Freshworks’s patent involves a computer-implemented method for extracting key-value attributes from unstructured data to compare and generate scores for incidents affecting IT systems. The technology utilizes machine learning and cosine similarity to recommend related incidents for management and resolution. GlobalData’s report on Freshworks gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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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 May 2024 was 43%. Grant share is based on the ratio of number of grants to total number of patents.
Extracting key-value attributes from unstructured data using ml
A recently granted patent (Publication Number: US12001468B1) discloses a computer-implemented method for extracting key-value attributes from unstructured data. The method involves receiving incidents related to unforeseen events affecting IT systems, parsing these incidents for key-value attributes, and using a machine learning model to compare common attributes between incidents. A cosine similarity module computes scores for these attributes, generating a final score by averaging them. The system also includes a recommendation function to rank and identify related incidents for management and resolution, allowing for the resolution of one incident from the top five.
Furthermore, the patent describes a system configured to extract key-value attributes from unstructured data, comprising a parser module, a machine learning model, and a cosine similarity module. The system is designed to parse incidents, compare key-value attributes, compute cosine similarity scores, and generate final scores for incident resolution. Additionally, the system includes instructions for extracting attributes, searching for common attributes, computing cosine similarity, and calculating the L2 norm for vectors. This innovative approach aims to streamline incident management and resolution processes by leveraging machine learning and cosine similarity techniques to identify related incidents and recommend solutions effectively.
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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.
