attention has been paid to the applicable insights of text mining in ISS. In this chapter, we address a variety of technological applications of text mining in security issues. The techniques are categorized according to the types of knowledge to be discovered and the text formats to be analyzed. Privacy issues of text mining as well as future trends are also discussed.

Using Knowledge Management and Machine Learning to Identify Victims of Human Sex Trafficking

2020 ◽  
pp. 360-389
Author(s):  
Jessica Whitney ◽  
Marisa Hultgren ◽  
Murray Eugene Jennex ◽  
Aaron Elkins ◽  
Eric Frost
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Knowledge Management ◽  
Action Research ◽  
Text Mining ◽  
Research Methodology ◽  
Sex Trafficking ◽  
System Development ◽  
Management Approach ◽  
Unexpected Outcome

Social media and the interactive Web have enabled human traffickers to lure victims and then sell them faster and in greater safety than ever before. However, these same tools have also enabled investigators in their search for victims and criminals. Authors used system development action research methodology to create and apply a prototype designed to identify victims of human sex trafficking by analyzing online ads. The prototype used a knowledge management approach of generating actionable intelligence by applying a set of strong filters based on an ontology to identify potential victims. Authors used the prototype to analyze a dataset generated from online ads from southern California and used the results of this process to generate a revised prototype that included the use of machine learning and text mining enhancements. An unexpected outcome of the second dataset was the discovery of the use of emojis in an expanded ontology.

Current Issues and Future Analysis in Text Mining for Information Security Applications

2010 ◽  
pp. 165-177 ◽  
Author(s):  
Shuting Xu ◽  
Xin Luo
Keyword(s):  
Knowledge Management ◽  
Text Mining ◽  
Limited Attention ◽  
Future Trends ◽  
Information Systems Security ◽  
Security Issues ◽  
Security Applications ◽  
Systems Security ◽  
Technological Developments ◽  
Privacy Issues

Text mining is an instrumental technology that today’s organizations can employ to extract information and further evolve and create valuable knowledge for more effective knowledge management. It is also an important tool in the arena of information systems security (ISS). While a plethora of text mining research has been conducted in search of revamped technological developments, relatively limited attention has been paid to the applicable insights of text mining in ISS. In this chapter, we address a variety of technological applications of text mining in security issues. The techniques are categorized according to the types of knowledge to be discovered and the text formats to be analyzed. Privacy issues of text mining as well as future trends are also discussed.

Advancing Automated Content Analysis in Knowledge Management Research

2019 ◽  
Vol 15 (1) ◽  
pp. 53-68
Author(s):  
Nora Fteimi ◽  
Dirk Basten ◽  
Franz Lehner
Keyword(s):  
Knowledge Management ◽  
Content Analysis ◽  
Organizational Learning ◽  
Text Mining ◽  
Related Compound ◽  
Management Research ◽  
Research Opportunities ◽  
Automated Content Analysis ◽  
Research Themes ◽  
Compound Concepts

This article reports on the development of a knowledge management (KM) dictionary and its application to automated content analysis to investigate topical foci of KM publications and provide an overview of the current research landscape. While automated content analysis gains importance, a problem prevails concerning the use and analysis of compound concepts (e.g., organizational learning). Using a self-developed dictionary of KM-related compound concepts, a sample of 4,290 publications from ten top-ranked KM journals and one KM conference was analyzed using text-mining software. Based on the dictionary approach, this study investigates core research themes of the KM discipline and compares key research interests throughout the IJKM community and those of other outlets. The investigation provides guidance to identify research opportunities in KM and provides useful implications concerning the application of dictionaries. Practitioners might adapt their organizations' approaches to KM accordingly, with regard to prevailing themes and trends in KM research.

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