Larsen & Toubro has patented a method for text summarization involving clustering paragraph-vectors based on user queries. By analyzing similarity, relevant clusters and excerpts are identified and outputted. This innovative approach streamlines text summarization processes efficiently. GlobalData’s report on Larsen & Toubro gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on Larsen & Toubro, Solar-powered EVs was a key innovation area identified from patents. Larsen & Toubro's grant share as of January 2024 was 32%. Grant share is based on the ratio of number of grants to total number of patents.
Text summarization method using paragraph and token clustering
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A recently granted patent (Publication Number: US11822589B2) outlines a method for text summarization using a text summarization device. The method involves receiving an input text with multiple paragraphs and a user query, segregating the text into paragraphs, creating paragraph-vectors, clustering these vectors to generate clusters, and determining a relevant cluster based on similarity to the user query. The system then identifies relevant token-vectors and outputs a summary of relevant paragraphs and excerpts based on the user query.
Furthermore, the patent details the creation of paragraph-vectors from token-vectors, the use of clustering models like hierarchical or K-Means, and the verification of the optimal number of clusters using methods such as silhouette analysis or dendrograms. The system also includes provisions for modifying clustering thresholds based on the number of clusters generated, ensuring an efficient and accurate text summarization process. This innovative method aims to enhance the efficiency and accuracy of text summarization by leveraging advanced clustering and similarity analysis techniques.
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