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US-9460095-B2 · Oct 4, 2016 · US
US2016335572A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016335572-A1 |
| Application number | US-201514714109-A |
| Country | US |
| Kind code | A1 |
| Filing date | May 15, 2015 |
| Priority date | May 15, 2015 |
| Publication date | Nov 17, 2016 |
| Grant date | — |
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A system that analyses content of electronic communications may automatically detect requests or commitments from the electronic communications. In one example process, a processor may identify a request or a commitment in the content of the electronic message; based, at least in part, on the request or the commitment, determine an informal contract; and execute one or more actions to manage the informal contract, the one or more actions based, at least in part, on the request or the commitment.
Opening claim text (preview).
What is claimed is: 1 . A system comprising: a receiver port to receive content of an electronic message; and a processor to: identify a request or a commitment in the content of the electronic message; based, at least in part, on the request or the commitment, determine an informal contract; and execute one or more actions to manage the informal contract, the one or more actions based, at least in part, on the request or the commitment. 2 . The system of claim 1 , wherein the processor is configured to: based, at least in part, on the request or the commitment, query one or more data sources; and in response to the query of the one or more data sources, receive information from the one or more data sources, wherein the one or more actions to manage the request or the commitment is further based, at least in part, on the information received from the one or more data sources. 3 . The system of claim 2 , wherein the information of the one or more data sources comprises personal data of one or more authors of the content of the electronic message. 4 . The system of claim 2 , wherein the one or more actions comprise determining likelihood that the commitment will be fulfilled by a particular person, wherein the determining is based, at least in part, on the information received from the one or more data sources. 5 . The system of claim 2 , wherein a subject of the request or the commitment is associated with a meeting; and the one or more actions comprise: automatically identifying or modifying an attendee list or location for the meeting based, at least in part, on the information received from the one or more data sources. 6 . The system of claim 5 , wherein the one or more data sources include at least one of location or mapping services, personal data of one or more authors of the content of the electronic message, calendar services, or meeting room schedule services. 7 . The system of claim 1 , wherein the one or more actions comprise: modifying an electronic calendar of one or more authors of the content of the electronic message, wherein the modifying is based, at least in part, on relative relationships between or among the one or more authors. 8 . The system of claim 2 , wherein the processor is configured to select the one or more data sources by applying statistical models to the content of the electronic message. 9 . The system of claim 2 , further comprising: a machine learning module configured to use the content of the electronic message and/or the information from the one or more data sources as training data. 10 . A method comprising: identifying a request or a commitment in an electronic message; determining an informal contract based, at least in part, on the request or the commitment; and determining a task-oriented process based, at least in part, on the informal contract. 11 . The method of claim 10 , further comprising: searching one or more sources of data for information related to the request or the commitment in the electronic message; and receiving the information related to the request or the commitment in the electronic message from the one or more sources of data, wherein determining the task-oriented process is further based, at least in part, on the information received from the one or more data sources. 12 . The method of claim 10 , further comprising: determining the task-oriented process while at least a portion of the electronic message is being generated. 13 . The method of claim 11 , wherein the information related to the electronic message comprises one or more aspects of an author of the electronic message. 14 . The method of claim 10 , further comprising: tracking one or more activities associated with the request or the commitment; and modifying the task-oriented process in response to the one or more activities. 15 . The method of claim 10 , further comprising: grouping the request or the commitment with additional requests or commitments to form a project. 16 . The method of claim 11 , wherein the one or more sources of data comprise an electronic calendar for an author of the electronic message, and further comprising: while the author is generating at least a portion of the electronic message that includes a commitment, notifying the author about time constraints likely to affect the commitment. 17 . A computing device comprising: a transceiver port to receive and to transmit data; and a processor to: detect a request or a commitment included in an electronic message; transmit, via the transceiver port, a query to retrieve information from one or more entities, wherein the query is based, at least in part, on the request or the commitment; manage one or more tasks associated with the request or the commitment, wherein the one or more tasks are based, at least in part, on the retrieved information. 18 . The computing device of claim 17 , wherein the retrieved information comprises a weather forecast, and wherein the one or more tasks include modifying a schedule associated with the request or the commitment based, at least in part, on the weather forecast. 19 . The computing device of claim 17 , wherein the processor is configured to: provide the electronic message or the retrieved information as training data for a machine learning process; and apply the machine learning process to managing the one or more tasks. 20 . The computing device of claim 17 , wherein the one or more tasks comprise iteratively modifying a schedule for one or more authors of the electronic message over a period of time.
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