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Web intelligence in practice

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Journal of Service Science Research

Abstract

Modern service enterprises are challenged by a strong competition and dynamically changing business environments. Consequently, the precision of the business requirements identification and rigorous planning regarding investments to information technologies play a key role in the implementation of new capabilities. As the business today is more and more powered by information that is unstructured, social and distributed via various channels, the multi-channel interaction is a reality. It means each customer generates more and more data. On the other hand, a customer is often flooded with a huge amount, mostly not relevant, advertising information. Companies are challenged to collect the data from the customer interaction, analyze it and prepare an intelligent recommendation for an agent or to feed relevant offers to the customer. Modern understanding of the unstructured information requires a fundamentally new approach using the technology to deliver insights, ideas, and an intuition into the rapidly growing and diverse data that customers deal with every day. A hot topic is to decrease the costs and increase the customer satisfaction. One of the sensitive areas is customers’ interaction via company’s contact web forms. This interaction consists mostly of questions or complaints. Accordingly, we describe in our paper a new approach for generating these contact forms using the textual analytics, processing of frequently asked questions and a rule-based system. We also present particular use-cases to illustrate how this approach works in practice.

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Authors and Affiliations

  1. Department of Information Systems, Faculty of Management, Comenius University in Bratislava, Bratislava, Slovakia

    Eugen Molnár & Michal Greguš

  2. Imperial College Business School, Imperial College, London, USA

    Rastislav Molnár

  3. Department of eBusiness, School of Business, Economics and Statistics, University of Vienna, Vienna, Austria

    Natalia Kryvinska

Authors
  1. Eugen Molnár
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  2. Rastislav Molnár
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  3. Natalia Kryvinska
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  4. Michal Greguš
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Correspondence to Eugen Molnár.

Additional information

Eugen Molnár is a Solution Architect in HP Slovakia and a researcher at the Department of information systems of Comenius University in Bratislava. He has experience in the Enterprise Architecture, Big Data and Data Analysis, SOA, Integration, Testing and HP Autonomy software. He has more than 10 years research experience in Artificial Intelligence and his current research is oriented in the areas of DSS for Big Data, Analytics and Text Mining.

Rastislav Molnár is a PhD student at the Imperial College Business School, Imperial College London. His research interests cover empirical asset pricing, market microstructure, textual analysis and Big Data. He is currently working on the projects related to the news analysis and impact of news on stock market.

Natalia Kryvinska is a Senior Researcher at the e-Business research group, Faculty of Business, Economics and Statistics, University of Vienna. She received her diploma engineer degree in telecommunications from National University “Lviv Polytechnics,” Lviv, Ukraine, and a PhD in electrical engineering from the Vienna University of Technology, Vienna, Austria. Her research interests include distributed systems management, service delivery platforms, and e-Services.

Michal Greguš is currently a professor at the Comenius University in Bratislava. He is head of the Department of Information Systems. His main interests are in the field of ICT. Prof. Greguš obtained his PhD degree is in the field of mathematical analysis. He was working for few years at the Joint Institute for Nuclear Research in Dubna, mainly on computer mathematical modeling. He is also a vice-dean for international relations at the Faculty of Management.

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Molnár, E., Molnár, R., Kryvinska, N. et al. Web intelligence in practice. J Serv Sci Res 6, 149–172 (2014). https://doi.org/10.1007/s12927-014-0006-4

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