WO2015081801A1 - Method, server, and system for information push - Google Patents

Method, server, and system for information push Download PDF

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Publication number
WO2015081801A1
WO2015081801A1 PCT/CN2014/092241 CN2014092241W WO2015081801A1 WO 2015081801 A1 WO2015081801 A1 WO 2015081801A1 CN 2014092241 W CN2014092241 W CN 2014092241W WO 2015081801 A1 WO2015081801 A1 WO 2015081801A1
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WIPO (PCT)
Prior art keywords
click
clicks
location
information push
user
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PCT/CN2014/092241
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English (en)
French (fr)
Inventor
Bing Cai
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Tencent Technology (Shenzhen) Company Limited
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Publication of WO2015081801A1 publication Critical patent/WO2015081801A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation

Definitions

  • the present disclosure generally relates to internet technology, particularly to a method, a server, and a system for information push.
  • the explosive growth of Internet information makes the problem of information overload more and more serious. It is very difficult for users to find out the content what they are interested in from vast amounts of information source such as news sites, BBS, blog and so on. Hence, a personalized recommendation system is produced. Usually, the personalized recommendation system calculates the content what users might be interested in according to the user's browsing history, and then shows the content to users preferentially.
  • the personalized recommendation system is faced with a very important problem of how to determine the amount of issued recommended results for every user request. If the amount is insufficient, every demand for browsing of user will not be completely satisfied, thus user needs to request again; if the amount is too much, the user will not consume completely one time, which will lead to an unnecessary waste of traffic.
  • the existing strategy for issuing recommended results adopts a fixed artificial experience value combining with business. Its defect is: not considering that the usage of product might be different in different times, which makes the issue recommendation not to be an optimal issue scheme. Therefore, the existing strategy for issuing recommended results cannot achieve a flexible control.
  • the present disclosure provides a method, a server and a system for information push, to improve the flexibility of strategy for issuing information push results, which both meets the demand of most users browsing at a different time, and avoids a waste of traffic caused by redundant issue.
  • the present disclosure provides a method for information push, comprising the steps of: obtaining the click information on an information push list by client to form an user click log; analyzing the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result; selecting the corresponding recommended items from said information push list according to said analysis result to issue.
  • the present disclosure also provides a server for information push, comprising: an obtaining module, programmed to obtain the click information on an information push list by client to form an user click log; an analyzing module, programmed to analyze the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result; an issuing module, programmed to select the corresponding recommended items from said information push list according to said analysis result to issue.
  • the present disclosure also provides a system for information push, comprising a client and a server which is connected to said client for communication; wherein, said server is a server as mentioned above; said client is programmed to respond to a click operation on the information push list by user and reporting click information to the server, as well as receiving issued recommended items from the server.
  • Present disclosure refers to a method, a server and a system for information push, wherein the method comprises the steps of: obtaining the click information on an information push list by client to form an user click log; analyzing the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result; selecting the corresponding recommended items from said information push list according to said analysis result to issue.
  • Present disclosure forms a user click log through obtaining the click information on an information push list by client, and analyzes the distribution of user’s click behavior based on said user click log—specifically, can analyze the distribution of click location, even combine the distribution in different times, so as to issue different items in different times. Thereby implements a flexible control of strategy for issuing information push results, which makes the push items both meet the demand of most users browsing at a different time, and avoid a waste of traffic caused by redundant issue.
  • FIG. 1 is a flowchart of a method for information push according to embodiments of the present disclosure.
  • FIG. 2a is a flowchart of one implement way of analyzing the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result according to embodiments of the present disclosure.
  • FIG. 2b is a flowchart of one implement way of selecting the corresponding recommended items from said information push list according to said analysis result to issue according to embodiments of the present disclosure.
  • FIG. 3 is a statistical map of a analysis strategy based on the distribution of click location by user
  • FIG. 4a is a flowchart of another implement way of analyzing the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result according to embodiments of the present disclosure.
  • FIG. 4b is a flowchart of another implement way of selecting the corresponding recommended items from said information push list according to said analysis result to issue according to embodiments of the present disclosure.
  • FIG. 5 is a statistical map of a analysis strategy based on the distribution of click location by user in different times
  • FIG. 6 shows the function structure of a server for information push according to embodiments of the present disclosure.
  • FIG. 7 shows the structure of the analyzing module according to embodiments of the present disclosure.
  • FIG. 8 shows the structure of a system for information push according to embodiments of the present disclosure.
  • FIG. 9 is a block diagram of a partial device according to embodiments of the present disclosure.
  • module may refer to, be part of, or include an Application Specific Integrated Circuit (ASIC) ; an electronic circuit; a combinational logic circuit; a field programmable gate array (FPGA) ; a processor (shared, dedicated, or group) that executes code; other suitable hardware components that provide the described functionality; or a combination of some or all of the above, such as in a system-on-chip.
  • ASIC Application Specific Integrated Circuit
  • FPGA field programmable gate array
  • processor shared, dedicated, or group
  • the term module or unit may include memory (shared, dedicated, or group) that stores code executed by the processor.
  • the exemplary environment may include a server, a client, and a communication network.
  • the server and the client may be coupled through the communication network for information exchange, such as sending/receiving identification information, sending/receiving data files such as splash screen images, etc.
  • information exchange such as sending/receiving identification information, sending/receiving data files such as splash screen images, etc.
  • client and one server are displayed in the environment, any number of terminals or servers may be included, and other devices may also be included.
  • the communication network may include any appropriate type of communication network for providing network connections to the server and client or among multiple servers or clients.
  • communication network may include the Internet or other types of computer networks or telecommunication networks, either wired or wireless.
  • the disclosed methods and apparatus may be implemented, for example, in a wireless network that includes at least one client.
  • the client may refer to any appropriate user terminal with certain computing capabilities, such as a personal computer (PC) , a work station computer, a server computer, a hand-held computing device (tablet) , a smart phone or mobile phone, or any other user-side computing device.
  • the client may include a network access device.
  • the client may be stationary or mobile.
  • a server may refer to one or more server computers configured to provide certain server functionalities, such as database management and search engines.
  • a server may also include one or more processors to execute computer programs in parallel.
  • a user may refer to one or more persons or things that control a client.
  • the user may control more than one clients or other devices.
  • the embodiments of the present disclosure provide a method for information push, comprising the steps of:
  • step 101 obtaining the click information on an information push list by client to form an user click log.
  • the information push list might be some recommended items including the content what user might be interested in, calculated by the backend server of personalized recommendation system according to the user's browsing history.
  • the recommended items included in the information push list could come from various news websites, BBS, blog, etc.
  • the information included in the information push list could also be the customized information such as microblog, data from public platform and so on.
  • this embodiment determine the optimal issue amount of push results through analyzing the information of user’s click on personalized push results, which satisfies the demands for every browsing of most users and avoids a waste of traffic. Thereby implements a flexible control of strategy for issuing information push results.
  • the user can click on the recommended items in web page what he want to browse from the personalized information push list according to his own demand. Then the client will respond to the click operation on the information push list, record the information of click by user, and report the information of click to a backend server.
  • the click information can include the time of click by user, the location of click in the information push list, user ID, etc.
  • the backend server forms a user click log after obtaining the click information on an information push list reported by client, so that analyzes the distribution of user’s click behavior based on said user click log.
  • Step 102 analyzing the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result.
  • user's click behavior can include the selection behavior of location where the user clicks on the information push list, the selection behavior of time when the user clicks on the information push list and so on.
  • the backend server analyzes the distribution of user’s click behavior based on said user click log, even combining the distribution in different times. Then calculates the percentages of clicks of the accumulation from the first item to current location in the total clicks of said information push list, thus obtains an analysis result. So that issues different items in different times depending on said analysis result. Thereby implements a flexible control of strategy for issuing information push results, which makes the push items both meet the demand of most users browsing at a different time, and avoid a waste of traffic caused by redundant issue.
  • Step 103 selecting the corresponding recommended items from said information push list according to said analysis result to issue.
  • the backend server selects and issues all the recommended items before the recommended item’s location which meets a preset condition in said information push list to the corresponding client, according to said analysis result.
  • Present embodiment forms a user click log through obtaining the click information on an information push list by client, and analyzes the distribution of user’s click behavior based on said user click log—specifically, can analyze the distribution of click location, even combine the distribution in different times, so as to issue different items in different times.
  • implements a flexible control of strategy for issuing information push results which makes the push items both meet the demand for browsing of most users at a different time, and avoid a waste of traffic caused by redundant issue.
  • said step 102: analyzing the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result can comprise the steps of:
  • step 1021 extracting the click location information on the information push list by client from said user click log;
  • step 1022 counting the clicks of each recommended item’s location according to the extracted click location information
  • step 1023 respectively calculating the percentages of clicks of the first 1 item, (1+n) , (1+2n) ... to all recommended items in the total clicks of said information push list, depending on the counted clicks of each recommended item’s location, wherein n is an integer which is greater than or equal to 1.
  • said step 103: selecting the corresponding recommended items from said information push list to issue can comprise the steps of:
  • step 1031 selecting a recommended item’s location which is corresponding to the percentage meeting preset condition from all the calculated percentages of clicks;
  • step 1032 issuing all the recommended items between the first and the selected recommended item’s location which is corresponding to the percentage meeting preset condition in said information push list to client.
  • present embodiment counts the clicks of each recommended item’s location according to the user click log, and respectively calculates the percentages of clicks of the first 1 item, (1+n) , (1+2n) ... to all recommended items in the total clicks of said information push list. For example, calculates the percentages of clicks of the first 10 items, 20 items, 30 items ... in the total clicks, in order to determine the finally issue amount.
  • the backend server records every click behavior of user and the location of present click in the information push list, which is similar to the search engines. For example, if the user clicks the first item, as a result, the record will be 1; if the user clicks the 10th item, as a result, the record will be 10. Then calculates the distribution of each recommended item’s location, and calculates the percentages of clicks of the accumulation from the first item to current location in the total clicks of said information push list.
  • the ideal amount is the first 60-70, items of the information push list, so that it can cover more than 90% of user clicks. If continue to increase the issue amount, the cost performance will be more and more low, which causes an unnecessary waste of traffic.
  • the embodiments form a user click log through obtaining the click information on an information push list by client, and analyze the distribution of user’s click behavior based on said user click log.
  • said step 102: analyzing the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result can comprise the steps of:
  • Step 10210 extracting click location information on the information push list by client from said user click log;
  • step 10220 respectively counting the clicks of each recommended item’s location in each set period according to the extracted click location information
  • step 10230 respectively calculating the percentages of clicks of the first 1 item, (1+n) , (1+2n) ... to all recommended items in the total clicks of said information push list in each period, depending on the counted clicks of each recommended item’s location in each set period, wherein n is an integer which is greater than or equal to 1.
  • said step 103: selecting the corresponding recommended items from said information push list to issue comprises the steps of:
  • step 10310 selecting a recommended item’s location which is corresponding to the percentage meeting preset condition in corresponding period from all the calculated percentages of clicks;
  • step 10320 issuing all the recommended items between the first and the selected recommended item’s location which is corresponding to the percentage meeting preset condition from said information push list in corresponding period to client.
  • present embodiment increases a time analysis dimension in the issue strategy of push results.
  • Present embodiment determines the optimal amount of push results through analysis of the click information on the personalized push results in different times.
  • the embodiment introduces a time context scenario, considering that the mood of user may be different in different periods or scenario, which may influence the click distribution.
  • each set period can be set according to the actual situation. For example, one day can be divided into two periods—after 12 o'clock and before 12 o'clock, or more periods.
  • n is an integer which is greater than or equal to 1. For example, respectively calculating the percentages of clicks of the first 10 item, 20, ... 60 items in the total clicks of said information push list in each period.
  • the embodiment implements a flexible control of strategy for issuing information push results, which makes the push items both meet the demand for browsing of most users at a different time, and avoid a waste of traffic caused by redundant issue.
  • the click distribution of the period after 12 o'clock is more decentralized compared to the click distribution of the period before 12 o'clock, so the issue amount of that can be more.
  • the reason is that the users’ desire to explore is stronger and they have more time in the afternoon or evening rest time. To be more flexible, the time can be divided into more periods.
  • This scheme of present embodiment provides a flexible strategy for issuing push result, combining the click feedback of user and the time context.
  • Present embodiment meets the demand for browsing of most users and avoids the issue of invalid results, which takes control of data traffic to some extent.
  • embodiments of the present disclosure provides a server for information push, comprising an obtaining module 201, an analyzing module 202 and an issuing module 203.
  • the obtaining module 201 is programmed to obtain the click information on an information push list by client to form a user click log.
  • the analyzing module 202 is programmed to analyze the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result.
  • the issuing module 203 is programmed to select the corresponding recommended items from said information push list according to said analysis result to issue.
  • the information push list might be some calculated recommended items including the content what user might be interested in by the backend server of personalized recommendation system according to the user's browsing history.
  • the recommended items included in the information push list could come from various news websites, BBS, blog, etc.
  • the information included in the information push list could also be the customized information such as microblog, data from public platform and so on.
  • this embodiment determine the optimal issue amount of push results through analyzing the information of user’s click on personalized push results, which satisfies the demands for every browsing of most users and avoids a waste of traffic. Thereby implements a flexible control of strategy for issuing information push results.
  • the user can click on the recommended items of web page what he want to browse from the personalized information push list according to his own demand. Then the client will respond to the click operation on the information push list, record the information of click by user, and report the information of click to a backend server.
  • the information of click can include the time of click by user, the location of click in the information push list, user ID, etc.
  • the obtaining module 201 of backend server obtains the click information on an information push list reported by client and forms a user click log, so that analyzes the distribution of user’s click behavior based on said user click log.
  • user's click behavior can include the selection behavior of location where the user clicks on the information push list, and the selection behavior of time when the user clicks on the information push list and so on.
  • the analyzing module 202 of backend server analyzes the distribution of user’s click behavior based on said user click log, even combining the distribution in different times. Then calculates the percentages of clicks of the accumulation from the first item to current location in the total clicks of said information push list, thus obtains an analysis result. So that the issuing module 203 issues different items in different times depending on said analysis result. Thereby implements a flexible control of strategy for issuing information push results, which makes the push items both meet the demand of most users browsing at a different time, and avoid a waste of traffic caused by redundant issue.
  • the backend server selects and issues all the recommended items before the recommended item’s location which meets a preset condition in said information push list to the corresponding client, according to said analysis result.
  • the present embodiment forms a user click log through obtaining the click information on an information push list by client, and analyzes the distribution of user’s click behavior based on said user click log, specifically analyze the distribution of click location, and combine the distribution in different times, so as to issue different items in different times.
  • said analyzing module 202 comprises an extracting unit of information 2021, a counting unit 2022 and a calculating unit2023.
  • the extracting unit 2021 of information is programmed to extract the click location information on an information push list by client from said user click log.
  • the counting unit 2022 is programmed to count the clicks of each recommended item’s location according to the extracted click location information
  • the calculating unit 2023 is programmed to respectively calculate the percentages of clicks of the first 1 item, (1+n) , (1+2n) ... to all recommended items in the total clicks of said information push list, depending on the counted clicks of each recommended item’s location, wherein n is an integer which is greater than or equal to 1.
  • Said issuing module 203 is also programmed to select a recommended item’s location which is corresponding to the percentage meeting preset condition from all the calculated percentages of clicks, and issue all the recommended items between the first and the selected recommended item’s location which is corresponding to the percentage meeting preset condition in said information push list to client.
  • said counting unit 2022 is also programmed to respectively count the clicks of each recommended item’s location in each set period according to the extracted click location information.
  • Said calculating unit 2023 is also programmed to respectively calculate the percentages of clicks of the first 1 item, (1+n) , (1+2n) ... to all recommended items in the total clicks of said information push list in each period, depending on the counted clicks of each recommended item’s location in each set period, wherein n is an integer which is greater than or equal to 1.
  • Said issuing module 203 is also programmed to select a recommended item’s location which is corresponding to the percentage meeting preset condition in corresponding period from all the calculated percentages of clicks, and issuing all the recommended items between the first and the selected recommended item’s location which is corresponding to the percentage meeting preset condition from said information push list in corresponding period to client.
  • the backend server records every click behavior of user and the location of present click in the information push list, which is similar to the search engines. For example, if the user clicks the first item, as a result, the record will be 1; if the user clicks the 10th item, as a result, the record will be 10. Then calculates the distribution of each recommended item’s location, and calculates the percentages of clicks of the accumulation from the first item to current location in the total clicks of said information push list.
  • the ideal amount is the first 60-70, items of the information push list, so that it can cover more than 90% of user clicks. If continue to increase the issue amount, the cost performance will be more and more low, which causes an unnecessary waste of traffic.
  • present embodiment forms a user click log through obtaining the click information on an information push list by client, and analyzes the distribution of user’s click behavior based on said user click log.
  • present embodiment increases a time analysis dimension in the issue strategy of push results compared to the above embodiment.
  • Present embodiment determines the optimal amount of push results through analysis of the click information on the personalized push results in different times.
  • the embodiment introduces a time context scenario, considering that the mood of user may be different in different periods or scenario, which may influence the click distribution.
  • each set period can be set according to the actual situation. For example, one day can be divided into two periods—after 12 o'clock and before 12 o'clock, or more periods.
  • n is an integer which is greater than or equal to 1. For example, respectively calculating the percentages of clicks of the first 10 item, 20, ... 60 items in the total clicks of said information push list in each period.
  • the embodiment implements a flexible control of strategy for issuing information push results, which makes the push items both meet the demand for browsing of most users at a different time, and avoid a waste of traffic caused by redundant issue.
  • one day can be divided into two periods—after 12 o'clock and before 12 o'clock.
  • the embodiment respectively counts the cumulative click ratio of each location in two periods, to determine the corresponding issue amount.
  • the click distribution of the period after 12 o'clock is more decentralized compared to the click distribution of the period before 12 o'clock, so the issue amount of that can be more.
  • the reason is that the users’ desire to explore is stronger and they have more time in the afternoon or evening rest time. To be more flexible, the time can be divided into more periods.
  • This scheme of present embodiment provides a flexible strategy for issuing push result, combining the click feedback of user and the time context.
  • Present embodiment meets the demand for browsing of most users and avoids the issue of invalid results, which takes control of data traffic to some extent.
  • embodiments of the present disclosure provide a system for information push, comprising a client 301 and a server 302 which is connected to said client 301 for communication.
  • said server 302 can be any one of servers mentioned in the above embodiments.
  • the server 302 is programmed to obtain the click information on an information push list by client to form a user click log, analyzing the distribution of user’s click behavior based on said user click log, thus obtaining an analysis result, selecting the corresponding recommended items from said information push list according to said analysis result to issue.
  • Said client 301 is programmed to respond to a click operation on the information push list by user and reporting click information to the server, as well as receiving issued recommended items from the server 302.
  • the information push list might be some calculated recommended items including the content what user might be interested in by the backend server of personalized recommendation system according to the user's browsing history.
  • the recommended items included in the information push list could come from various news websites, BBS, blog, etc.
  • the information included in the information push list could also be the customized information such as microblog, data from public platform and so on.
  • this embodiment determine the optimal issue amount of push results through analyzing the information of user’s click on personalized push results, which satisfies the demands for every browsing of most users and avoids a waste of traffic. Thereby implements a flexible control of strategy for issuing information push results.
  • the user can click on the recommended items of web page what he want to browse from the personalized information push list according to his own demand. Then the client 301 will respond to the click operation on the information push list, record the information of click by user, and report the information of click to a backend server 302.
  • the information of click can include the time of click by user, the location of click in the information push list, user ID, etc.
  • the backend server 302 forms a user click log after obtaining the click information on an information push list reported by client 301, so that analyzes the distribution of user’s click behavior based on said user click log.
  • user's click behavior can include the selection behavior of location where the user clicks on the information push list, the selection behavior of time when the user clicks on the information push list and so on.
  • the backend server 302 analyzes the distribution of user’s click behavior based on said user click log, even combining the distribution in different times. Then calculates the percentages of clicks of the accumulation from the first item to current location in the total clicks of said information push list, thus obtains an analysis result. So that issues different items in different times depending on said analysis result. Thereby implements a flexible control of strategy for issuing information push results, which makes the push items both meet the demand of most users browsing at a different time, and avoid a waste of traffic caused by redundant issue.
  • the backend server 302 selects and issues all the recommended items before the recommended item’s location which meets a preset condition in said information push list to the corresponding client 301, according to said analysis result.
  • Present embodiment forms a user click log through obtaining the click information on an information push list by client 301, and analyzes the distribution of user’s click behavior based on said user click log—specifically, can analyze the distribution of click location, even combine the distribution in different times, so as to issue different items in different times.
  • implements a flexible control of strategy for issuing information push results which makes the push items both meet the demand for browsing of most users at a different time, and avoid a waste of traffic caused by redundant issue.
  • the backend server 302 records every click behavior of user and the location of present click in the information push list, which is similar to the search engines. For example, if the user clicks the first item, as a result, the record will be 1; if the user clicks the 10th item, as a result, the record will be 10. Then calculates the distribution of each recommended item’s location, and calculates the percentages of clicks of the accumulation from the first item to current location in the total clicks of said information push list.
  • the ideal amount is the first 60-70, items of the information push list, so that it can cover more than 90% of user clicks. If continue to increase the issue amount, the cost performance will be more and more low, which causes an unnecessary waste of traffic.
  • present embodiment forms a user click log through obtaining the click information on an information push list by client 301, and analyzes the distribution of user’s click behavior based on said user click log.
  • present embodiment increases a time analysis dimension in the issue strategy of push results compared to the above embodiment.
  • Present embodiment determines the optimal amount of push results through analysis of the click information on the personalized push results in different times.
  • the embodiment introduces a time context scenario, considering that the mood of user may be different in different periods or scenario, which may influence the click distribution.
  • each set period can be set according to the actual situation. For example, one day can be divided into two periods—after 12 o'clock and before 12 o'clock, or more periods.
  • n is an integer which is greater than or equal to 1. For example, respectively calculating the percentages of clicks of the first 10 item, 20, ... 60 items in the total clicks of said information push list in each period.
  • the embodiment implements a flexible control of strategy for issuing information push results, which makes the push items both meet the demand for browsing of most users at a different time, and avoid a waste of traffic caused by redundant issue.
  • one day can be divided into two periods—after 12 o'clock and before 12 o'clock.
  • Present embodiment respectively counts the cumulative click ratio of each location in two periods, to determine the corresponding issue amount.
  • the click distribution of the period after 12 o'clock is more decentralized compared to the click distribution of the period before 12 o'clock, so the issue amount of that can be more.
  • the reason is that the users’ desire to explore is stronger and they have more time in the afternoon or evening rest time. To be more flexible, the time can be divided into more periods.
  • This scheme of present embodiment provides a flexible strategy for issuing push result, combining the click feedback of user and the time context.
  • Present embodiment meets the demand for browsing of most users and avoids the issue of invalid results, which takes control of data traffic to some extent.
  • FIG. 9 is a block diagram of a server according to the above embodiments.
  • the server may communicate with a client device such as a mobile phone.
  • the server may include a radio frequency (RF) circuit 510, a memory 520, an input unit 530, a display unit 540, a sensor 550, an audio circuit 560, a wireless fidelity (WiFi) module 570, a processor 580, and a power 590, etc.
  • RF radio frequency
  • the structure of the server illustrated in FIG. 9 is not limited, some components can be added or omitted, or some combinations or arrangement can be included.
  • the RF circuit 510 is configured to receive and sending signals during calling or process of receiving and sending message. Specially, the RF circuit 510 will receive downlink information from the base station and send it to the processor 580; or send uplink data to the base station.
  • the RF circuit 510 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (LNA) , a diplexer, and the like.
  • the RF circuit 40 can communicate with network or other devices by wireless communication.
  • Such wireless communication can use any one communication standard or protocol, which includes, but is not limited to, Global System of Mobile communication (GSM) , (General Packet Radio Service, GPRS) , (Code Division Multiple Access, CDMA) , (Wideband Code Division Multiple Access, WCDMA) , (Long Term Evolution, LTE) , email, or (Short Messaging Service, SMS) .
  • GSM Global System of Mobile communication
  • GPRS General Packet Radio Service
  • CDMA Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • LTE Long Term Evolution
  • SMS Short Messaging Service
  • the memory 520 is configured to store software program and module which will be run by the processor 580, so as to perform multiple functional applications of the server and data processing.
  • the memory 530 mainly includes storing program area and storing data area.
  • the storing program area can store the operating system, at least one application program with required function (such as sound playing function, image playing function, etc. ) .
  • the storing data area can store data established by server according to actual using demand (such as audio data, phonebook, etc. )
  • the memory 520 can be high-speed random access memory, or nonvolatile memory, such as disk storage, flash memory device, or other volatile solid-state memory devices.
  • the input unit 530 is configured to receive the entered number or character information, and the entered key signal related to user setting and function control of the server 500.
  • the input unit 530 includes a touch panel 531 or other input devices 532.
  • the touch panel 531 is called as touch screen, which can collect user’s touch operations thereon or nearby (for example the operations generated by fingers of user or stylus pen, and the like, touching on the touch panel 531 or touching near the touch panel 531) , and drive the corresponding connection device according to the preset program.
  • the touch panel 531 includes two portions including a touch detection device and a touch controller.
  • the touch detection device is configured to detect touch position of the user and detecting signals accordingly, and then sending the signals to the touch controller.
  • the touch controller receives touch information from the touch detection device, and converts it to contact coordinates which are to be sent to the processor 580, and then receives command sent by the processor 580 to perform.
  • the touch panel 531 can be implemented is forms of resistive type, capacitive type, infrared type and surface acoustic wave type.
  • the input unit 530 can include, but is not limited to other input devices 532, such as one or more selected from physical keyboard, function keys (such as volume control keys, switch key-press, etc. ) , a trackball, a mouse, and an operating lever, etc.
  • the display unit 540 is configured to display information entered by the user or information supplied to the user, and menus of the server.
  • the display unit 540 includes a display panel 541, such as a Liquid Crystal Display (LCD) , or an Organic Light-Emitting Diode (OLED) .
  • the display panel 541 can be covered by the touch panel 531, after touch operations are detected on or near the touch panel 531, they will be sent to the processor 580 to determine the type of the touching event. Subsequently, the processor 580 supplies the corresponding visual output to the display panel 541 according to the type of the touching event.
  • the touch panel 531 and the display panel 541 are two individual components to implement input and output of the server, but they can be integrated together to implement the input and output in some embodiments.
  • the server 500 includes at least one sensor 550, such as light sensors, motion sensors, or other sensors.
  • the light sensors includes ambient light sensors for adjusting brightness of the display panel 541 according to the ambient light.
  • Accelerometer sensor as one of the motion sensors can detect the magnitude of accelerations in every direction (Triaxial, generally) , and detect the magnitude and direction of gravity in an immobile status, which is applicable to applications of identifying attitudes of the mobile (such as switching between horizontal and vertical screens, related games, magnetometer attitude calibration, etc. ) , vibration recognition related functions (such as pedometer, percussion, etc. ) .
  • the server 500 also can configure other sensors (such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc. ) whose detailed descriptions are omitted here.
  • the audio circuit 560, the speaker 561 and the microphone 562 supply an audio interface between the user and the server. Specifically, the audio data is received and converted to electrical signals by audio circuit 560, and then transmitted to the speaker 561, which are converted to sound signal to output. On the other hand, the sound signal collected by the speaker is then converted to electrical signals which will be received and converted to audio data. Subsequently, the audio data are output to the processor 580 to process, and then sent to client devices via the RF circuit 510, or sent to the memory 520 to process further.
  • WiFi pertains to short-range wireless transmission technology providing a wireless broadband Internet.
  • WiFi module 570 is illustrated in FIG. 9, it should be understood that, WiFi module 570 is not a necessary for the server, which can be omitted according the actual demand without changing the essence of the present disclosure.
  • the processor 580 is a control center of the server, which connects with every part of the server by various interfaces or circuits, and performs various functions and processes data by running or performing software program/module stored in the memory 520 or calling data stored in the memory 520, so as to monitor the server.
  • the processor 580 may include one or more processing units.
  • the processor 580 can integrate with application processors and modem processors, for example, the application processors include processing operating system, user interface and applications, etc.; the modern processors are used for performing wireless communication. It can be understood that, it’s an option to integrate the modern processors to the processor 580.
  • the server 500 may include a power supply (such as battery) supplying power for each component, preferably, the power supply can connect with the processor 580 by power management system, so as to manage charging, discharging and power consuming.
  • a power supply such as battery
  • the power supply can connect with the processor 580 by power management system, so as to manage charging, discharging and power consuming.
  • the server 500 may include a camera, and a Bluetooth module, etc., which are not illustrated.
  • Said software product is stored in a storage medium (such as ROM/RAM, disk, cd-rom) .
  • Said storage medium can be a terminal (such as mobile, computer, server, or network device) implementing the described method of present disclosure.

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  • Engineering & Computer Science (AREA)
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  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Information Transfer Between Computers (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
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CN106446189A (zh) * 2016-09-29 2017-02-22 广州艾媒数聚信息咨询股份有限公司 一种资讯推荐方法及系统
CN106936920A (zh) * 2017-03-31 2017-07-07 努比亚技术有限公司 一种应用消息的推送控制方法及装置
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CN116150482A (zh) * 2023-01-28 2023-05-23 北京黑马企服科技有限公司 一种基于大数据云平台的分布式消息推送系统
CN116150482B (zh) * 2023-01-28 2023-09-29 北京黑马企服科技有限公司 一种基于大数据云平台的分布式消息推送系统

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