Privacy Protection Algorithms
Objective: The objective of this work is to understand automated text anonymization system for protection of personal information of users and after anonymization, should still remain relevant in syntactic and semantics terms, without losing the conveyed meaning of text. Anonymized data can be used in many tasks such as data mining, machine learning, analysis, etc without revealing the identity of entities involved in the creation of data and be useful to improve the accuracy of the applied data analysis tool. Approach: Beyond simply recognizing entities, variation in the types of documents (e.g., financial or medical) and type of identifying information poses a challenge for automated systems. One common approach is to develop domain specific anonymization tools, where one can utilize knowledge about the structure and information content of documents to construct high quality anonymization models , other is to build general models. As different people have different wri