Content-based annotation detection and summarization for documents
AssigneeOpen Text Corporation
InventorsSamiksha Kharbanda, Ranjit Boddu
Life of this patent
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Abstract
Systems and methods for context-based annotation analyzation are provided. A system and method provides an artificial intelligence (AI) solution that aims to automate, accelerate, and enhance the accuracy of managing annotations and comments, thereby minimizing the risks associated with manual processing. The system and method leverages AI models to contextually identify and understand annotations within documents, allowing for precise summarization and enabling advanced search capabilities based on these annotations.
Claims20
A method of context-based annotation analyzation, the method comprising:
- obtaining a plurality of documents having annotations;
- for each of the plurality of documents:
- extracting annotation data, text, and corresponding coordinate data, the coordinate data associating the annotation data and the text with at least one corresponding coordinate in the document,
- creating a page chunk for the document, the page chunk combining the annotation data and the text for the document and associating the annotation data and the text data based on the coordinate data, and
- creating an embedding from the annotation data and the text of the respective page chunk and storing the embedding in a vector store;
- in response to a user query, providing the embedding to a Large Language Model (LLM) trained to recognize patterns in annotations;
- and
- generating a response to the user query using an output of the LLM.
A system for context-based annotation analyzation, the system comprising:
- a processor;
- and
- a non-transitory computer readable medium storing instructions translatable by the processor, the instructions when translated by the processor perform:
- obtaining a plurality of documents having annotations;
- for each of the plurality of documents:
- extracting annotation data, text, and corresponding coordinate data, the coordinate data associating the annotation data and the text with at least one corresponding coordinate in the document,
- creating a page chunk for the document, the page chunk combining the annotation data and the text for the document and associating the annotation data and the text data based on the coordinate data, and
- creating an embedding from the annotation data and the text of the respective page chunk and storing the embedding in a vector store;
- in response to a user query, providing the embedding to a Large Language Model (LLM) trained to recognize patterns in annotations;
- and
- generating a response to the user query using an output of the LLM.
A computer program product comprising a non-transitory computer readable medium storing instructions translatable by a processor, the instructions when translated by the processor perform, in an enterprise computing network environment:
- obtaining a plurality of documents having annotations;
- for each of the plurality of documents:
- extracting annotation data, text, and corresponding coordinate data, the coordinate data associating the annotation data and the text with at least one corresponding coordinate in the document,
- creating a page chunk for the document, the page chunk combining the annotation data and the text for the document and associating the annotation data and the text data based on the coordinate data, and
- creating an embedding from the annotation data and the text of the respective page chunk and storing the embedding in a vector store;
- in response to a user query, providing the embedding to a Large Language Model (LLM) trained to recognize patterns in annotations;
- and
- generating a response to the user query using an output of the LLM.
Dependencies are inferred from the claim text.