Generating context specific electronic communications utilizing a neural network
US-2024403597-A1 · Dec 5, 2024 · US
US2025286850A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2025286850-A1 |
| Application number | US-202519217583-A |
| Country | US |
| Kind code | A1 |
| Filing date | May 23, 2025 |
| Priority date | Jul 9, 2021 |
| Publication date | Sep 11, 2025 |
| Grant date | — |
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Systems, methods, and computer program products for adaptively splitting electronic chats are provided. One embodiment includes receiving an electronic chat comprising a set of electronic chat messages, each of the electronic chat messages in the set of electronic chat messages having a timestamp; determining a set of time gaps between the electronic chat messages from the set of electronic chat messages; determining a set of models that model the set of time gaps, selecting an optimum model from the set of models; based on selecting the single Gaussian distribution as the optimum model, determining that the electronic chat comprises a single electronic chat, and storing the set of electronic chat messages as the single electronic chat.
Opening claim text (preview).
What is claimed is: 1 . An electronic discovery system, comprising: a computer processor; and a non-transitory computer-readable medium storing instructions that, when executed by the computer processor, cause the system to perform operations comprising: receiving a set of electronic chat messages, each electronic chat message in the set of electronic chat messages having a timestamp; determining a set of time gaps, each time gap in the set of time gaps representing a time difference between temporally adjacent electronic chat messages in the set of electronic chat messages; generating a plurality of models based on the set of time gaps, each model being configured to provide a distinct representation of characteristics of the set of time gaps; selecting one of the models based on selection criteria, the selected one of the models being a splitting model; splitting the set of electronic chat messages into a plurality of electronic chat conversations in accordance with the splitting model; and storing the plurality of electronic chat conversations. 2 . The electronic discovery system of claim 1 , wherein the plurality of models comprises one or more distribution models representing a single Gaussian distribution of the set of time gaps and one or more Gaussian mixture models representing a mixture of Gaussian distributions of the set of time gaps. 3 . The electronic discovery system of claim 1 , wherein one or more selection criteria comprise a Bayesian Information Criterion (BIC). 4 . The electronic discovery system of claim 1 , wherein each electronic chat conversation in the plurality of electronic chat conversations is distinct. 5 . The electronic discovery system of claim 1 , further comprising indexing each electronic chat conversation so that content from each electronic chat conversation is electronically searchable. 6 . The electronic discovery system of claim 1 , wherein receiving the set of electronic chat messages is based on the set of electronic chat messages meeting a predefined chat query criterion. 7 . The electronic discovery system of claim 1 , wherein each electronic chat conversation in the plurality of electronic chat conversations comprises at least a predefined minimum number of electronic chat messages. 8 . A non-transitory computer-readable medium storing instructions that, when executed by a computer processor of an electronic discovery system, cause the electronic discovery system to perform operations comprising: receiving a set of electronic chat messages, each electronic chat message in the set of electronic chat messages having a timestamp; determining a set of time gaps, each time gap in the set of time gaps representing a time difference between temporally adjacent electronic chat messages in the set of electronic chat messages; generating a plurality of models based on the set of time gaps, each model being configured to provide a distinct representation of characteristics of the set of time gaps; selecting one of the models based on selection criteria, the selected one of the models being a splitting model; splitting the set of electronic chat messages into a plurality of electronic chat conversations in accordance with the splitting model; and storing the plurality of electronic chat conversations. 9 . The non-transitory computer-readable medium of claim 8 , wherein the plurality of models comprises one or more distribution models representing a single Gaussian distribution of the set of time gaps and one or more Gaussian mixture models representing a mixture of Gaussian distributions of the set of time gaps. 10 . The non-transitory computer-readable medium of claim 8 , wherein one or more selection criteria comprise a Bayesian Information Criterion (BIC). 11 . The non-transitory computer-readable medium of claim 8 , wherein each electronic chat conversation in the plurality of electronic chat conversations is distinct. 12 . The non-transitory computer-readable medium of claim 8 , wherein the instructions further cause the electronic discovery system to index each electronic chat conversation so that content from each electronic chat conversation is electronically searchable. 13 . The non-transitory computer-readable medium of claim 8 , wherein receiving of the set of electronic chat messages is based on the set of electronic chat messages meeting a predefined chat query criterion. 14 . The non-transitory computer-readable medium of claim 8 , wherein each electronic chat conversation in the plurality of electronic chat conversations comprises at least a predefined minimum number of electronic chat messages. 15 . A method of processing electronic chat data in an electronic discovery system, the method comprising: receiving, by a computer processor of the electronic discovery system, a set of electronic chat messages, each electronic chat message in the set of electronic chat messages having a timestamp; determining, by the computer processor, a set of time gaps, each time gap in the set of time gaps representing a time difference between temporally adjacent electronic chat messages in the set of electronic chat messages; generating, by the computer processor, a plurality of models based on the set of time gaps, each model being configured to provide a distinct representation of characteristics of the set of time gaps; selecting one of the models based on selection criteria, the selected one of the models being a splitting model; splitting, by the computer processor, the set of electronic chat messages into a plurality of electronic chat conversations in accordance with the splitting model; and storing the plurality of electronic chat conversations. 16 . The method of claim 15 , wherein the plurality of models comprises one or more distribution models representing a single Gaussian distribution of the set of time gaps and one or more Gaussian mixture models representing a mixture of Gaussian distributions of the set of time gaps. 17 . The method of claim 15 , wherein one or more selection criteria comprise a Bayesian Information Criterion (BIC). 18 . The method of claim 15 , wherein each electronic chat conversation in the plurality of electronic chat conversations is distinct. 19 . The method of claim 15 , further comprising indexing, by the computer processor, each electronic chat conversation so that content from each electronic chat conversation is electronically searchable. 20 . The method of claim 15 , wherein receiving of the set of electronic chat messages is based on the set of electronic chat messages meeting a predefined chat query criterion.
characterised by the inclusion of specific contents · CPC title
User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail · CPC title
Monitoring or handling of messages · CPC title
Timestamp · CPC title
Real-time or near real-time messaging, e.g. instant messaging [IM] · CPC title
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