Textual Analysis of Customer Statements for Quality Control and Help Desk Support

Bohnacker, Ulrich; Dehning, Lars; Franke, J.; Renz, Ingrid

doi:10.1007/978-3-642-56181-8_48

Cited by 7 publications

(1 citation statement)

References 6 publications

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“…The term text mining is also often associated with data mining as its upper category. Alternatively, text mining and web mining are described as a special form of data mining [19]. Data mining, also known as knowledge discovery in databases (KDD), is concerned with the search and analysis of large amounts of data and the analysis of recognizable patterns and rules [20].…”

Section: Integrative Text Miningmentioning

confidence: 99%

Knowledge discovery in multidimensional knowledge representation framework

2018

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Visualization of results is one of the central challenges in big data analytics and integrative text mining. With a growing amount of unstructured data and different perspectives on big data, knowledge graphs have difficulties to simultaneously represent and visualize all analyzed dimensions of knowledge. This paper proposes integrative text mining as a solution to combine results from different dimensional analysis in a multidimensional knowledge representation (MKR) for knowledge discovery and visualization purpose. Analysis results from named entity recognition, topic detection, sentiment analysis and the extraction of semantic relationships are, therefore, integrated into a common representation structure. In the implementation part of this research, an application is introduced which utilizes MKR based on the results of stated text mining methods applied on a German and English news data set. State-of-the-art visualizations are used in the application and MKR adaptively transforms the visualization type of the knowledge graph according to the selected context for knowledge discovery.

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Section: Integrative Text Miningmentioning

confidence: 99%