SWCTE: Semantic weighted context tagging engine for privacy preserving data mining

Privacy Preserving in Data Mining is a very important area which deals with hiding an individual's sensitive data without affecting the usability of data. In this paper, we put forward a technique to provide privacy preservation of sensitive data based on the semantic context. Our approach encapsulates various techniques of Text-processing, keyphrase extraction, Cooccurrence analysis, ontology construction and query analysis. To handle privacy issues Correlation Based Transformation Strategy (CBTS) is performed on sensitive data, additionally we can add custom properties to the attributes of the ontology to indicate the sensitive data. Our experimental results indicate that our solution is effective in marking the private data using the semantic context of the input text. The main goal of our work is to construct a module which acts as an intermediate step in pre-processing for data mining while preserving the privacy.