• Mrs. V. Vetriselvi
• V. Prahatha

Classification of the nodes along with the interconnected semantic edges in a Heterogeneous Information Network (HIN) has a lot of significance in identifying the class labels which involves the application of knowledge and dissemination of knowledge from one node to the other. In this research work, PathSim similarity measure - Host based Intrusion Detection system with Proposed PFSM and Proposed IRGM gives minimum number of rules for detecting the unknown attacks in the network has applied for finding classification techniques along with the use of the well-known MapReduce paradigm to classify the meta-paths in a Heterogeneous Information Network. Applying MapReduce simplified the classification approach which deals with huge data present in the Heterogeneous Information Networks. Experiments were carried out on DARPA dataset, and the results are accurate and successful.

Evaluation of Classification Techniques Using MapReduce for Meta-Path Classification in Heterogeneous Information Networks

"Evaluation of Classification Techniques Using MapReduce for Meta-Path Classification in Heterogeneous Information Networks ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.27-37, June 2019, Available :http://www.jetir.org/papers/JETIRDB06005.pdf

"Evaluation of Classification Techniques Using MapReduce for Meta-Path Classification in Heterogeneous Information Networks ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp27-37, June 2019, Available at : http://www.jetir.org/papers/JETIRDB06005.pdf