Privacy Preserving Document Classification using Convolution Neural Network- A Deep Learning Approach
Darshan Patil, Reena Lokare, Sunita Patil · 2022
Increased digitization in nearly every sector demands huge data storage requirements. Every person upload tons of information related to themselves on Internet through some mobile or web application, knowingly or sometimes unknowingly. Such increasing personal data storage requirement has created data privacy issues. There is no law which prohibits someone from using personal information of an individual. India is still in the process of preparing personal data protection law, whereas European Union's data protection regulation has already took place in the year 2018. Some organizations are in the process of developing applications which can check whether a document is personal or non-personal. Such applications can be developed with the help of deep learning models such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Term Short Memory (LSTM), etc. This research focuses on different text representation techniques required to represent text in text classification problems such as private data classification, sentiment analysis, language detection, online abuse detection, recommendations systems, to name a few. Having represented text in different formats, helps in increasing accuracy of classification algorithms.