Efficient Approach for Land Record Classification and Information Retrieval in Data Warehouse
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@Article{JICS-13-003,
author = {C. B. David Joel Kishore and T. Bhaskara Reddy},
title = {Efficient Approach for Land Record Classification and Information Retrieval in Data Warehouse},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {13},
number = {1},
pages = {003--021},
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
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22459.html}
}
TY - JOUR
T1 - Efficient Approach for Land Record Classification and Information Retrieval in Data Warehouse
AU - C. B. David Joel Kishore and T. Bhaskara Reddy
JO - Journal of Information and Computing Science
VL - 1
SP - 003
EP - 021
PY - 2024
DA - 2024/01
SN - 13
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22459.html
KW - artificial neural network, cat swarm optimization, data warehouse, fuzzy, mongo database
AB - 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
C. B. David Joel Kishore and T. Bhaskara Reddy. (2024). Efficient Approach for Land Record Classification and Information Retrieval in Data Warehouse.
Journal of Information and Computing Science. 13 (1).
003-021.
doi:
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