The world of digitalisation is changing the way how people and business companies communicate with each other. Electronic negotiations represent one of the most important forms of business communication and can influence the successes and failures of companies in a significant way, whether in interorganisational or intraorganisational processes. Analysing negotiation interactions to determine pattern-based peculiarities in the communication offers new value-adding information concerning the management of optimised communication processes, even though the machine-based processing of communication data bears a series of challenges. The present book develops a new approach to analyse the automated pattern recognition potential of Machine Learning methods in unstructured negotiation communication. It presents holistic research frameworks for the effective detection of structural patterns and reveals the pattern labelling potential in high-dimensional communication data by analytically implementing a series of Machine Learning methods.

Introduction

Application of Data Mining Methods for Pattern Recognition in  Negotiation Support Systems
Advanced Maintenance of Data Richness in Business Communication Data - An Evaluation of Dimensionality Reduction Techniques
Analytical Comparison of Clustering Techniques for the Recognition of Communication Patterns
Pattern Labelling of Business Communication Data
Discussion and Outlook
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