Assessment For Commercial Potential Of Patent Using Natural Language Programming

According to World Intellectual Property Organization (2017) report, over 3 million patents exist in the patent database, but only certain numbers have commercial potential. Generally, to assess the commercial potential of patent, it consumes time and requires various expertise. Currently, several models have been developed to address this matter, which to assess using questionnaire tool for portfolios by human. So that occurs bias any limitation exists that our research will address by artificial intelligence. Hence, this research applies a Natural Language Programming to assess for commercial potential of patent, consisting of five steps (i) Morphological analysis based on the Lexical database, (ii) Syntactic analysis of sentence to check syntax sentence patterns, (iii) Sematic analysis to interpret the meaning of words derived from the previous step, (iv) Discourse integration from context of domain together with the main sentence providing more accurate sentence analysis, and (v) Pragmatic analysis to ensure the correct meaning of interpretation. Then, the obtained data is used to determine criterion factors and formulate the model for assessing commercial potential of patent using Natural Language programming. This finding should deliver an alternative effective patent assessment system, which addresses some current deficiency in patent's assessment for commercial potential.