Adaptive contact window

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.

What is claimed is: 
     
         1 - 10 . (canceled) 
     
     
         11 . 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:
 generating one or more analytical models based on respective response rates of one or more answering users responding to requests, 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; 
 identifying, for each answering user, a class associated with the answering user, each answering user of the one or more answering users associated with a common schedule characteristic; 
 determining a time corresponding to the request, the time indicating a time of day at which the request was issued; 
 identifying a subset of the one or more analytical models based on the i) the class associated with each answering user and ii) the time corresponding to the request; 
 processing at least one analytical model of the subset of 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. 
   
     
     
         12 . The system of  claim 11 , wherein the operations further comprise:
 determining a response of a particular answering user of the subset of the one or more answering users to the request;   modifying an analytical model of the one or more analytical models based on the response to provide a modified analytical model, the modified analytical model being specific to the particular answering user; and   in response to receiving a subsequent request, determining whether to transmit the subsequent request to the particular answering user based on the modified analytical model.   
     
     
         13 . The system of  claim 11 , wherein the analytical model comprises count data, the count data comprising a number of successful requests and a number of unsuccessful requests corresponding to each time period of a plurality of time periods associated with each analytical model. 
     
     
         14 . The system of  claim 11 , wherein processing the analytical model comprises:
 identifying a particular time period based on the time corresponding to the request;   determining a number of successful requests and a number of unsuccessful requests for the particular time period;   calculating the probability based on the number of successful requests and the number of unsuccessful requests; and   including the answering user in the subset of the one or more answering users based on the probability.   
     
     
         15 . The system of  claim 14 , wherein including the answering user in the subset of the one or more answering users based on the probability comprises:
 comparing the probability to a threshold probability; and   determining that the probability is greater than or equal to the threshold probability.   
     
     
         16 . The system of  claim 14 , wherein including the answering user in the subset of the one or more answering users based on the probability comprises:
 generating a random number; and   determining that the random number is less than or equal to the probability.   
     
     
         17 . The system of  claim 16 , wherein including the answering user in the subset of the one or more answering users based on the probability further comprises:
 comparing the probability to a threshold probability; and   determining that the probability is less than the threshold probability, wherein generating the random number occurs in response to determining that the probability is less than the threshold probability.   
     
     
         18 . (canceled) 
     
     
         19 . 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:
 generating one or more analytical models based on respective response rates of one or more answering users responding to requests, 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;   identifying, for each answering user, a class associated with the answering user, each answering user of the one or more answering users associated with a common schedule characteristic;   determining a time corresponding to the request, the time indicating a time of day at which the request was issued;   identifying a subset of the one or more analytical models based on the i) the class associated with each answering user and ii) the time corresponding to the request;   processing at least one analytical model of the subset of 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.   
     
     
         20 . A computer-implemented method comprising:
 generating one or more analytical models based on respective response rates of one or more answering users responding to requests, 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;   identifying, for each answering user, a class associated with the answering user, each answering user of the one or more answering users associated with a common schedule characteristic;   determining a time corresponding to the request, the time indicating a time of day at which the request was issued;   identifying a subset of the one or more analytical models based on the i) the class associated with each answering user and ii) the time corresponding to the request;   processing at least one analytical model of the subset of 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.   
     
     
         21 . The computer storage medium of  claim 19 , the operations further comprising:
 determining a response of a particular answering user of the subset of the one or more answering users to the request;   modifying an analytical model of the one or more analytical models based on the response to provide a modified analytical model, the modified analytical model being specific to the particular answering user; and   in response to receiving a subsequent request, determining whether to transmit the subsequent request to the particular answering user based on the modified analytical model.   
     
     
         22 . The computer storage medium of  claim 19 , wherein the analytical model comprises count data, the count data comprising a number of successful requests and a number of unsuccessful requests corresponding to each time period of a plurality of time periods associated with each analytical model. 
     
     
         23 . The computer storage medium of  claim 19 , wherein processing the analytical model comprises:
 identifying a particular time period based on the time corresponding to the request;   determining a number of successful requests and a number of unsuccessful requests for the particular time period;   calculating the probability based on the number of successful requests and the number of unsuccessful requests; and   including the answering user in the subset of the one or more answering users based on the probability.   
     
     
         24 . The computer storage medium of  claim 23 , wherein including the answering user in the subset of the one or more answering users based on the probability comprises:
 comparing the probability to a threshold probability; and   determining that the probability is greater than or equal to the threshold probability.   
     
     
         25 . (canceled) 
     
     
         26 . The computer-implemented method of  claim 20 , further comprising:
 determining a response of a particular answering user of the subset of the one or more answering users to the request;   modifying an analytical model of the one or more analytical models based on the response to provide a modified analytical model, the modified analytical model being specific to the particular answering user; and   in response to receiving a subsequent request, determining whether to transmit the subsequent request to the particular answering user based on the modified analytical model.   
     
     
         27 . The computer-implemented method of  claim 20 , wherein the analytical model comprises count data, the count data comprising a number of successful requests and a number of unsuccessful requests corresponding to each time period of a plurality of time periods associated with each analytical model. 
     
     
         28 . The computer-implemented method of  claim 20 , wherein processing the analytical model comprises:
 identifying a particular time period based on the time corresponding to the request;   determining a number of successful requests and a number of unsuccessful requests for the particular time period;   calculating the probability based on the number of successful requests and the number of unsuccessful requests; and   including the answering user in the subset of the one or more answering users based on the probability.   
     
     
         29 . The computer-implemented method of  claim 28 , wherein including the answering user in the subset of the one or more answering users based on the probability comprises:
 comparing the probability to a threshold probability; and   determining that the probability is greater than or equal to the threshold probability.   
     
     
         30 . (canceled)