KNN-ROBKP: An Approach for Improvement of Spam Detection over Documents
Shikha sohgaura, Rakesh Kumar Lodhi, Neetesh Gupta · 2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) · 2021
Data spamming over the document is one of the common issue among various articles. Many item such as mail, authentic communication and other media of writing needed proper and unique content without any spamming information. Documents contain information such as privacy preserving data, resource oriented information having the spamming issue as well as duplicity issue. In such scenario the spamming analysis algorithm plays an important role which make easy to identity and stop the data to process. NLP which is natural language processing and spam stoppage help analysis of words, content and its meaning to decide the authenticity. Many approaches used exactness algorithm approach which is limited to some extent. Thus the new KNN based model with NLP is used in given research. Solution for Robin Karp. A hybrid approach is then provided with the term KNN-ROBKPP. The implementation is carried out using the Java language as a parameter with calculation time and similarity measurement. The results obtained indicate that the efficacy of the suggested method is greater than that of the standard N-Gram solution.