activity
20112014
most citedExtracting useful rules through improved decision tree induction using information entropy

6 citations · 14 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CR2014★ 2 cited

Phishing Detection in IMs using Domain Ontology and CBA - An innovative Rule Generation Approach

Mohammad S. Qaseem, A. Govardhan

User ignorance towards the use of communication services like Instant Messengers, emails, websites, social networks etc. is becoming the biggest advantage for phishers. It is requi…

cs.DB2014★ 1 cited

Mining Frequent Itemsets (MFI) over Data Streams: Variable Window Size (VWS) by Context Variation Analysis (CVA) of the Streaming Transactions

V. Sidda Reddy, Dr. T. V. Rao, Dr. A. Govardhan

The challenges with respect to mining frequent items over data streaming engaging variable window size and low memory space are addressed in this research paper. To check the varyi…

cs.DB2014

Front End Data Cleaning And Transformation In Standard Printed Form Using Neural Models

Raju Dara, Dr. Ch. Satyanarayana, Dr. A. Govardhan

Front end of data collection and loading into database manually may cause potential errors in data sets and a very time consuming process. Scanning of a data document in the form o…

cs.DB2013

Gcube Indexing

M. Laxmaiah, A. Govardhan

Spatial Online Analytical Processing System involves the non-categorical attribute information also whereas standard Online Analytical Processing System deals with only categorical…

cs.DB2013★ 2 cited

A Conceptual Metadata Framework for Spatial Data Warehouse

M. Laxmaiah, A. Govardhan

Metadata represents the information about data to be stored in Data Warehouses.It is a mandatory element of Data Warehouse to build an efficient Data Warehouse.Metadata helps in da…

cs.LG2013★ 6 cited

Extracting useful rules through improved decision tree induction using information entropy

Mohd Mahmood Ali, Mohd S Qaseem, Lakshmi Rajamani +1

Classification is widely used technique in the data mining domain, where scalability and efficiency are the immediate problems in classification algorithms for large databases. We…