US 8,712,944 B1Granted

Adaptive contact window wherein the probability that an answering user/expert will respond to a question corresponds to the answering users having response rates that are based on the time of day

AssigneeGoogle Inc.

InventorMichael Kim

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Abstract

Methods, systems and apparatus, including computer programs encoded on a computer storage medium, for receiving aggregate user data, the aggregate user data corresponding to response rate of one or more answering users responding to requests, processing the aggregate user data to generate one or more analytical models, each of the one or more analytical models providing a plurality probabilities that an average answering user will respond to a request, each probability of the plurality of probabilities corresponding to a particular time period during a day, receiving a request, determining a time corresponding to the request, identifying a plurality of answering users, processing the one or more analytical models based on the time to identify a sub-set of answering users of the plurality of answering users, and transmitting the request to each answering user of the sub-set of answering users.

Claims20

Dependent claims

A system comprising:

a computing device;
and
a computer-readable medium coupled to the computing device and having instructions stored thereon which, when executed by the computing device, cause the computing device to perform operations comprising:
receiving aggregate user data, the aggregate user data corresponding to respective response rates of one or more answering users responding to requests;
processing the aggregate user data to generate one or more analytical models, each answering user of the one or more answering users associated with one particular analytical model of the one or more analytical models, each of the one or more analytical models providing one or more probabilities that the answering user associated with the analytical model will respond to a request;
receiving the request;
determining a time corresponding to the request, the time indicating a time of day at which the request was issued;
processing the one or more analytical models, the processing including:
comparing, for each answering user, the time of day at which the request was issued with the analytical model associated with the answering user,
based on the comparing, identifying, for each answering user, a particular probability associated with the time of day at which the request was issued,
identifying a subset of the one or more answering users based on the particular probability that is associated with each answering user for the time of day at which the request was issued;
and
transmitting the request to each answering user of the sub-set of the one or more answering users.

10 more elements

A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

receiving aggregate user data, the aggregate user data corresponding to respective response rates of one or more answering users responding to requests;
processing the aggregate user data to generate one or more analytical models, each answering user of the one or more answering users associated with one particular analytical model of the one or more analytical models, each of the one or more analytical models providing one or more probabilities that the answering user associated with the analytical model will respond to a request;
receiving the request;
determining a time corresponding to the request, the time indicating a time of day at which the request was issued;
processing the one or more analytical models, the processing including:
comparing, for each answering user, the time of day at which the request was issued with the analytical model associated with the answering user,
based on the comparing, identifying, for each answering user, a particular probability associated with the time of day at which the request was issued,
identifying a subset of the one or more answering users based on the particular probability that is associated with each answering user for the time of day at which the request was issued;
and
transmitting the request to each answering user of the sub-set of the one or more answering users.

7 more elements

A computer-implemented method comprising:

receiving aggregate user data, the aggregate user data corresponding to respective response rates of one or more answering users responding to requests;
processing the aggregate user data to generate one or more analytical models, each answering user of the one or more answering users associated with one particular analytical model of the one or more analytical models, each of the one or more analytical models providing one or more probabilities that the answering user associated with the analytical model will respond to a request;
receiving the request;
determining a time corresponding to the request, the time indicating a time of day at which the request was issued;
processing the one or more analytical models, the processing including:
comparing, for each answering user, the time of day at which the request was issued with the analytical model associated with the answer user,
based on the comparing, identifying, for each answering user, a particular probability associated with the time of day at which the request was issued,
identifying a subset of the one or more answering users based on the particular probability that is associated with each answering user for the time of day at which the request was issued;
and
transmitting the request to each answering user of the sub-set of the one or more answering users.

7 more elements

Dependencies are inferred from the claim text.