機械学習を活用したテキストマイニング : クチコミを用いた商品・サービスカテゴリーの横断分析機械学習を活用したテキストマイニング : クチコミを用いた商品・サービスカテゴリーの横断分析AN00240555 Text Mining using Machine Learning : Cross-sectional Analysis of Products／Service Categories using Reviews
In recent years, AlphaGo developed by google has become a topic notonly in the world of Go but also in society, words related to AI such asmachine learning and deep learning are becoming widely recognized.Advances in these technologies are quick, and discussion about medicalassistance AI which applies image recognition technology is active, and it isexpected to be applied in various fields even now. As an applicationpossibility to management research and management practice,improvement of natural language processing technology in recent years,especially progressive technology concerning distributed representation,can be said to be a fully usable technology.And, it is not a direct competition relationship like a smartphone and adigital camera, www (world wide web) and a book, which is a threat ofsubstitute in Porter’s 5force analysis, that is, competitive relations beyondproduct categories are topics.In this paper, we consider a recent social change and propose a methodto analyze and visualize competing relationships beyond the categories ofgoods and services by machine mining using machine learning (AI)technology. The method of text mining adopted by this paper is not basedon aggregate values such as mainstream current weighing text analysisbut based on the distributed representation of words calculated bymachine learning (fasttext). Therefore, the basis of the analysis is not thesum of the words in the text but the similarity using the distributedrepresentation of the word. Text mining based on distributedrepresentation is still an incomplete technology and it is not a fixedmethod, it is a field where further development is expected in the future.In this paper, we propose two analytical methods using this distributedrepresentation.The method proposed by this paper is useful for business researchers,also for practitioners, when planning and model change of products/services, comparison with other company’s product services becomeseasier than ever, more detailed analysis.