HubSpot has been granted a patent for an entity resolution system that uses vectorized representations to identify and merge duplicate entities within a database. The system improves data management and enhances sales, marketing, and service activities. GlobalData’s report on HubSpot 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 HubSpot, Predictive modeling techniques was a key innovation area identified from patents. HubSpot's grant share as of January 2024 was 49%. Grant share is based on the ratio of number of grants to total number of patents.
Entity resolution system for identifying and merging duplicate entities
A recently granted patent (Publication Number: US11847106B2) discloses an entity resolution system that utilizes artificial intelligence to identify and merge duplicate entities within a database. The system involves generating vectorized representations of features in entities, reducing them to entity-specific vectors, and arranging them into a two-dimensional matrix. A companion matrix is then generated based on these vectors to determine the likelihood of entities being duplicates of each other. Candidate duplicate entities are identified using a duplicate threshold filter, and a deduplication action is performed by merging the entity with its duplicate within the database.
Furthermore, the system includes features such as a feature encoding scheme for generating vectorized representations, a neural network dimension-reducing tower for generating entity-specific vectors, and an entity deduplication model trained on known duplicate statuses of entities. The companion matrix is generated by multiplying the transposed two-dimensional matrix with the original matrix, with each row reflecting the likelihood of an entity being a duplicate of others in the matrix. The system also includes a training process for the entity deduplication model, where a preconfigured value is compared to duplication likelihood values. Candidate duplicate entities are identified based on threshold values in the companion matrix, and a fixed count set of entities with higher entry values are classified as duplicates. The system is designed to work with core objects or custom objects, utilizing object properties as features for entity resolution.
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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.
