WO2016101852A1 - 数据处理方法和系统 - Google Patents

数据处理方法和系统 Download PDF

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Publication number
WO2016101852A1
WO2016101852A1 PCT/CN2015/098045 CN2015098045W WO2016101852A1 WO 2016101852 A1 WO2016101852 A1 WO 2016101852A1 CN 2015098045 W CN2015098045 W CN 2015098045W WO 2016101852 A1 WO2016101852 A1 WO 2016101852A1
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WIPO (PCT)
Prior art keywords
user
snap
request
level
remaining amount
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PCT/CN2015/098045
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English (en)
French (fr)
Inventor
隋剑锋
高建峰
邹毅
邹开红
王凯
徐涛
Original Assignee
北京京东尚科信息技术有限公司
北京京东世纪贸易有限公司
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Publication of WO2016101852A1 publication Critical patent/WO2016101852A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55—Detecting local intrusion or implementing counter-measures
    • G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55—Detecting local intrusion or implementing counter-measures
    • G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
    • G06F21/566—Dynamic detection, i.e. detection performed at run-time, e.g. emulation, suspicious activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
    • G06Q30/0212—Chance discounts or incentives
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/03—Indexing scheme relating to G06F21/50, monitoring users, programs or devices to maintain the integrity of platforms
    • G06F2221/031—Protect user input by software means

Definitions

  • the present application relates to the field of network data processing technologies, and in particular, to a data processing method and system.
  • the e-commerce system is mainly used for information processing system for human-computer interaction with a user, accepting a user's instruction to generate a corresponding service request (for example, an order is a service request), and performing data processing on the corresponding commodity target information.
  • the verification is currently performed mainly by means of verification code, authorization authentication, and the like.
  • the existing verification code technical solution mainly includes: processing the snap request (buy The request is also a kind of service request in the e-commerce system.
  • the user inputs the verification code
  • the server verifies the verification code
  • the verification is correct
  • the subsequent process is continued, and if the verification fails, the input is re-entered. Verification code.
  • the existing authorization authentication technical solutions mainly include: generally, the user needs to apply for the preemption qualification before the snapping, after the start of the snapping activity, the user participates in the snapping, the server verifies whether the user has the qualification or judges according to the user level, and the verification succeeds to continue the later process. If the verification fails, it cannot participate in the purchase.
  • the existing methods of blocking malicious users generally only improve the difficulty of the system to imitate the software, such as increasing the difficulty of the verification code and adding more human-computer interaction processes.
  • malicious users often use semi-automated software to participate in the rush before the system is cracked.
  • the software is only responsible for regular access and submission functions. If manual input is required, the malicious user uses manual input. After the manual input is completed, the software automatically submits.
  • the speed of the software is very fast, and this malicious user has a significant speed advantage compared to normal users.
  • malicious users generally use a large number of registered users to snap up. A large proportion of malicious users plus speed advantage, resulting in a high probability of malicious snapping, the corresponding ordinary users are difficult to snap up successfully.
  • the main object of the present invention is to provide a data processing method and system that reduces the probability of successful malicious rush.
  • a data processing method comprising:
  • the filtering step receiving the user's snap request, obtaining the user's level information, determining the remaining amount of the snap target corresponding to the user level, and rejecting the snap request if the remaining amount is zero, the remaining amount is not In the case of zero, the user's snap request is filtered according to a predetermined screening probability, and the screening is performed by entering a subsequent random extraction step, otherwise entering a subsequent queuing step;
  • Queueing step receiving a query request of the user in the queue, judging whether the delay condition is satisfied, and determining whether the remaining amount of the snap target corresponding to the user level is zero if the delay condition is satisfied, and the remaining amount is not In the case of zero, the random extraction step is entered;
  • the random extraction step selecting the user's snap request according to the predetermined extraction probability, and confirming the successful purchase in the selected case.
  • the method further includes: determining that the step of the subsequent random extraction step has been entered. The number of users, if the number of users is less than the snapped target capacity corresponding to the user level, the user's snap request is filtered according to a predetermined screening probability; otherwise, the subsequent queuing step is entered.
  • the panning target expansion capacity corresponding to the user level is: a total amount of the snapping target corresponding to the user level multiplied by a capacity expansion coefficient corresponding to the user level; the random extraction probability is greater than or equal to the user level
  • the reciprocal of the corresponding expansion coefficient, the expansion coefficient corresponding to the user level is greater than or equal to 1.
  • the method further includes: determining whether the number of times the user queries the request exceeds a predetermined number of queries, and if yes, Confirm that the panning has failed, otherwise enter the random extraction step.
  • the determining the remaining amount of the snapping target corresponding to the user level comprises: pre-allocating the total amount of the snapping target according to the user level, and the number of the snapping target corresponding to each user level accounts for the total amount of the snapping target.
  • the ratio is specified; the number of snapped targets corresponding to the user level corresponding to the snap request is subtracted from the snapped number of the user level that has been snapped up, and the remaining amount of the snap target corresponding to the user level is obtained.
  • a data processing device comprising:
  • a filtering module configured to receive a snap request of the user, obtain level information of the user, determine a remaining amount of the snap target corresponding to the user level, and reject the snap request if the remaining amount is zero, in the remaining amount If the value is not zero, the user's snap request is filtered according to a predetermined screening probability, and the screening is performed by entering a subsequent random extraction module, otherwise entering the subsequent queuing module;
  • a queuing module configured to receive a query request of the user in the queue, determine whether the delay condition is met, and determine whether the remaining amount of the snap target corresponding to the user level is zero if the delay condition is met, in the remaining If the quantity is not zero, enter the random extraction module;
  • the random extraction module is configured to select a snap request of the user according to a predetermined extraction probability, and confirm that the snap purchase is successful in the selected case.
  • the filtering module is further configured to further determine that the user has entered the same level of the subsequent random extraction module before the screening request of the user is filtered according to the predetermined screening probability in the case that the remaining amount is not zero.
  • the number of users if the number of users is less than the capacity of the snap target corresponding to the user level, the user's snap request is filtered according to a predetermined screening probability; otherwise, the subsequent queuing module is entered.
  • the panning target expansion capacity corresponding to the user level is: a total amount of the snapping target corresponding to the user level multiplied by a capacity expansion coefficient corresponding to the user level; the random extraction probability is greater than or equal to the user level
  • the reciprocal of the corresponding expansion coefficient, the expansion coefficient corresponding to the user level is greater than or equal to 1.
  • the queuing module is further configured to: before entering the random extraction module, further determining whether the number of times the user queries the request exceeds a predetermined number of queries, if the remaining amount is not zero, if Confirm that the panning has failed, otherwise enter the random extraction module.
  • the filtering module includes a module for determining a remaining amount of the snapping target corresponding to the user level, and the module is specifically configured to: pre-purchase the target according to the user level.
  • the total amount is allocated, and the number of snapping targets corresponding to each user level accounts for a specified proportion of the total amount of the snapped target; the number of snapped targets corresponding to the user level corresponding to the snap request is subtracted from the snapped purchase of the same user level that has been snapped up.
  • the quantity, the remaining amount of the snap target corresponding to the user level is obtained.
  • the present invention classifies users, and divides the number of corresponding snapped targets for different user levels.
  • the user After receiving the snap request, the user determines the corresponding target of the snapped purchase according to the user level of the snap request.
  • the remaining amount in the case that the remaining amount is zero, rejects the snap request, and if the remaining amount is not zero, the user's snap request is filtered according to a predetermined screening probability, and the screening is performed by entering a subsequent random extraction step. Otherwise, it will enter the subsequent queuing step; in this way, the snapping request cannot snap up the total amount of the target to be snapped, but only for a certain proportion.
  • the malicious user will have some obvious features, such as frequent snapping and frequent IP address replacement.
  • the camouflage is a higher level user, and the invention can also pass the sieve
  • the probability is to perform the second layer filtering on the user, so that some malicious users can be filtered out; then, the snapping request entering the random extraction step is selected according to the extraction probability, so that some malicious users can be filtered out;
  • the snap request is filtered according to the delay condition, and the query request frequently sent by the malicious user using the software is effectively filtered.
  • FIG. 1 is a flow chart of an embodiment of a data processing method according to the present invention.
  • FIG. 2 is a schematic flow chart of a further embodiment of the data processing method according to the present invention.
  • FIG. 3 is a schematic flowchart of a more detailed service level of a further embodiment of the data processing method according to the present invention.
  • FIG. 4 is a schematic diagram of a composition of a data processing apparatus according to the present invention.
  • FIG. 1 is a flowchart of an embodiment of a data processing method according to the present invention. referring to FIG. 1, the method of the present invention mainly includes:
  • the filtering step 101 is: receiving a snap request of the user, obtaining the level information of the user, determining the remaining amount of the snap target corresponding to the user level, and rejecting the snap request if the remaining amount is zero, the remaining amount is not In the case of zero, the user's snap request is filtered according to a predetermined screening probability, and the screening proceeds to the subsequent random extraction step 103, otherwise to the subsequent queuing step 102.
  • the determining the remaining amount of the snapping target corresponding to the user level specifically includes: pre-allocating the total amount of the snapping target according to the user level, and the number of the snapping target corresponding to each user level accounts for the snapping purchase.
  • the specified proportion of the target total amount; the sum of the proportions of the respective user levels is equal to 1, and the number of snapped targets corresponding to the user level corresponding to the snap request is subtracted from the snapped number of the user level that has been snapped up, and the user is obtained.
  • the remaining amount of the snap target corresponding to the level specifically includes: pre-allocating the total amount of the snapping target according to the user level, and the number of the snapping target corresponding to each user level accounts for the snapping purchase.
  • the specified proportion of the target total amount; the sum of the proportions of the respective user levels is equal to 1, and the number of snapped targets corresponding to the user level corresponding to the snap request is subtracted from the snapped number of the user level that has been snapped up, and the user is obtained
  • users are hierarchically classified in advance, and the number of corresponding snapped targets is divided for different user levels.
  • the historical behavior data of the user may be queried, and the user is classified according to the historical behavior data.
  • the historical behavior data may include, for example, an address of an access page, an order record, a payment record, a number of rushes, a frequency of accessing a certain page, IP addresses, login habits, etc.
  • malicious users will have some more obvious features, such as frequent snaps and frequent IP address changes, so that malicious users can be classified into lower-level users.
  • the user can be divided into three levels of A, B, and C from high to low, and the corresponding proportion of the corresponding target is 50%, 30%, and 20%.
  • the user of the A level The number that can be snapped up is 50%*N
  • the number of users who can be snapped up by B-level is 30%*N
  • the number of users who can be snapped up by C-level is 20%*N. If the C-level user has snapped up the successful number of snaps, then the C-level user is received. After the snap request, the remaining amount of the snap target corresponding to the user level is 20%*N-k.
  • Queueing step 102 receiving a query request of the user in the queue, determining whether the delay condition is satisfied, and determining whether the remaining amount of the snap target corresponding to the user level is zero if the delay condition is satisfied, in the remaining amount In the case of not zero, the random extraction step is entered. In the case where the remaining amount is zero, it is confirmed that the snapping has failed.
  • Random extraction step 103 selecting the user's snap request according to a predetermined extraction probability, confirming that the snap purchase is successful in the selected case, otherwise confirming the snap purchase failure; after the snap purchase is successful, updating the target corresponding to the user level The remaining amount, that is, the current remaining amount, is correspondingly subtracted from the number of snaps in the current snap request.
  • the filtering step 101 may further include: before the screening request of the user is filtered according to the predetermined screening probability, in the case that the remaining amount is not zero, the method further includes:
  • Determining the number of users of the same level that has entered the subsequent random extraction step 103 Determining the number of users of the same level that has entered the subsequent random extraction step 103. If the number of users is less than the capacity of the snap target corresponding to the user level, the user's snap request is filtered according to a predetermined screening probability, and the screening is passed. After the subsequent random extraction step 103 is entered, the screening proceeds to the subsequent queuing step 102; if the number of users exceeds the snap target expansion capacity corresponding to the user level, the subsequent queuing step 102 is entered.
  • the screening probability may be set in advance, for example, may be set to 50%.
  • the panning target expansion capacity corresponding to the user level is: the number n of the snapping targets corresponding to the user level multiplied by the expansion coefficient r corresponding to the user level, that is, n ⁇ r, the n
  • the total amount of the snapped target N is a specified proportion corresponding to the user level; the random extraction probability is greater than or equal to the expansion factor corresponding to the user level.
  • the number, that is, the random extraction probability ⁇ 1 / r, the expansion coefficient corresponding to the user level is greater than or equal to 1, that is, r ⁇ 1.
  • the method further includes: determining whether the number of times the user queries the request exceeds a predetermined one. The number of queries, if it is exceeded, confirms that the panning has failed, otherwise it enters the random extraction step.
  • the present invention can classify users, and divide the number of corresponding snapped targets for different user levels. After receiving the snap request, determine the corresponding target of the snapped target according to the user level of the snap request. The remaining amount is rejected in the case where the remaining amount is zero, and if the remaining amount is not zero, the user's snap request is filtered according to a predetermined screening probability, and the screening is performed by entering a subsequent random extraction step. Otherwise, the subsequent queuing step is entered; thus, the snap request cannot capture the total amount of the target to be snapped, but only for a proportion of the number, and the malicious user may have some obvious features, such as frequent snapping and frequent IP address replacement.
  • malware users can be classified into lower-level users, and the proportion of users that can be snapped up is relatively low, so that the malicious layer can be filtered by the first layer according to the user level; if the malicious user is pretending Well, disguised as a higher-ranking user, the invention can also pass through The screening probability performs second-level filtering on the user, so that some malicious users can be filtered out; then, the snapping request entering the random extraction step is selected according to the extraction probability, so that some malicious users can be filtered out; The snap request is filtered according to the delay condition, and the query request frequently sent by the malicious user using the software is effectively filtered.
  • the present invention can effectively filter out the snapping request issued by a malicious user, and reduce the probability of successful malicious purchase by a malicious user.
  • FIG. 2 is a schematic flowchart of a further embodiment of a data processing method according to the present invention
  • FIG. 3 is a schematic flowchart of a more detailed service level of a further embodiment of the data processing method according to the present invention.
  • the user accesses the front-end snapped goods page, and the front page page asynchronously requests to query the commodity snapping state or actively requests to query the commodity snapping state, and the background receives the request for querying the snapping state.
  • the background refers to a background server or a server cluster
  • the foreground usually refers to a user interaction end, which can be implemented by a special client (Client) or by a web browser (Browser) to access the server. That is, you can use a browser/server (B/S) structure or a client/server (C/S) structure, but in the era of rapid development of network information, the system architecture may develop and change, but no matter what. Architecture, the core idea of the present invention and the core functional modules are the same, except that the modules that perform the specific functions are located at different locations.
  • S101 Check the status of the commodity, and if the verification is successful, return the purchase entry address and status information.
  • the background server After the background server receives the request for the query panning status, it first checks whether the query panning status request is normalized (the specification information of the query panning status may be preset, and the request is checked by preset specification information. Whether the specification), if not standardized, return the abnormal state information; if the specification, according to the query, the commodity number in the state request (that is, the number of the snap target), query the local storage unit (such as database, data file, etc.), further Determine whether the target of the snapping is in the snapping period; if not, return to the unstarted state, such as the snap button in the front page is "not started”; If it has ended, it returns to the end state, such as the snap button in the front page is "Ended”; if the activity is in progress, and the snap target has the remaining quantity (ie, there is still goods), then return to the in-progress state, For example, the snap button in the front page is "buy", and can be pressed, and the activity portal is returned together, and the
  • S102 A conventional verification code process.
  • the server receives the snap request, and the snap request is a request to actually enter the snap.
  • the step S104 Query the user level, the total amount and the remaining amount of the target (the total inventory and the remaining inventory), and the number of users who have entered the random extraction step (ie, the rushing step), and perform user shunting.
  • the step S104 may specifically include the following step 41.
  • the present invention can pre-set the parameter standard information of the snap request, and can check whether the parameters in the snap request meet the standard according to the preset parameter standard, and the compliance is legal, otherwise it is illegal.
  • the server checks whether the user logs in. If there is no login, he jumps into the login page and has logged in to proceed to the next step.
  • the server checks the legality of the product according to the product number in the snap request. If it is not legal, enter the failure page, otherwise go to the next step.
  • the server queries the total amount and remaining amount of the commodity and the number of users of each level that have entered the snapping process according to the product number in the snap request.
  • the server queries the user information of the user who initiates the snap request, and queries the user level of the user according to the user information, and determines the number of the snap target corresponding to the user level according to the specified proportion of the user level, and the number of the snap target is the total target of the snap target.
  • the quantity N is the ratio ⁇ corresponding to the user level, that is, ⁇ *N, and the number k of the snapped target that has been snapped up is obtained, and the remaining amount of the snapped target corresponding to the user level is: ⁇ *Nk, and the remaining amount is the snapped purchase.
  • the remaining inventory of the target if the remaining inventory is zero, enter the failure page, if the remaining inventory is not zero, proceed to the next step.
  • the purchase quota is included, that is, determining the number of users of the same level that have entered the subsequent snapping process (ie, the random extraction step), and if the number of users is greater than or equal to the target expansion capacity corresponding to the user level, the snapped-up quota is full. After entering the queuing process S106; otherwise, the snapping quota is not full, if the user rating is satisfied, the snapping process S105 is entered.
  • S107 Receive a query request of the user in the queue, for example, for the user in the queue, the countdown may be displayed in the foreground, for example, the countdown time is 10 seconds, and the countdown is allowed to allow the user to issue a query request.
  • S108 Determine the delay, the remaining inventory, and the number of queued user queries.
  • the server After receiving the query request of the queuing user, the server performs the following verification and check. Inquiry:
  • the server queries the remaining amount of the snap target corresponding to the user level, that is, the remaining inventory, determines whether there is remaining inventory, and the remaining inventory enters the abnormal processing flow, otherwise proceeds to the next step;
  • the default number of queries is 1, and it is determined whether the number of times the user queries the request exceeds a predetermined number of queries. If it exceeds, the purchase failure is confirmed, and the abnormal processing flow is entered, otherwise, the snapping process S105 is entered.
  • S109 The order is completed according to a random probability.
  • the user's snap request is selected according to a predetermined extraction probability, and the snapped purchase is confirmed to be successful if selected. Otherwise, the purchase failure is confirmed; after the purchase is successful, the remaining amount of the snap target corresponding to the user level needs to be updated, that is, the current remaining amount is correspondingly subtracted from the current purchase amount.
  • the user grading measures can filter out some of the irregular users, and randomly select some of the users who have entered the rushing process to successfully complete the order, further weakening the speed advantage of the malicious users using the software to snap up orders.
  • FIG. 4 is a schematic diagram of a composition of a data processing apparatus according to the present invention.
  • the data processing apparatus includes:
  • the filtering module 401 is configured to receive a snap request of the user, obtain the level information of the user, determine a remaining amount of the snap target corresponding to the user level, and reject the snap request if the remaining amount is zero. If the quantity is not zero, the user's snap request is filtered according to a predetermined screening probability, and the screening proceeds to the subsequent random extraction module 403, otherwise enters the subsequent queuing module 402;
  • the queuing module 402 is configured to receive a query request of the user in the queue, determine whether the delay condition is met, and determine whether the remaining amount of the snap target corresponding to the user level is zero if the delay condition is met, If the remaining amount is not zero, enter the random extraction module 403;
  • the random extraction module 403 is configured to select a snap request of the user according to a predetermined extraction probability, and confirm that the snap purchase is successful in the selected case.
  • the filtering module 401 is further configured to:
  • the number of users of the same level that has entered the subsequent random extraction module 403 is further determined, and the number of users is less than
  • the user's snap request is filtered according to a predetermined screening probability; otherwise, the subsequent queue module 402 is entered.
  • the panning target expansion capacity corresponding to the user level is: a total amount of the snapping target corresponding to the user level multiplied by a capacity expansion coefficient corresponding to the user level; the random extraction probability is greater than And a reciprocal of the expansion coefficient corresponding to the user level, where the expansion coefficient corresponding to the user level is greater than or equal to 1.
  • the queuing module 402 is further configured to: before entering the random extraction module 403, if the remaining amount is not zero, further determining whether the number of times the user queries the request exceeds a predetermined number. The number of queries, if it is exceeded, confirms that the snapping fails, otherwise enters the random extraction module 403.
  • the filtering module 401 is included for determining and using The module of the remaining amount of the snapping target corresponding to the household level, the module is specifically configured to: allocate the total amount of the snapping target according to the user level in advance, and the number of the snapping target corresponding to each user level accounts for a specified proportion of the total amount of the snapped target; The sum of the proportions of the user levels is equal to 1, and the number of snapped targets corresponding to the user level corresponding to the snap request is subtracted from the snapped number of the user level that has been snapped up, and the remaining target of the snapped target corresponding to the user level is obtained. the amount.
  • each functional module in each embodiment of the present invention may be integrated into one processing unit, or each module may exist physically separately, or two or more modules may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • the functional modules of the various embodiments may be located at one terminal or network node, or may be distributed to multiple terminals or network nodes.
  • each of the embodiments of the present invention can be implemented by a data processing program executed by a data processing device such as a computer.
  • the data processing program constitutes the present invention.
  • a data processing program usually stored in a storage medium is executed by directly reading a program out of a storage medium or by installing or copying the program to a storage device (such as a hard disk and or a memory) of the data processing device. Therefore, such a storage medium also constitutes the present invention.
  • the storage medium can use any type of recording method, such as paper storage medium (such as paper tape, etc.), magnetic storage medium (such as floppy disk, hard disk, flash memory, etc.), optical storage medium (such as CD-ROM, etc.), magneto-optical storage medium (such as MO, etc.).
  • paper storage medium such as paper tape, etc.
  • magnetic storage medium such as floppy disk, hard disk, flash memory, etc.
  • optical storage medium such as CD-ROM, etc.
  • magneto-optical storage medium Such as MO, etc.
  • the present invention therefore also discloses a storage medium in which is stored a data processing program for performing any of the above embodiments of the present invention.
  • the method steps of the present invention can be implemented by a data processing program, and can also be implemented by hardware, for example, by logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers, and embedded micro-controls. And so on.
  • ASICs application specific integrated circuits
  • programmable logic controllers programmable logic controllers
  • embedded micro-controls embedded micro-controls.

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Abstract

一种数据处理方法和装置，包括：过滤步骤：接收用户的抢购请求，获取该用户的等级信息，确定为该用户等级对应划分的抢购目标的剩余量，在所述剩余量为零的情况下拒绝该抢购请求，在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取步骤，否则进入后续排队步骤（101）；排队步骤：接收在排队中的用户的查询请求，判断是否满足延时条件，在满足延时条件的情况下判断与该用户等级对应的抢购目标的剩余量是否为零，在所述剩余量不为零的情况下，进入所述随机抽取步骤（102）；随机抽取步骤：根据预定的抽取概率对所述用户的抢购请求进行选择，在选中的情况下确认抢购成功（103）。该方法和装置可以降低恶意用户的抢购成功几率。

Description

数据处理方法和系统 技术领域
本申请涉及网络数据处理技术领域，尤其涉及一种数据处理方法和系统。
背景技术
目前，随着网络的普及，基于智能设备(如计算机、智能手机、平板电脑等)和通信网络的电子商务系统和电子物流系统迅猛发展起来，通过互联网进行网上购物和销售也越来越成为一种趋势。电子商务系统主要是用于与用户进行人机交互，接受用户的指令生成对应的业务请求(例如订单就是一种业务请求)，对相应的商品标的信息进行数据处理的信息处理系统。
随着电子商务的快速发展，电子商务系统各方之间的竞争也愈加激烈，各种类型的抢购活动已成为一种常用的促销方式，通过选择低于市场价格的商品让利于买家，以作为增加老用户的粘度，同时吸引新用户加入的手段之一。
抢购商品以价格低于市场价或者商品比较稀有等因素，不止吸引普通用户的关注，同时很多恶意用户采用机器软件来参与抢购活动，抢到商品加价转手销售。普通用户的抢购速度很难达到软件速度，因此原本让利与买家的活动，不仅没有真正让用户得到实惠，还有可能给用户带来挫败感。
现有技术中，为了阻挡恶意用户使用软件等方式参与抢购活动，目前主要以验证码、授权认证等方式进行验证。
其中，现有的验证码技术方案主要包括：在处理抢购请求(抢购 请求也是一种电子商务系统中的一种业务请求)的过程中，加入验证码校验的环节，用户输入验证码，服务器校验验证码，校验正确继续后面流程，校验失败则重新输入验证码。
现有的授权认证技术方案主要包括：一般是用户需在抢购之前申请抢购资格，抢购活动开始之后，用户参与抢购，服务器校验用户有没有资格或者根据用户等级来判断，校验成功继续后面流程，校验失败则不能参与抢购。
但是，现有技术存在以下缺陷：
现有的阻挡恶意用户的方式，一般只在提升系统对软件模仿的难度，比如提升验证码难度，增加更多的人机互动的流程。但是现在的恶意用户在未破解系统之前，经常使用半自动化的软件参与抢购，软件只负责常规访问和提交功能，需要人工输入的，则恶意用户采用人工输入，人工输入完成后，软件自动提交。软件的速度很快，与正常用户相比，这种恶意用户有明显的速度优势。同时恶意用户一般使用大量的注册用户来抢购，大比例的恶意用户加上速度优势，造成恶意抢购的成功几率很高，相应的普通用户就很难抢购成功了。
发明内容
有鉴于此，本发明的主要目的是提供一种数据处理方法和系统，降低恶意抢购的成功几率。
本发明的技术方案是这样实现的：
一种数据处理方法，包括：
过滤步骤：接收用户的抢购请求，获取该用户的等级信息，确定为该用户等级对应划分的抢购目标的剩余量，在所述剩余量为零的情况下拒绝该抢购请求，在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取步骤，否则进入后续排队步骤；
排队步骤：接收在排队中的用户的查询请求，判断是否满足延时条件，在满足延时条件的情况下判断与该用户等级对应的抢购目标的剩余量是否为零，在所述剩余量不为零的情况下，进入所述随机抽取步骤；
随机抽取步骤：根据预定的抽取概率对所述用户的抢购请求进行选择，在选中的情况下确认抢购成功。
优选的，所述过滤步骤中，在所述在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选之前，进一步包括：确定已进入后续随机抽取步骤的同等级的用户数，在该用户数小于与该用户等级对应的抢购目标扩容量的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选；否则进入后续排队步骤。
优选的，所述与该用户等级对应的抢购目标扩容量为：与该用户等级对应的抢购目标的总量乘以与该用户等级对应的扩容系数；所述随机抽取概率大于等于与该用户等级对应的扩容系数的倒数，所述与该用户等级对应的扩容系数大于等于1。
优选的，所述排队步骤中，在所述剩余量不为零的情况下，进入所述随机抽取步骤之前，进一步包括：判断所述用户查询请求的次数是否超过预定的查询次数，如果超过则确认抢购失败，否则进入所述随机抽取步骤。
优选的，所述确定与该用户等级对应的抢购目标的剩余量，具体包括：预先根据用户等级对抢购目标的总量进行分配，每一用户等级对应的抢购目标数量占该抢购目标总量的指定比例；将所述抢购请求对应的用户等级对应的抢购目标数量减去同用户等级中已经抢购成功的抢购数量，得到与该用户等级对应的抢购目标的剩余量。
一种数据处理装置，包括：
过滤模块，用于接收用户的抢购请求，获取该用户的等级信息，确定为该用户等级对应划分的抢购目标的剩余量，在所述剩余量为零的情况下拒绝该抢购请求，在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取模块，否则进入后续排队模块；
排队模块，用于接收在排队中的用户的查询请求，判断是否满足延时条件，在满足延时条件的情况下判断与该用户等级对应的抢购目标的剩余量是否为零，在所述剩余量不为零的情况下，进入所述随机抽取模块；
随机抽取模块，用于根据预定的抽取概率对所述用户的抢购请求进行选择，在选中的情况下确认抢购成功。
优选的，所述过滤模块进一步用于：在所述在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选之前，进一步确定已进入后续随机抽取模块的同等级的用户数，在该用户数小于与该用户等级对应的抢购目标扩容量的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选；否则进入后续排队模块。
优选的，所述与该用户等级对应的抢购目标扩容量为：与该用户等级对应的抢购目标的总量乘以与该用户等级对应的扩容系数；所述随机抽取概率大于等于与该用户等级对应的扩容系数的倒数，所述与该用户等级对应的扩容系数大于等于1。
优选的，所述排队模块进一步用于：在所述剩余量不为零的情况下，进入所述随机抽取模块之前，进一步判断所述用户查询请求的次数是否超过预定的查询次数，如果超过则确认抢购失败，否则进入所述随机抽取模块。
优选的，所述过滤模块中包括用于确定与用户等级对应的抢购目标的剩余量的模块，该模块具体用于：预先根据用户等级对抢购目标 的总量进行分配，每一用户等级对应的抢购目标数量占该抢购目标总量的指定比例；将所述抢购请求对应的用户等级对应的抢购目标数量减去同用户等级中已经抢购成功的抢购数量，得到与该用户等级对应的抢购目标的剩余量。
与现有技术相比，本发明对用户划分等级，针对不同的用户等级对相应的抢购目标的数量进行划分，在收到抢购请求后，根据该抢购请求的用户等级，确定对应划分的抢购目标的剩余量，在所述剩余量为零的情况下拒绝该抢购请求，在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取步骤，否则进入后续排队步骤；这样抢购请求就不能抢购待抢购目标的总量，而是只针对一个比例的数量，恶意用户会具备一些较明显的特征，例如抢购次数多，IP地址更换频繁等特征，这样就可以将恶意用户划分到等级较低的用户中，这部分用户所可以抢购的数量比例较低，这样就可以按照用户等级对恶意用户进行了第一层的过滤；如果恶意用户伪装得较好，伪装成了等级较高的用户，则本发明还可以通过所述筛选概率对用户进行第二层过滤，这样又可以过滤掉一部分恶意用户；接下来，再对进入随机抽取步骤的抢购请求按照抽取概率进行选择，这样又可以过滤掉一部分恶意用户；对于进入排队步骤的抢购请求，会根据时延条件进行过滤，对恶意用户使用软件频繁地发出的查询请求会进行有效地过滤。通过上述综合的过滤处理，本发明可以有效地过滤掉恶意用户发出的抢购请求，降低恶意用户的恶意抢购的成功几率。
附图说明
图1为本发明所述数据处理方法的一种实施例流程图；
图2为本发明所述数据处理方法的进一步实施例的流程示意图；
图3为本发明所述数据处理方法的进一步实施例的更为详细的业务层面的流程示意图；
图4为本发明所述数据处理装置的一种组成示意图。
具体实施方式
下面结合附图及具体实施例对本发明再作进一步详细的说明。
图1为本发明所述数据处理方法的一种实施例流程图；参见图1，本发明的方法主要包括：
过滤步骤101：接收用户的抢购请求，获取该用户的等级信息，确定为该用户等级对应划分的抢购目标的剩余量，在所述剩余量为零的情况下拒绝该抢购请求，在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取步骤103，否则进入后续排队步骤102。
所述过滤步骤101中，所述确定与该用户等级对应的抢购目标的剩余量，具体包括：预先根据用户等级对抢购目标的总量进行分配，每一用户等级对应的抢购目标数量占该抢购目标总量的指定比例；各个用户等级所占比例的和值等于1，将所述抢购请求对应的用户等级对应的抢购目标数量减去同用户等级中已经抢购成功的抢购数量，得到与该用户等级对应的抢购目标的剩余量。
本发明中，预先对用户划分等级，针对不同的用户等级对相应的抢购目标的数量进行划分。例如可以查询用户的历史行为数据，根据历史行为数据对用户进行分类划分，所述历史行为数据例如可以包括：访问页面的地址、下单记录、付款记录、抢购次数、访问某个页面的频率、IP地址、登录习惯等等，恶意用户会具备一些较明显的特征，例如抢购次数多，IP地址更换频繁等特征，这样就可以将恶意用户划分到等级较低的用户中。例如可以将用户由高到低分为A、B、C三个等级，对应的分配抢购目标的指定比例为50％、30％、20％，假设抢购目标的总量为N，则A等级用户可以抢购的数量为50％*N，B等级用户可以抢购的数量为30％*N，C等级用户可以抢购的数量为20％*N。假如C等级用户已经抢购成功的抢购数量为k，则当收到C等级用户 的抢购请求后，该用户等级对应的抢购目标的剩余量为20％*N-k。
目前的电子商务系统中，都有用户行为数据的采集系统和查询接口，本发明可以从该查询接口直接查询需要的用户行为数据。
排队步骤102：接收在排队中的用户的查询请求，判断是否满足延时条件，在满足延时条件的情况下判断与该用户等级对应的抢购目标的剩余量是否为零，在所述剩余量不为零的情况下，进入所述随机抽取步骤。在所述剩余量为零的情况下，确认抢购失败。
随机抽取步骤103：根据预定的抽取概率对所述用户的抢购请求进行选择，在选中的情况下确认抢购成功，否则确认抢购失败；抢购成功后，则需要更新与该用户等级对应的抢购目标的剩余量，即当前剩余量要相应地减去当前抢购请求中的抢购数量。
在一种优选实施例中，所述过滤步骤101中，在所述在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选之前，还可以进一步包括：
确定已进入后续随机抽取步骤103的同等级的用户数，在该用户数小于与该用户等级对应的抢购目标扩容量的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取步骤103，筛选通不过则进入后续排队步骤102；在该用户数超过与该用户等级对应的抢购目标扩容量的情况下，进入后续排队步骤102。
所述筛选概率可以预先设置，例如可以设置为50％。
更为具体的，所述与该用户等级对应的抢购目标扩容量为：与该用户等级对应的抢购目标的数量n乘以与该用户等级对应的扩容系数r，即n×r，所述n为：该抢购目标的总量N×该用户等级对应的指定比例；所述随机抽取概率大于等于与该用户等级对应的扩容系数的倒 数，即随机抽取概率≥1/r，所述与该用户等级对应的扩容系数大于等于1，即r≥1。
在一种优选实施例中，所述排队步骤102中，在所述剩余量不为零的情况下，进入所述随机抽取步骤之前，进一步包括：判断所述用户查询请求的次数是否超过预定的查询次数，如果超过则确认抢购失败，否则进入所述随机抽取步骤。
通过上述处理，本发明可以对用户划分等级，并针对不同的用户等级对相应的抢购目标的数量进行划分，在收到抢购请求后，根据该抢购请求的用户等级，确定对应划分的抢购目标的剩余量，在所述剩余量为零的情况下拒绝该抢购请求，在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取步骤，否则进入后续排队步骤；这样抢购请求就不能抢购待抢购目标的总量，而是只针对一个比例的数量，恶意用户会具备一些较明显的特征，例如抢购次数多，IP地址更换频繁等特征，这样就可以将恶意用户划分到等级较低的用户中，这部分用户所可以抢购的数量比例较低，这样就可以按照用户等级对恶意用户进行了第一层的过滤；如果恶意用户伪装得较好，伪装成了等级较高的用户，则本发明还可以通过所述筛选概率对用户进行第二层过滤，这样又可以过滤掉一部分恶意用户；接下来，再对进入随机抽取步骤的抢购请求按照抽取概率进行选择，这样又可以过滤掉一部分恶意用户；对于进入排队步骤的抢购请求，会根据时延条件进行过滤，对恶意用户使用软件频繁地发出的查询请求会进行有效地过滤。通过上述综合的过滤处理，本发明可以有效地过滤掉恶意用户发出的抢购请求，降低恶意用户的恶意抢购的成功几率。
上述所介绍的是本发明所述方法的几种基本的实施例，在进一步的实施例中，在所述数据处理过程中，还可以包括更加丰富的校验、检查等处理步骤，这样可以进一步增加恶意用户抢购失败的几率。下 面结合附图进一步介绍本发明的更进一步的实施例。
图2为本发明所述数据处理方法的进一步实施例的流程示意图；图3为本发明所述数据处理方法的进一步实施例的更为详细的业务层面的流程示意图。参见图2和图3，介绍本发明所述的基于用户行为的分级阻挡恶意用户抢购的详细流程如下：
S100：接收查询抢购状态的请求。
实际应用中，用户访问前台的抢购商品页面，前台页面会异步请求查询商品抢购状态或者主动请求查询商品抢购状态，此时后台接收查询抢购状态的请求。
所述后台是指后台服务器或服务器集群，所述前台通常是指与用户交互端，具体可以通过专门的客户端(Client)实现，也可以通过网络浏览器(Browser)来访问服务器的方式实现，即可以采用浏览器/服务器(B/S)结构，也可以采用客户端/服务器(C/S)结构，但是在网络信息飞速发展的年代，系统架构可能还会发展和变化，但不论是什么架构，本发明的核心思想和核心的功能模块是相同的，只是执行具体功能的模块的所处位置不同而已。
S101：校验商品状态，若校验成功则返回抢购入口地址和状态信息。
其中具体包括：后台服务器接收到所述查询抢购状态的请求之后，首先检验该查询抢购状态请求是否规范(可以预先设定该查询抢购状态的规范信息，以预先设定的规范信息来检查该请求是否规范)，如果不规范，则返回异常状态信息；如果规范，则根据该查询抢购状态请求中的商品编号(即抢购目标的编号)，查询本地存储单元(如数据库，数据文件等)，进一步判断本抢购目标是否在抢购期间；如果未开始则返回未开始状态，如前台页面中的抢购按钮为“未开始”； 如果已结束，则返回已结束状态，如前台页面中的抢购按钮为“已结束”；如果活动正在进行中，且该抢购目标还有剩余数量(即还有货)，则返回进行中状态，如前台页面中的抢购按钮为“抢购中”，并且可以按下，并把活动入口一并返回，并加上基于用户的会话数据(session)，进入下一步；如果活动正在进行中，但该抢购目标没有剩余数量(即无货)，则返回进行中状态，前台页面中的抢购按钮为“抢购中”，但不可以按下。
S102：常规验证码流程。
本步骤中，可以采用现有技术中的常规验证码验证流程，本文对此不再赘述。
S103：接收抢购请求。
服务器接收抢购请求，该抢购请求就是实质进入抢购的请求。
S104：查询用户等级，抢购目标的总量和剩余量(总库存和剩余库存)，以及已经进入随机抽取步骤(即抢购步骤)的用户数量，进行用户分流，该步骤S104具体可以包括以下步骤41至46：
服务器接收到用户的抢购请求之后，进行如下流程：
41、检查该抢购请求的参数是否合法，如果非法则进入错误处理流程，合法进入下一步。本发明可以预先设置所述抢购请求的参数标准信息，可以根据预先设置的参数标准检查该抢购请求中的参数是否符合标准，符合则合法，否则不合法。
42、服务器检验用户是否登陆，如果没有登陆，则跳入登陆页面，已经登录则进入下一步。
43、服务器根据抢购请求中的商品编号，进行商品合法性检查， 如果不合法则进入失败页面，否则进入下一步。
44、服务器根据抢购请求中的商品编号，查询本商品总量和剩余量以及已进入抢购流程的各等级的用户数。
45、服务器查询发起抢购请求用户的用户信息，根据用户信息，查询该用户的用户等级，按照该用户等级的指定比例确定该用户等级对应的抢购目标的数量，该抢购目标的数量为抢购目标总量N×该用户等级对应的比例α，即α*N，查询本抢购目标已经被抢购的数量k，得到该用户等级对应的抢购目标的剩余量为：α*N-k，该剩余量就是该抢购目标的剩余库存，如果剩余库存为零，则进入失败页面，如果剩余库存不为零，则进入下一步。
46、判断是否含有抢购名额，即确定已进入后续抢购流程(即随机抽取步骤)的同等级的用户数，如果该用户数大于等于与该用户等级对应的抢购目标扩容量，则抢购名额满，进入排队流程S106；否则抢购名额未满，则在满足用户分级的情况下，进入抢购流程S105。所述抢购目标的扩容量为α*N*r，所述r为扩容系数，r＞＝1。
S105：进入抢购流程，进入抢购流程的用户，进入后续步骤S109。
S106：进入排队流程，进入排队流程的用户，进入后续步骤S107。
S107：接收在排队中的用户的查询请求，例如针对排队中的用户，在前台可以显示倒计时，例如倒计时的时间为10秒，倒计时结束才允许用户发出查询请求。
S108：判断延时、剩余库存和排队用户查询次数。
具体的，服务器接收排队用户的查询请求后，进行如下验证和查 询：
81、验证查询请求的数据是否合法，不合法则进入异常处理流程，所述异常处理流程即进入失败页面，合法进入下一步；
82、验证查询请求时间差是否在指定的时延以上(如10s以上)，小于指定的时延则进入异常处理流程，否则进入下一步；
83、服务器查询与该用户等级对应的抢购目标的剩余量即剩余库存，判断是否还有剩余库存，没有剩余库存进入异常处理流程，否则进入下一步；
84、用户是否满足查询次数，例如默认的查询次数为1，判断所述用户查询请求的次数是否超过预定的查询次数，如果超过则确认抢购失败，进入异常处理流程，否则进入抢购流程S105。
S109：按照随机概率选择完成订单。
根据预定的抽取概率对所述用户的抢购请求进行选择，在选中的情况下确认抢购成功。否则确认抢购失败；抢购成功后，则需要更新与该用户等级对应的抢购目标的剩余量，即当前剩余量要相应地减去当前抢购请求中的抢购数量。所述随机抽取概率大于等于与该用户等级对应的扩容系数r的倒数。例如：该用户等级对应的抢购目标的数量为n，则进入抢购流程的该等级的用户数量为r*n(r＞＝1)，则随机选择n个用户可以成功完成订单，抢购成功。
通过本发明的处理，可以有效的降低恶意用户的订单成功率。用户分级措施可以过滤掉部分不合规则用户，同时从进入抢购流程的用户中随机抽取部分成功完成下单，进一步弱化了恶意用户利用软件抢购订单的速度优势。
与上述方法对应，本发明还公开了一种数据处理装置。图4为本发明所述数据处理装置的一种组成示意图。参见图4，该数据处理装置包括：
过滤模块401，用于接收用户的抢购请求，获取该用户的等级信息，确定为该用户等级对应划分的抢购目标的剩余量，在所述剩余量为零的情况下拒绝该抢购请求，在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取模块403，否则进入后续排队模块402；
排队模块402，用于接收在排队中的用户的查询请求，判断是否满足延时条件，在满足延时条件的情况下判断与该用户等级对应的抢购目标的剩余量是否为零，在所述剩余量不为零的情况下，进入所述随机抽取模块403；
随机抽取模块403，用于根据预定的抽取概率对所述用户的抢购请求进行选择，在选中的情况下确认抢购成功。
在一种优选实施例中，所述过滤模块401进一步用于：
在所述在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选之前，进一步确定已进入后续随机抽取模块403的同等级的用户数，在该用户数小于与该用户等级对应的抢购目标扩容量的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选；否则进入后续排队模块402。
在一种优选实施例中，所述与该用户等级对应的抢购目标扩容量为：与该用户等级对应的抢购目标的总量乘以与该用户等级对应的扩容系数；所述随机抽取概率大于等于与该用户等级对应的扩容系数的倒数，所述与该用户等级对应的扩容系数大于等于1。
在一种优选实施例中，所述排队模块402进一步用于：在所述剩余量不为零的情况下，进入所述随机抽取模块403之前，进一步判断所述用户查询请求的次数是否超过预定的查询次数，如果超过则确认抢购失败，否则进入所述随机抽取模块403。
在又一种优选实施例中，所述过滤模块401中包括用于确定与用 户等级对应的抢购目标的剩余量的模块，该模块具体用于：预先根据用户等级对抢购目标的总量进行分配，每一用户等级对应的抢购目标数量占该抢购目标总量的指定比例；各个用户等级所占比例的和值等于1，将所述抢购请求对应的用户等级对应的抢购目标数量减去同用户等级中已经抢购成功的抢购数量，得到与该用户等级对应的抢购目标的剩余量。
另外，在本发明各个实施例中的各功能模块可以集成在一个处理单元中，也可以是各个模块单独物理存在，也可以两个或两个以上模块集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。所述各实施例的功能模块可以位于一个终端或网络节点，或者也可以分布到多个终端或网络节点上。
另外，本发明的每一个实施例可以通过由数据处理设备如计算机执行的数据处理程序来实现。显然，数据处理程序构成了本发明。此外，通常存储在一个存储介质中的数据处理程序通过直接将程序读取出存储介质或者通过将程序安装或复制到数据处理设备的存储设备(如硬盘和或内存)中执行。因此，这样的存储介质也构成了本发明。存储介质可以使用任何类型的记录方式，例如纸张存储介质(如纸带等)、磁存储介质(如软盘、硬盘、闪存等)、光存储介质(如CD-ROM等)、磁光存储介质(如MO等)等。
因此本发明还公开了一种存储介质，其中存储有数据处理程序，该数据处理程序用于执行本发明上述方法的任何一种实施例。
另外，本发明所述的方法步骤除了可以用数据处理程序来实现，还可以由硬件来实现，例如，可以由逻辑门、开关、专用集成电路(ASIC)、可编程逻辑控制器和嵌入微控制器等来实现。因此这种可以实现本发明所述方法的硬件也可以构成本发明。
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内，所做的任何修改、等同替换、改进等，均应包含在本发明保护的范围之内。

Claims (10)

  1. 一种数据处理方法，其特征在于，包括：
    过滤步骤：接收用户的抢购请求，获取该用户的等级信息，确定为该用户等级对应划分的抢购目标的剩余量，在所述剩余量为零的情况下拒绝该抢购请求，在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取步骤，否则进入后续排队步骤；
    排队步骤：接收在排队中的用户的查询请求，判断是否满足延时条件，在满足延时条件的情况下判断与该用户等级对应的抢购目标的剩余量是否为零，在所述剩余量不为零的情况下，进入所述随机抽取步骤；
    随机抽取步骤：根据预定的抽取概率对所述用户的抢购请求进行选择，在选中的情况下确认抢购成功。
  2. 根据权利要求1所述的方法，其特征在于，所述过滤步骤中，在所述在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选之前，进一步包括：
    确定已进入后续随机抽取步骤的同等级的用户数，在该用户数小于与该用户等级对应的抢购目标扩容量的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选；否则进入后续排队步骤。
  3. 根据权利要求2所述的方法，其特征在于，
    所述与该用户等级对应的抢购目标扩容量为：与该用户等级对应的抢购目标的总量乘以与该用户等级对应的扩容系数；
    所述随机抽取概率大于等于与该用户等级对应的扩容系数的倒数，所述与该用户等级对应的扩容系数大于等于1。
  4. 根据权利要求1所述的方法，其特征在于，所述排队步骤中， 在所述剩余量不为零的情况下，进入所述随机抽取步骤之前，进一步包括：
    判断所述用户查询请求的次数是否超过预定的查询次数，如果超过则确认抢购失败，否则进入所述随机抽取步骤。
  5. 根据权利要求1所述的方法，其特征在于，所述确定与该用户等级对应的抢购目标的剩余量，具体包括：
    预先根据用户等级对抢购目标的总量进行分配，每一用户等级对应的抢购目标数量占该抢购目标总量的指定比例；将所述抢购请求对应的用户等级对应的抢购目标数量减去同用户等级中已经抢购成功的抢购数量，得到与该用户等级对应的抢购目标的剩余量。
  6. 一种数据处理装置，其特征在于，包括：
    过滤模块，用于接收用户的抢购请求，获取该用户的等级信息，确定为该用户等级对应划分的抢购目标的剩余量，在所述剩余量为零的情况下拒绝该抢购请求，在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选，筛选通过进入后续随机抽取模块，否则进入后续排队模块；
    排队模块，用于接收在排队中的用户的查询请求，判断是否满足延时条件，在满足延时条件的情况下判断与该用户等级对应的抢购目标的剩余量是否为零，在所述剩余量不为零的情况下，进入所述随机抽取模块；
    随机抽取模块，用于根据预定的抽取概率对所述用户的抢购请求进行选择，在选中的情况下确认抢购成功。
  7. 根据权利要求6所述的装置，其特征在于，所述过滤模块进一步用于：
    在所述在剩余量不为零的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选之前，进一步确定已进入后续随机抽取模块的同等级的用户数，在该用户数小于与该用户等级对应的抢购目标扩容量 的情况下，根据预定的筛选概率对该用户的抢购请求进行筛选；否则进入后续排队模块。
  8. 根据权利要求7所述的装置，其特征在于，
    所述与该用户等级对应的抢购目标扩容量为：与该用户等级对应的抢购目标的总量乘以与该用户等级对应的扩容系数；
    所述随机抽取概率大于等于与该用户等级对应的扩容系数的倒数，所述与该用户等级对应的扩容系数大于等于1。
  9. 根据权利要求6所述的装置，其特征在于，所述排队模块进一步用于：
    在所述剩余量不为零的情况下，进入所述随机抽取模块之前，进一步判断所述用户查询请求的次数是否超过预定的查询次数，如果超过则确认抢购失败，否则进入所述随机抽取模块。
  10. 根据权利要求6所述的装置，其特征在于，所述过滤模块中包括用于确定与用户等级对应的抢购目标的剩余量的模块，该模块具体用于：预先根据用户等级对抢购目标的总量进行分配，每一用户等级对应的抢购目标数量占该抢购目标总量的指定比例；将所述抢购请求对应的用户等级对应的抢购目标数量减去同用户等级中已经抢购成功的抢购数量，得到与该用户等级对应的抢购目标的剩余量。
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* Cited by examiner, † Cited by third party
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* Cited by examiner, † Cited by third party
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CN106096996A (zh) * 2016-05-31 2016-11-09 北京奇虎科技有限公司 移动终端作弊行为的检测方法及相应装置
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CN106598881B (zh) * 2016-12-20 2020-10-09 北京小米移动软件有限公司 页面处理方法及装置
CN107273220A (zh) * 2017-05-11 2017-10-20 广东网金控股股份有限公司 一种电商平台数据处理方法、装置及用户终端
CN107230133B (zh) * 2017-05-26 2020-12-22 努比亚技术有限公司 一种数据处理方法、设备和计算机存储介质
CN108512938B (zh) * 2018-04-17 2021-03-30 创新先进技术有限公司 一种数据请求的处理方法、装置及电子设备
CN109451506B (zh) * 2018-11-27 2022-04-15 中国联合网络通信集团有限公司 Lte扩容的评估方法、装置、终端及计算机存储介质
CN110175880B (zh) * 2019-04-02 2022-04-19 创新先进技术有限公司 商品购买方法、装置、设备及存储介质
CN112148756A (zh) * 2020-09-24 2020-12-29 四川长虹电器股份有限公司 商品预约抢购优化方法
CN112085240A (zh) * 2020-09-28 2020-12-15 中国建设银行股份有限公司 抢购商品交易数据处理方法及系统
CN113596127B (zh) * 2021-07-20 2022-08-02 中国联合网络通信集团有限公司 一种服务提供方法及装置

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102346891A (zh) * 2010-07-30 2012-02-08 阿里巴巴集团控股有限公司 一种网络交易方法及服务器
CN103679497A (zh) * 2012-09-20 2014-03-26 阿里巴巴集团控股有限公司 一种试用商品的派发方法及装置
US20140278610A1 (en) * 2013-03-15 2014-09-18 Live Nation Entertainment, Inc. Abuse tolerant ticketing system
CN104184730A (zh) * 2014-08-20 2014-12-03 小米科技有限责任公司 访问处理方法和装置、电子设备
CN104462977A (zh) * 2014-12-23 2015-03-25 北京京东尚科信息技术有限公司 数据处理方法和系统

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101393630A (zh) * 2007-09-21 2009-03-25 莱尔富国际股份有限公司 限量商品的销售系统及方法
CN103246929A (zh) * 2012-02-07 2013-08-14 周双桂 一种网上预订的数据处理及自动售票方法
CN103581271B (zh) * 2012-08-08 2018-09-18 腾讯科技（深圳）有限公司 确定预选择用户的方法和装置、系统
CN102930628A (zh) * 2012-11-13 2013-02-13 任建军 一种根据参与者抢占特定位置决定是否中奖的抽奖方法及系统
CN103136690A (zh) * 2013-02-03 2013-06-05 张俊良 一种免费抢购营销模式及交易方法
CN103745387A (zh) * 2014-01-27 2014-04-23 胡泽军 一种火车票网络销售方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102346891A (zh) * 2010-07-30 2012-02-08 阿里巴巴集团控股有限公司 一种网络交易方法及服务器
CN103679497A (zh) * 2012-09-20 2014-03-26 阿里巴巴集团控股有限公司 一种试用商品的派发方法及装置
US20140278610A1 (en) * 2013-03-15 2014-09-18 Live Nation Entertainment, Inc. Abuse tolerant ticketing system
CN104184730A (zh) * 2014-08-20 2014-12-03 小米科技有限责任公司 访问处理方法和装置、电子设备
CN104462977A (zh) * 2014-12-23 2015-03-25 北京京东尚科信息技术有限公司 数据处理方法和系统

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110333951A (zh) * 2019-07-09 2019-10-15 北京首汽智行科技有限公司 一种商品抢购请求分配方法
CN110333951B (zh) * 2019-07-09 2023-08-01 北京首汽智行科技有限公司 一种商品抢购请求分配方法
CN112508641A (zh) * 2020-12-01 2021-03-16 数字广东网络建设有限公司 一种物品的分配方法、装置、计算机设备和存储介质

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