ForeScout Technologies had two patents in big data during Q4 2023. ForeScout Technologies Inc filed patents for systems and methods to generate entity classification models using text classification of raw text information, as well as for classifying devices on a network by capturing device information, inputting unstructured crowdsourced data into a machine learning model, and classifying the device based on the structured crowdsourced data. GlobalData’s report on ForeScout Technologies gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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ForeScout Technologies grant share with big data as a theme is 0% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Text classification based device profiling (Patent ID: US20230315991A1)
The patent filed by ForeScout Technologies Inc. describes systems and methods for generating an entity classification model using text classification of raw text information of entities. The process involves obtaining raw text information associated with multiple entities, converting the text into character strings, generating numerical vectors for each entity based on these strings, selecting entity properties for classification based on these vectors, and performing classification of a network-connected entity using the selected properties. The method also includes generating a classification model based on the entity properties and applying it to monitor network traffic and classify entities based on probabilities of different entity types.
The system described in the patent includes a memory and a processing device that carries out the steps of obtaining raw text information, converting it into character strings, generating numerical vectors, selecting entity properties for classification, and performing entity classification based on the selected properties. The processing device can also generate a classification model, monitor network traffic, apply the model to classify entities, generate probability vectors for different entity types, and select the entity type with the highest likelihood for classification. The system also involves ranking entity properties based on correlations with numerical vectors and selecting a subset of properties for classification based on this ranking.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
