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US 11,057,330 B2Granted
Determination of conversation threads in a message channel based on conversational flow and semantic similarity of messages
AssigneeInternational Business Machines Corporation
InventorsMing Tan, Haoyu Wang, Dakuo Wang, Chuang Gan
Life of this patent
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Abstract
A deep learning module classifies messages received from a plurality of entities into one or more conversation threads. In response to receiving a subsequent message, the deep learning module determines which of the one or more conversation threads and a new conversation thread is contextually a best fit for the subsequent message. The subsequent message is added to the determined conversation thread.
Claims18
A method, comprising:
- classifying, by a deep learning module implemented in a computational device, messages received from a plurality of entities into one or more conversation threads;
- for each conversation thread, determining via a flow model, a flow fit measure of a subsequent message, wherein the flow fit measure represents a fluency of conversation in the conversation thread if the subsequent message is added to the conversation thread;
- for each conversation thread, determining via a semantic match model, a semantic match measure of the subsequent message, wherein the semantic match measure represents a semantic closeness of conversation in the conversation thread if the subsequent message is added to the conversation thread;
- subsequent to determining the flow fit measure and the semantic match measure of the subsequent message, determining a flow fit and semantic match combination measure for each conversation thread from the flow fit measure and the semantic match measure of the conversation threads;
- and
- classifying the subsequent message into a conversation thread that has a best flow fit and semantic match combination measure in comparison to other conversation threads.
3 more elements
A system, comprising:
- a memory;
- and
- a processor coupled to the memory, wherein the processor performs operations, the operations comprising:
- classifying, by a deep learning module, messages received from a plurality of entities into one or more conversation threads;
- for each conversation thread, determining via a flow model, a flow fit measure of a subsequent message, wherein the flow fit measure represents a fluency of conversation in the conversation thread if the subsequent message is added to the conversation thread;
- for each conversation thread, determining via a semantic match model, a semantic match measure of the subsequent message, wherein the semantic match measure represents a semantic closeness of conversation in the conversation thread if the subsequent message is added to the conversation thread;
- subsequent to determining the flow fit measure and the semantic match measure of the subsequent message, determining a flow fit and semantic match combination measure for each conversation thread from the flow fit measure and the semantic match measure of the conversation threads;
- and
- classifying the subsequent message into a conversation thread that has a best flow fit and semantic match combination measure in comparison to other conversation threads.
6 more elements
A computer program product, the computer program product comprising a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code configured to perform operations on a processor, the operations comprising:
- classifying, by a deep learning module, messages received from a plurality of entities into one or more conversation threads;
- for each conversation thread, determining via a flow model, a flow fit measure of a subsequent message, wherein the flow fit measure represents a fluency of conversation in the conversation thread if the subsequent message is added to the conversation thread;
- for each conversation thread, determining via a semantic match model, a semantic match measure of the subsequent message, wherein the semantic match measure represents a semantic closeness of conversation in the conversation thread if the subsequent message is added to the conversation thread;
- subsequent to determining the flow fit measure and the semantic match measure of the subsequent message, determining a flow fit and semantic match combination measure for each conversation thread from the flow fit measure and the semantic match measure of the conversation threads;
- and
- classifying the subsequent message into a conversation thread that has a best flow fit and semantic match combination measure in comparison to other conversation threads.
3 more elements
Dependencies are inferred from the claim text.