Freshworks has been granted a patent for a computer-implemented method that automatically extracts situations from conversations between users and bots. The method involves generating abstract knowledge graphs, pruning redundant information, and converting manifests into situation images using machine learning models. GlobalData’s report on Freshworks gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Freshworks, Location-based IM was a key innovation area identified from patents. Freshworks's grant share as of April 2024 was 63%. Grant share is based on the ratio of number of grants to total number of patents.

Automatic extraction of situations from conversations for knowledge graphs

Source: United States Patent and Trademark Office (USPTO). Credit: Freshworks Inc

A recently granted patent (Publication Number: US11954436B2) discloses a computer-implemented method for generating abstract knowledge graphs from textual conversations between users and bots or other users. The method involves creating manifests by pruning the knowledge graph to eliminate redundant information, segmenting the pruned graph into multiple manifests, and converting these manifests into situation images based on predicted probabilities from machine learning models. The system also includes steps for preprocessing conversations, removing tags, evaluating confidence levels, discarding ambiguous tags, and summarizing situation-based text after segmentation.

Furthermore, the patent describes a computer program and system embodying the method, with additional functionalities such as detecting animate or inanimate entities, initializing manifests with sentences, evaluating sentence links, and summarizing situation-based text. The program and system also involve data enrichment models, name entity recognition models, and syntactic information to identify entities, along with event analysis modules for extracting events information and validating against event chains. Overall, the patent outlines a comprehensive approach to processing textual conversations, generating knowledge graphs, and creating situation images to enhance user-bot interactions based on machine learning predictions.

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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.