Paper Details

Data Mining is the process to extract unknown, valid patterns and relationships that provide usefulinformation. Non relational databases are a broad class of database management systems identified by non-adherence tothe widely used relational database management system model. Non relational databases are not built fundamentally ontables, and generally do not use SQL for data manipulation. Non relational database systems are often highly optimizedfor retrieval and appending operations and often offer little functionality beyond record storage. The reduced run-timeflexibility compared to full SQL systems is compensated by marked gains in scalability and performance for certain datamodels Clustering technique defines classes and put objects which are related to them in one class on the other hand inclassification objects are placed in predefined classes. There are various algorithms used for clustering. These are kmeans algorithm, k-medoid algorithm, k-nearest neighbour algorithm, k-mode algorithm etc. K-Modes algorithm is anextension of K-Means and uses simple matching dissimilarity function instead of Euclidean distance. The majordrawback of k-mode is that the user needs to define the centroid points. The nature-inspired harmonic algorithm ishybridized to optimize the k-mode algorithm. Harmonic K-Mode Algorithm is proposed in this work that reduces thecomputation time and improves the execution time for cluster generation.

Sandeep Kaur, Er. Gurleen Kaur Dhaliwal, “Improved Efficiency of NoSql using Optimized K-Mode”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 9, pp. 498-503, September 2017.