The IP Street semantic concept search engine minimizes the human bias inherent in keyword patent search and the bureaucratic patent classification system. Rather than merely checking whether a word exists or not in a patent document, our concept search algorithm analyzes the specification and claims of all patent documents, treating them as an interconnected community of documents. Patents which contain more similar words and phrases are considered more semantically similar. An exact keyword match is not required for two patents to be semantically close. However, because the algorithm analyzes the language patterns rather than the simple existence of a word or phrase, the tool often returns highly related documents which don't include a given keyword at all.
Below, our head of product, shows you how our semantic search API can be used to perform prior art searches for patent prosecution, patent litigation, and inter partes reviews.
If you would like to learn more about our patent API, please reach out to us. We are always happy to provide a free trial for you see if IP Street's patent data and patent analytics algorithms are the right solution for your intellectual property analytics needs.
