Exponentially traditional keyword

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Non-Patent Literature (NPL): For abstract technologies, NPL such as academic papers, technical reports, or proprietary research are also crucial, as many software innovations are not covered by traditional patent documents alone. Patent searchers often rely on semantic search techniques and AI tools to detect subtle, potentially novel features of software inventions samoa b2b leads facing challenges unique to this field. 3. What is the Role of Semantic Search in Patentability Searches? As patent databases grow based searches can miss contextual or subtle relationships between patents. Semantic search leverages AI and natural language processing (NLP) to identify documents related to concepts, even when exact keywords or phrases are not the same.


How it works: Semantic search goes beyond simple keyword matching to identify patents with related ideas, applications, or implementations, even if they use different terminology. Use cases: This is especially useful for inventions where the description is technical, complex, or abstract, such as machine learning algorithms, biotechnology, or cutting-edge materials. Semantic search allows inventors to find potentially overlapping patents that may be hidden in a traditional search. Limitations: While powerful semantic search requires careful interpretation of results, patent claims can be drafted in very specific technical language, which can introduce complexities in terms of precise concept matching.