Implementation of Semantic Retrieval by Data Similarity of Trademark |
Author(s): |
Priya Malve , Central India Institute of Technology,Indore; Prof. Megha Singh, Central India Institute of Technology,Indore |
Keywords: |
Data Mining, EDM, K-Means, Decision Tree, Students Data |
Abstract |
A trademarks is a sign that you can use to distinguish your business goods or services from those of other traders. Trademark can be defined expressly in the form of any symbol, logo, titles etc. so, they need to be secure. This project deciphers the hypothetic similarities among trademarks, which happens when more than two or more trademarks hail equal or relevant semantic implant. The state-of-the-art by offering a semantic algorithm to similitude trademarks in pre conditions of hypothetic parallelism. By using data similarity, it is derived that search and indexing technique developed similarity distance. The offered reflow algorithm is confirmed using two resources: a trademark database of conflicting cases and a databases company names. Extends the conceptual model by developing and evaluating a semantic algorithm for trademark retrieval based on conceptual similarity. The conceptual comparison of text documents that share similar domain, use similar concepts, or express similar ideas has been studied extensively. The underlying technology embedded in existing trademark search systems is primarily based on text-based retrieval. Use the different domains to measures the accuracy of the algorithm which gathered different data. |
Other Details |
Paper ID: IJSRDV7I20078 Published in: Volume : 7, Issue : 2 Publication Date: 01/05/2019 Page(s): 2005-2009 |
Article Preview |
|
|