Data Anonymization for Service Strategy Development and Information Recommendation to Users Based on TF-IDF Method
Kazuhiro Kono, Noboru Babaguchi · International Symposium on Information Theory and its Applications · 2020
This paper proposes a data anonymization method considering service strategies and information recommendations for users. Adopting the TF-IDF method, we attach importance to the personal data attributes required for strategy development and user’s information recommendation in the case of anonymization. As a result, we generate anonymized personal data suitable for the strategy and the recommendation. We examine through simulation that the anonymized data generated by our method leaves information required for the recommendation in more detail.