LivePerson had 18 patents in ecommerce during Q4 2023. LivePerson Inc filed patents related to evaluating intent confusion in conversations between customers and agents, providing conversational interfaces on websites or applications with dynamic content updates, delivering specialized media on websites based on user interactions, and determining predictive model types for web pages based on performance indicators. GlobalData’s report on LivePerson gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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LivePerson grant share with ecommerce as a theme is 38% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Data-driven taxonomy for annotation resolution (Patent ID: US20230410123A1)
The patent filed by LivePerson Inc. describes an intent confusion evaluation engine that assesses conversation data between customers and agents to determine levels of confusion among different intents identified in the messages exchanged. The engine generates a graphical representation illustrating the various intents and their confusion levels, updating dynamically in real-time as annotations are modified. The method involves applying a machine-learning model to ongoing conversation data, generating annotations and metrics, and dynamically creating a graphical representation based on these metrics as conversations progress.
The system and computer-readable storage medium described in the patent store executable instructions that, when executed, perform operations such as receiving conversation data, applying a machine-learning model to generate annotations, and dynamically creating a graphical representation illustrating confusion levels among intents. The system allows for interactions with the graphical representation to modify annotations, re-evaluate conversation data, and update the graphical representation in real-time. The method also includes merging classifications, using confidence scores to assess message associations, and training the machine-learning model with sample conversation data and annotations. Overall, the patent outlines a comprehensive system for evaluating intent confusion in conversations between customers and agents, providing real-time insights into the effectiveness of communication.
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
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.
