Abstract
The objective of this paper is identification and analysis of the prevention policies of trademark infraction and challenges to find similarity between trademarks. Additionally, this paper proposed an approach to enhance semantic retrieval system of conceptually similar trademarks using algorithms of machine learning like Naive Bayes (NB), Artificial Neural Network (ANN) and Support Vector Machine (SVM). Similarity of trademarks is calculated using Tversky index, Cosine similarity, Jaccard coefficient etc. The performance of classification algorithms are compared on the parameter like accuracy on a same set of trademarks representing real trademark infraction cases. The proposed approach is the first step to automate the process of finding conceptually similar trademarks.
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