Systems and methods for structuring information in a collaboration environment
AssigneeRingCentral, Inc.
InventorsVadim Zhuk, Helen Prask, Ivan Anisimov, William Zhuk
Life of this patent
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Abstract
A computer-implemented machine learning method for improving a collaboration environment is provided. The method comprises receiving text data for one or more users of the collaboration environment. The method further comprises generating a statement by partitioning the text data. The method further comprises determining an act using the statement and generating a thread using at least the statement and the act. The method further comprises generating an actor list using at least the thread, and generating an actionable item using the actor list and the thread.
Claims20
A computer-implemented machine learning method for improving a collaboration environment, the method comprising:
- receiving text data for one or more users of the collaboration environment;
- generating a statement by partitioning the text data;
- generating an actor list using at least the statement;
- determining an act using the statement, wherein determining the act comprises extracting feature data and semantic vector data from the statement, and processing the feature data and the semantic vector data using a trained machine learning model;
- and
- determining first relational information between a first actor and a second actor in the actor list, wherein the determining comprises processing the statement using the trained machine learning model.
A machine learning system for improving a collaboration environment, the system comprising:
- a processor;
- a memory operatively connected to the processor and storing instructions that, when executed by the processor, cause:
- receiving text data for one or more users of the collaboration environment;
- generating a statement by partitioning the text data;
- generating an actor list using at least the statement;
- determining an act using the statement, wherein determining the act comprises extracting feature data and semantic vector data from the statement, and processing the feature data and the semantic vector data using a trained machine learning model to determine the act;
- and
- determining first relational information between a first actor and a second actor in the actor list, wherein the determining comprises processing the statement using the trained machine learning model.
A non-transitory, computer-readable medium storing instructions that, when executed by a processor, cause:
- receiving text data for one or more users of the collaboration environment;
- generating a statement by partitioning the text data;
- generating an actor list using at least the statement;
- determining an act using the statement, wherein determining the act comprises extracting feature data and semantic vector data from the statement, and processing the feature data and the semantic vector data using a trained machine learning model to determine the act;
- and
- determining first relational information between a first actor and a second actor in the actor list, wherein the determining comprises processing the statement using the trained machine learning model.
Dependencies are inferred from the claim text.