Toplantı tutanaklarının analizi ile bir karar destek sistemi

Günümüzde veri madenciliği firmalar açısından çok önemli hale gelmiştir. Firmalar sektörde rekabet avantajı sağlayabilmek için veri madenciliği tekniklerini kullanarak büyük veriden işlerine yarayacak, daha önceden keşfedilmemiş, kullanılabilir örüntüler elde eder. Gelişen haberleşme teknolojileri sonucu firmalarda biriken veri yığınları, firmalar için hayati önem taşıyan bilgileri içinde barındırır. Karar vericiler, klasik tekniklerle bu verilerden çıkarımlarda bulunurken, önemli bilgileri gözden kaçırırlar. Veriyi doğru yönetemeyen firmalar ise işlerine yaramayan veri yığınlarında kaybolur. Bir işletmeye ait sayısal platformdaki bu verilerin %80’i metin formundadır. Ancak yapısal olmayan verileri de içeren büyük veri klasik istatistiksel tekniklerle analiz edilen veriler kadar kolay işlenemez. Doğal dil işleme tekniklerinden faydalanılması gerekmektedir. Böylece, soyut ve yığın yapısal olmayan bilgiler, sayısal somut ifadelere dönüştürülebilmektedir. Bu araştırma, Kayseri’de bir imalat fabrikasında yapılan üst düzey toplantıların metin formatındaki tutanaklarını analiz ederek bilgi çıkarımı gerçekleştirmektedir. Yöneticilerin verdiği stratejik kararlarda önemli toplantı sonuçları çok etkilidir. Araştırmanın en genel amacı toplantıların kalitesini artırmaktır. Araştırmada, toplantı tutanaklarından kelime çıkarımı yapılarak, toplantılara ait genel konu başlıkları metin madenciliği ile elde edilecektir. Yöneticiler çeşitli madenleme teknikleriyle gruplanmış konu başlıklarına göre değerlendirme yaparak sonraki toplantıların kalitesini artırarak zaman kazanabilir.

A decision support system by analysis of the meeting reports

Recently, data mining has become crucial for firms. Using data mining, Firms, in order to have comparative advantage in industry / sector / market, obtain patterns that they can utilize and that have not been discovered before. The data accumulated as a result of the advanced communication channels within firms contain crucial information. Decision makers’ undersees important information while they use classical techniques for data analysis. Firms that cannot manage data accurately get lost in piles of data that would not be useful for them. 80% of the data in the quantitative platform belonging to a firm is in text format. However, large data containing non-structural data cannot be analyzed as easily as the data analyzed by using classical statistical techniques. Natural language analysis techniques should be used. In this way, abstract and non-structural data can be converted into concrete and quantitative statements. In this analysis, information is inferred by the analysis of transcripts—in text format—of meetings among senior managers at a manufacturing company in Kayseri. Outcomes of the important meetings are very crucial in the decisions the directors take. The main goal of the study is to increase the efficiency of the meetings. In this research, the general themes of the meetings are found out by word inference from the meeting transcripts. Directors can have better time-management by increasing the quality of the future meetings by conducting evaluations according to the topics categorized by the data mining techniques.

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