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IPlytics’ entity recognition system allows monitoring a company’s activities across different sources of information. Sorting with complex company tree information and M&A activities, users can also track a company’s activities with regards to worldwide patent files, patent transfers or litigation as well as a company’s activities in scientific publications, business news or technology standards.
Through Artifical Intelligence
Users of IP Analytics tools usually spend most of their time searching and filtering information before they achieve meaningful results that actually answer their questions. IPlytics has developed a keyword refinement tool to help users gain more accurate results faster. Based on natural language processing methods, the IPlytics Keyword Suggestion generates an output set of semantically relevant keywords. Users are thus able to specify or extend their search without losing control of their query.
The IPlytics Artificial Intelligence-based cluster algorithm groups millions of documents into meaningful categories in just a few seconds. A semantic cluster overview allows users to navigate into more specific sub-clusters until deep-diving into the source of information. Network graphs illustrate connections of hidden patterns, directing the user to the relevant information needed.
IPlytics has developed a unique algorithm to compare textual similarities among different document collections e.g. patents, literature or standard documents. Based on a term vector model, the Semantic Search feature understands the content of a given text to identify similarities beyond mutual keyword analyses.