Ontology Based Pivoted normalization using Vector Based Approach for information Retrieval
This addresses information retrieval challenges for users, but appears incremental as it builds on existing data mining and vector-based techniques.
The paper tackles the problem of retrieving relevant documents for user queries by proposing a procedural methodology that uses data mining principles and a vector-based statistical approach to represent documents as term sets.
The proposed methodology is procedural i.e. it follows finite number of steps that extracts relevant documents according to users query. It is based on principles of Data Mining for analyzing web data. Data Mining first adapts integration of data to generate warehouse. Then, it extracts useful information with the help of algorithm. The task of representing extracted documents is done by using Vector Based Statistical Approach that represents each document in set of Terms.