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General Information
    • ISSN: 2382-6185
    • Frequency: Quarterly (2015-2016); semiyearly (Since 2017)
    • DOI: 10.18178/IJKE
    • Editor-in-Chief: Prof. Chen-Huei Chou
    • Executive Editor: Ms. Nina Lee
    • Indexed by: Google Scholar, Crossref, ProQuest
    • E-mail: ijke@ejournal.net
Prof. Chen-Huei Chou
College of Charleston, SC, USA
It is my honor to be the editor-in-chief of IJKE. I will do my best to help develop this journal better.
IJKE 2015 Vol.1(1): 68-71 ISSN: 2382-6185
DOI: 10.7763/IJKE.2015.V1.12

Mining Customer Feedback Documents

Eduard Alexandru Stoica and Esra Kahya Özyirmidokuz
Abstract—Managing customer feedback data has become a necessity for firms in order for them to gain competitive advantage in the sector. Analyzing customer complaints’ data to find useful information that’s hidden is an important step in understanding customers. This important, hidden knowledge must be extracted automatically to allow firms to gain a better understanding of the general market and of their own and their competitors' customers. A firm can learn the needs of customers and show how its products and services satisfy these needs by analyzing these documents.
The aim of this research is to summarize and extract data from unstructured customer feedback documents which are about ignoring subscriptions to a telecommunication firm in Turkey. The data are transformed to a collection of documents by generating a document for each record. Text processing techniques are applied. Cosine similarity analysis is used to classify documents into relevant categories. Clusters are determined.

Index Terms—Data mining, text mining, customer feedback data, natural language processing.

E. Kahya-Özyirmidokuz is with the Computer Technologies Department, Erciyes University, Kayseri, Turkey (e-mail: esrakahya@erciyes.edu.tr).
E. A. Stoica is with the Department of Information Economics, Lucian Blaga University, Sibiu, Romania (e-mail: eduard.stoica@ulbsibiu.ro).


Cite: Eduard Alexandru Stoica and Esra Kahya Özyirmidokuz, "Mining Customer Feedback Documents," International Journal of Knowledge Engineering vol. 1, no. 1, pp. 68-71, 2015.

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