Communication method and apparatus
US-2024422514-A1 · Dec 19, 2024 · US
US2016337208A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016337208-A1 |
| Application number | US-201415107572-A |
| Country | US |
| Kind code | A1 |
| Filing date | Jun 16, 2014 |
| Priority date | Dec 25, 2013 |
| Publication date | Nov 17, 2016 |
| Grant date | — |
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A method and system for evaluating user perception are provided. The method includes that: a perception evaluation result of each service among multiple services used by a user is acquired; a corresponding service weight value is allocated to each service according to service parameter information of each service used by the user, wherein the service weight value refers to a ratio of each service to the multiple services; and an overall perception evaluation result of the multiple services used by the user is generated according to all perception evaluation results and corresponding service weight values. By means of the method and system, the effects of making perception evaluation more scientific and improving the accuracy of perception evaluation are achieved.
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1 . A method for evaluating user perception, comprising: acquiring a perception evaluation result of each service among multiple services used by a user; allocating a corresponding service weight value to each service according to service parameter information of each service used by the user, wherein the service weight value refers to a ratio of each service to the multiple services; and generating an overall perception evaluation result of the multiple services used by the user according to all perception evaluation results and corresponding service weight values. 2 . The method as claimed in claim 1 , wherein acquiring the perception evaluation result of each service among the multiple services used by the user comprises: executing a perception evaluation grading operation on each service by using a pre-determined algorithm according to a service evaluation index corresponding to each service to obtain the perception evaluation result. 3 . The method as claimed in claim 2 , wherein before the perception evaluation result of each service among the multiple services used by the user is acquired, the method comprises: setting the service evaluation index corresponding to each service according to a service type of each service. 4 . The method as claimed in claim 3 , wherein before the service evaluation index corresponding to each service is set according to the service type of each service, the method comprises: acquiring service data generated in an internet-surfing process of the user; and identifying each service used by the user and the service type corresponding to each service from the service data. 5 . The method as claimed in claim 3 , wherein the service type comprises: a webpage browsing service, an instant messaging service, a blog service, a Weibo service, a search service, a game service or a video watching service. 6 . The method as claimed in claim 5 , wherein when the service type is the webpage browsing service, the service evaluation index comprises at least one of: a home page request success rate, a home page request average total delay, a session-level webpage complete opening rate, a session-level webpage complete opening delay and a session-level webpage complete response average delay; when the service type is the instant messaging service, the service evaluation index comprises at least one of: a login success rate, an uplink message success rate, an uplink message average delay, a downlink message success rate and a downlink message average delay; and when the service type is the Weibo service, the service evaluation index comprises at least one of: a refreshing response average delay, a refreshing operation success rate, a refreshing speed, an issuing response average delay, an issuing operation success rate and an issuing speed. 7 . The method as claimed in claim 1 , wherein the service parameter information comprises at least one of: a service using time length, a service using frequency and a service traffic magnitude. 8 . A system for evaluating user perception, comprising: a first acquisition component, configured to acquire a perception evaluation result of each service among multiple services used by a user; an allocation component, configured to allocate a service weight value corresponding to each service according to service parameter information of each service used by the user, wherein the service weight value refers to a ratio of each service to the multiple services; and a generation component, configured to generate an overall perception evaluation result of the multiple services used by the user according to all perception evaluation results and corresponding service weight values. 9 . The system as claimed in claim 8 , further comprising: a setting component, configured to set a service evaluation index corresponding to each service according to a service type of each service; and a grading component, configured to execute a perception evaluation grading operation on each service by using a pre-determined algorithm according to the service evaluation index corresponding to each service to obtain the perception evaluation result. 10 . The system as claimed in claim 9 , further comprising: a second acquisition component, configured to acquire service data generated in an internet-surfing process of the user; and an identification component, configured to identify each service used by the user and the service type corresponding to each service from the service data. 11 . The method as claimed in claim 4 , wherein the service type comprises: a webpage browsing service, an instant messaging service, a blog service, a Weibo service, a search service, a game service or a video watching service. 12 . The method as claimed in claim 11 , wherein when the service type is the webpage browsing service, the service evaluation index comprises at least one of: a home page request success rate, a home page request average total delay, a session-level webpage complete opening rate, a session-level webpage complete opening delay and a session-level webpage complete response average delay; when the service type is the instant messaging service, the service evaluation index comprises at least one of: a login success rate, an uplink message success rate, an uplink message average delay, a downlink message success rate and a downlink message average delay; and when the service type is the Weibo service, the service evaluation index comprises at least one of: a refreshing response average delay, a refreshing operation success rate, a refreshing speed, an issuing response average delay, an issuing operation success rate and an issuing speed. 13 . The method as claimed in claim 2 , wherein the service parameter information comprises at least one of: a service using time length, a service using frequency and a service traffic magnitude. 14 . The method as claimed in claim 3 , wherein the service parameter information comprises at least one of: a service using time length, a service using frequency and a service traffic magnitude. 15 . The method as claimed in claim 4 , wherein the service parameter information comprises at least one of: a service using time length, a service using frequency and a service traffic magnitude.
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