Efficient Approach for Land Record Classification and Information Retrieval in Data Warehouse
Year: 2018
Journal of Information and Computing Science, Vol. 13 (2018), Iss. 1 : pp. 3–21
Abstract
A data warehouse collects the recent and ancient data that are used for creating analytical reports and put together to produce useful information. Retrieve the information accurately from a large source of data is a challenging task. A novel ANN-FUZZY-CSO approach is proposed to predict and retrieve the information accurately. First, the artificial neural network (ANN) classifies the input data for ordering the information to construct a database as different classes. Then, the mongo database will store a large amount of data for facilitating easy maintenance, prompt updating of land records and security. After that, the optimized fuzzy ranking function is used to retrieve the information from the database based on the optimal fuzzy rules using cat swarm optimization algorithm. The fuzzy rules provide a ranking for an individual field in the database. The accurate results for the user query are retrieved using cat swarm optimization (CSO) algorithm. The optimized fuzzy rules allow the users for easy access to their records. Finally, the performance is evaluated for the retrieval results
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22459
Journal of Information and Computing Science, Vol. 13 (2018), Iss. 1 : pp. 3–21
Published online: 2018-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 19