Tool and method for assisting business hall to carry out window service

Abstract

The invention relates to a tool and a method for assisting a business hall to carry out window service, which are characterized in that an input association form is judged, a corresponding conversion time range is determined according to the specific length of data in different forms and the conversion frequency among the different forms, and a calibration time range belonging to a corresponding link is determined; then, a basic range is positioned in a calibration time range of different links, so that a final to-be-transformed form is positioned, the information form transformation frequency is higher, the time is shorter, the extraction time is reduced to the maximum extent, and the extraction frequency is ensured; in order to distinguish whether the service prediction information has the corresponding business hall window which is not input or not in the tracing period, the corresponding associated time-point line is combined to execute centralized analysis, so that the associated business hall window which is not input can be efficiently positioned and directly displayed, and therefore, related operators can timely grasp the input information of the service prediction information, and the service prediction efficiency is improved. And the method is suitable for information backtracking for future service prediction.

Description

Technical Field

[0001] The present invention belongs to the technical field of assisting business halls in carrying out window services, and in particular relates to a tool and method for assisting business halls in carrying out window services. Background Art

[0002] The functions of the power supply business hall include business processing, charging, notice, guidance, negotiation, as well as providing comprehensive energy services, intelligent guidance, self-service, online business experience, etc. As the forefront of power services, the innovation of the functions and service models of the power supply business hall is directly related to the experience and satisfaction of power customers. With the development of technology and the renewal of service concepts, the power supply business hall is no longer just a traditional charging and business processing place, but is developing in a more intelligent and convenient direction.

[0003] In terms of customer satisfaction services provided at windows of auxiliary business halls, the existing technical solution with patent application number "CN202210574055.8" and patent name "A customer satisfaction prediction method and device" is often used to predict customer satisfaction of window services provided at auxiliary business halls.

[0004] Specifically, the audio stream information and video frame information when serving customers are obtained to predict the customer satisfaction with the window service provided by the auxiliary business hall. The audio stream information or video frame information is the information used for service prediction.

[0005] The service prediction information will also be used for retrospective use. During the execution of retrospective use, since different links correspond to different business hall windows and the service prediction information input by each business hall window is often in different forms, when performing service prediction information control in the future, different forms of service prediction information must be converted into information of the same form to perform future retrospective control. However, the current devices that assist business halls in providing window services do not have a high-performance form conversion method, which will result in a long time for form conversion and insufficient efficiency, which is not conducive to the subsequent retrospective control function. Summary of the invention

[0006] In order to solve the defects in the prior art, the present invention proposes a tool and method for assisting business halls in providing window services, which determines the input related forms and identifies the corresponding transformation time range according to the specific length of different form data and the transformation frequency between different forms, and then identifies the calibration time range belonging to the corresponding link according to the corresponding transformation time range identified by the corresponding link, and then locates the basic range in the calibration time range of different links to locate the final form to be transformed, and uses the above processing method to determine its time range, to ensure that during the data form transformation, the frequency of information form transformation is higher and the time is shorter, and the extraction time is minimized to ensure the extraction frequency; to identify whether the service prediction information has any corresponding business hall windows that have not been input during the tracing period, and to perform centralized analysis in conjunction with the corresponding related time point line, the related business hall windows that have not been input can be efficiently located and directly displayed, so that the relevant operation personnel can immediately grasp the service prediction information input information and can trace back the service prediction information in the future.

[0007] The present invention utilizes the following technical solutions.

[0008] A method for assisting a business hall in providing window services, comprising:

[0009] Acquire audio stream information and video frame information when serving customers, so as to predict customer satisfaction with window services provided by auxiliary business halls, and the audio stream information or video frame information is the information used for service prediction;

[0010] The service prediction information also performs backtracking, and its method includes:

[0011] The binary stream of the service prediction information is identified and input, and the corresponding check code of the service prediction information and other related information are input synchronously, and actively input through the corresponding business hall window, and the different service prediction information input is transferred to the information table for storage.

[0012] Preferably, the method for performing backtracking using service prediction information further includes:

[0013] Extracting the service prediction information value of the corresponding service prediction information, and performing format conversion for the service prediction information values ​​of different business hall windows of different formats, and identifying the service prediction information values ​​with the same format;

[0014] The input time point is identified in the service prediction information value, and an input time point queue is formed. Then, according to the associated information in the associated information, the corresponding associated time point line is identified. According to the input time point queue and the associated time point line, abnormal associated information is identified.

[0015] Based on the abnormal association information obtained, the location of the corresponding association is identified, and the service prediction information value is used to identify whether the location of the association is compatible with the corresponding business hall window. If it is compatible, the business hall window is defined as an abnormal window and transmitted to the external terminal. If it is not compatible, no registration is performed.

[0016] A tool to assist business halls in providing window services, including:

[0017] Information input module, information table, form transformation extraction module, time point information analysis module and abnormal window determination module;

[0018] Here, the information input module, information table, form transformation extraction module, time point information analysis module and abnormal window determination module are sequentially communicated via their output interface to their input interface, and the form transformation extraction module is communicated with the input interface of the abnormal window determination module.

[0019] Preferably, the information input module corresponds to different customer service desks of business hall windows, identifies and inputs the binary stream of the service prediction information, synchronously inputs the corresponding verification code of the service prediction information and other related information, actively inputs it through the corresponding business hall window, and transmits the input different service prediction information to the information table for storage.

[0020] Preferably, when each different business hall window performs consultation for a designated customer, the related processing information of the corresponding service prediction information is input, which is convenient for performing traceability control on such service prediction information later, and the corresponding service prediction information input by different business hall windows is in different forms.

[0021] Preferably, the information table stores different service prediction information values ​​inputted by different business hall windows, and the service prediction information value includes a verification code of the service prediction information and other related information, and a storage domain is set in the information table, which can store multiple service prediction information values ​​in different forms.

[0022] Preferably, the form transformation extraction module is arranged in the remote server, and its operator can extract the service prediction information value of the corresponding service prediction information through the form transformation extraction module, and perform form transformation on the service prediction information values ​​of different business hall windows of different forms, identify the service prediction information values ​​with the same form, and transmit the identified service prediction information values ​​with the same form to the time point information analysis module.

[0023] Preferably, the method for performing the format conversion comprises:

[0024] From the service prediction information values ​​of different business hall windows extracted, different service prediction information of different forms are identified, and the length values ​​S of different service prediction information are identified. j , where j represents different forms;

[0025] First, a group of forms is selected as the main form, and the forms other than the main form are regarded as the associated forms. Through the past form transformation information, the highest and lowest transformation frequencies of the single cluster associated forms during the transformation to the main form are determined, and they are set as [Wl zd , Wl zg ], where l represents different association forms, according to the overall length value S of the main form j , determine the corresponding transformation time [Ul zd , Ul zg ];

[0026] Set the minimum and maximum time values ​​as the calibration time range for this link [U zd , U zg ];

[0027] Then define the other modes that have not been selected as the main mode in sequence, and determine the calibration time range of different links in sequence. zd , Ur zg ], where r represents different links. A basic range is set among multiple calibration time ranges to locate the main form of the link corresponding to the corresponding basic range, and it is defined as the form to be transformed. The service prediction information of another form is transformed into the form to be transformed, and the service prediction information value with the same form is identified; to identify the corresponding main form, so as to identify the calibration time range of different links.

[0028] Preferably,

[0029] Preferably, the method for determining the basic range includes:

[0030] The time range of multiple group calibrations determined [Ur zd , Ur zg ], a cluster of calibration time ranges with the lowest value among multiple calibration time minimum values ​​is set as the main range, and whether other calibration time ranges have corresponding ranges belonging to the main range is identified:

[0031] If not, the main range is taken as the base range;

[0032] If it exists, define the corresponding range belonging to the main range as a sub-range, register the median of the main range, define it as AK, take the time interval before AK in the sub-range as the first time interval, take the time interval after AK in the sub-range as the last time interval, determine the amount AC obtained by subtracting the last time interval from the first time interval, where AC = the size of the first time interval - the size of the last time interval, and determine whether AC meets the requirement: AC≥0. If it meets the requirement, define the corresponding sub-range as the range to be determined. If it does not meet the requirement, delete the sub-range.

[0033] If the desired range has one cluster, the desired range is defined as the basic range. If the desired range has multiple clusters, the highest value is set within the corresponding time ratio AC, and the desired range corresponding to the highest value is defined as the basic range.

[0034] Preferably, the time point information analysis module identifies the input time point from the service prediction information value and forms an input time point queue, then identifies the corresponding associated time point line based on the associated information in the associated information, identifies the abnormal associated information based on the input time point queue and the associated time point line, and transmits the determined abnormal associated information to the abnormal window determination module.

[0035] Preferably, the method for determining abnormal correlation information includes:

[0036] According to a plurality of input time points in the service prediction information value, a queue of input time points of corresponding service prediction information is contacted and identified in order of time points;

[0037] The associated time point line is combined to identify the associated corresponding time interval, wherein the associated corresponding time interval is the corresponding time interval between the formation time points of two adjacent associated information, and it is determined whether the adjacent time intervals in the input time point queue have the associated corresponding time interval. If so, the corresponding associated corresponding time interval is defined as an abnormal time interval, and if not, no registration is performed;

[0038] The abnormal correlation information corresponding to the abnormal time interval is transmitted to the abnormal window determination module.

[0039] Preferably, the abnormal window determination module identifies the location of the corresponding association based on the abnormal association information obtained, and identifies whether the location of the association is compatible with the corresponding business hall window through the service prediction information value. If compatible, the business hall window is defined as an abnormal window and transmitted to the external terminal. If not compatible, no registration is performed.

[0040] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0041] By judging the input related forms, and according to the specific length of different form data and the frequency of transformation between different forms, the corresponding transformation time range is determined, and then the calibration time range belonging to the corresponding link is determined according to the corresponding transformation time range determined by the corresponding link, and then the basic range is located in the calibration time range of different links to locate the final form to be transformed. The above processing method is used to determine its time range to ensure that during the data form transformation, the frequency of information form transformation is higher and the time is shorter, so as to minimize the extraction time and ensure the extraction frequency; to identify whether the service prediction information has any corresponding business hall windows that have not been input during the tracing period, and to perform centralized analysis in combination with the corresponding related time point line, the related business hall windows that have not been input can be efficiently located and displayed directly, so that the relevant control personnel can grasp the service prediction information input information in real time and facilitate the future service prediction information backtracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a partial flow chart of the method for assisting business halls in providing window services in the present invention;

[0043] Figure 2 It is a partial structural diagram of the tool for assisting the business hall in providing window service in the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely expressed in combination with the drawings in the embodiments of the present invention. The embodiments expressed in this application are only part of the embodiments of the present invention, not all of them. According to the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the protection scope of the present invention.

[0045] like Figure 1 As shown, the method of assisting a business hall in providing window services according to the present invention comprises:

[0046] Acquire audio stream information and video frame information when serving customers, so as to predict customer satisfaction with window services provided by auxiliary business halls, and the audio stream information or video frame information is the information used for service prediction;

[0047] The service prediction information also performs backtracking, and its method includes:

[0048] The binary stream of the service prediction information is identified and input, and the corresponding check code of the service prediction information and other related information are input synchronously, and actively input through the corresponding business hall window, and the different service prediction information input is transferred to the information table for storage.

[0049] In a preferred but non-limiting embodiment of the present invention, the method for performing backtracking using service prediction information further includes:

[0050] Extracting the service prediction information value of the corresponding service prediction information, and performing format conversion for the service prediction information values ​​of different business hall windows of different formats, and identifying the service prediction information values ​​with the same format;

[0051] The input time point is identified in the service prediction information value, and an input time point queue is formed. Then, according to the associated information in the associated information, the corresponding associated time point line is identified. According to the input time point queue and the associated time point line, abnormal associated information is identified.

[0052] Based on the abnormal association information obtained, the location of the corresponding association is identified, and the service prediction information value is used to identify whether the location of the association is compatible with the corresponding business hall window. If it is compatible, the business hall window is defined as an abnormal window and transmitted to the external terminal. If it is not compatible, no registration is performed.

[0053] like Figure 2 As shown, the tool for assisting a business hall in providing window services according to the present invention includes:

[0054] Information input module, information table, form transformation extraction module, time point information analysis module and abnormal window determination module;

[0055] Here, the information input module, information table, form transformation extraction module, time point information analysis module and abnormal window determination module are sequentially communicated via their output interface to their input interface, and the form transformation extraction module is communicated with the input interface of the abnormal window determination module.

[0056] In a preferred but non-restrictive implementation of the present invention, the information input module corresponds to different customer consultation desks of business hall windows, identifies and inputs the binary stream of service prediction information, synchronously inputs the corresponding verification code of the service prediction information and other related information, actively inputs it through the corresponding business hall window, and transmits the input different service prediction information to the information table for storage.

[0057] In a preferred but non-limiting embodiment of the present invention, when each different business hall window performs consultation for a designated customer, the associated processing information of the corresponding service prediction information is input, which is convenient for performing traceability control on such service prediction information later, and the corresponding service prediction information input by different business hall windows is in different forms.

[0058] In a preferred but non-restrictive embodiment of the present invention, the information table stores different service prediction information values ​​input by different business hall windows, and the service prediction information value includes a verification code of the service prediction information and other related information, which is convenient for subsequent tracing control of the service prediction information, and a large storage domain is set in the information table, which can store multiple service prediction information values ​​in different forms.

[0059] In a preferred but non-restrictive embodiment of the present invention, a form transformation extraction module is disposed in a remote server, and its operator can extract the service prediction information value of the corresponding service prediction information through the form transformation extraction module, and perform form transformation on the service prediction information values ​​of different business hall windows of different forms, identify the service prediction information values ​​of the same form, and transmit the identified service prediction information values ​​of the same form to the point-in-time information analysis module.

[0060] In a preferred but non-limiting embodiment of the present invention, the method for performing format conversion comprises:

[0061] From the service prediction information values ​​of different business hall windows extracted, different service prediction information of different forms are identified, and the length values ​​S of different service prediction information are identified. j , where j represents different forms;

[0062] First, a group of forms is selected as the main form, and the forms other than the main form are regarded as the associated forms. Through the past form transformation information, the highest and lowest transformation frequencies of the single cluster associated forms during the transformation to the main form are determined, and they are set as [Wl zd , Wl zg ], where l represents different association forms, according to the overall length value S of the main form j , determine the corresponding transformation time [Ul zd , Ul zg ];

[0063] In a preferred but non-limiting embodiment of the present invention, Just as, there are 4 clusters of forms, namely B, C, D and E, and B is initially regarded as the main form, and the highest and lowest transformation frequencies of C, D and E during the transformation to the main form B are identified, and thus defined as [Wl zd , Wl zg ], the time taken for the transformation of the formed l clusters [Ul zd , Ul zg ]middle.

[0064] Set the minimum and maximum time values ​​as the calibration time range for this link [U zd , U zg ];

[0065] Just as the transformation times of the three clusters formed when C, D and E transform towards the main form A are [1,3], [2,4] and [1,5] respectively, the minimum value is one and the maximum value is five, so the calibration time range is [1,5].

[0066] Then define the other modes that have not been selected as the main mode as the main mode, and perform the above synchronous operations to determine the calibration time range of different links in sequence. zd , Ur zg ], where r represents different links, and a basic range is set in multiple calibration time ranges to locate the main form of the link corresponding to the corresponding basic range, and define it as the form to be transformed, and transform the service prediction information of other forms into the form to be transformed, and identify the service prediction information value with the same form; here it can be: the main form of link one is B, and the main form of link two is updated to C, and the corresponding transformation frequency of B, D and E to C is identified to identify the corresponding calibration time, and then continue to select D or E as the main form in sequence, and perform the processing in sequence to identify the corresponding main form, so as to identify the calibration time range of different links.

[0067] In a preferred but non-limiting embodiment of the present invention, the method for identifying the basic range comprises:

[0068] The time range of multiple group calibrations determined [Ur zd , Ur zg ], set the lowest calibration time range from multiple lowest calibration time values ​​as the main range (that is, [1,3], [2,4], one and two are the lowest values, here one value is the lowest, then [1,3] is a cluster of main ranges), and identify whether there is a corresponding range belonging to the main range in other calibration time ranges:

[0069] If not, the main range is taken as the base range;

[0070] If it exists, define the corresponding range belonging to the main range as a sub-range, register the median of the main range, define it as AK, take the time interval before AK in the sub-range as the first time interval, take the time interval after AK in the sub-range as the last time interval, determine the amount AC obtained by subtracting the last time interval from the first time interval, where AC = the size of the first time interval - the size of the last time interval, and determine whether AC meets the requirement: AC≥0. If it meets the requirement, define the corresponding sub-range as the range to be determined. If it does not meet the requirement, delete the sub-range.

[0071] If the desired range has one cluster, the desired range is defined as the basic range. If the desired range has multiple clusters, the highest value is set within the corresponding time ratio AC, and the desired range corresponding to the highest value is defined as the basic range.

[0072] For example, if the main range is [1,5], and there is a corresponding range [2,4], then the median of the main range is three, and the first time interval of the sub-range [2,4] is one and the last time interval is also one, then the ratio AC is zero, and this sub-range is positioned as the range to be set;

[0073] If the sub-range is [1,3], its ratio AC is 2, then the target range is directly identified. If there are multiple target ranges with the same ratio, then any cluster of target ranges can be selected;

[0074] Using the above method to determine the time range is to ensure that during the information form transformation, the frequency of information transformation is higher and the time is shorter, thereby minimizing the extraction time and ensuring the extraction frequency.

[0075] The present invention mainly performs time point analysis on the extracted service prediction information value to determine whether there is a situation in which the verification code of the service prediction information is not entered at the corresponding business hall window.

[0076] In a preferred but non-restrictive embodiment of the present invention, the time point information analysis module identifies the input time point from the service prediction information value and forms an input time point queue, then identifies the corresponding associated time point line based on the associated information in the associated information, identifies the abnormal associated information based on the input time point queue and the associated time point line, and transmits the determined abnormal associated information to the abnormal window determination module.

[0077] In a preferred but non-limiting embodiment of the present invention, the method for determining abnormal correlation information includes:

[0078] According to a plurality of input time points in the service prediction information value, a queue of input time points of corresponding service prediction information is contacted and identified in order of time points;

[0079] The associated time point line is used to identify the associated corresponding time interval, where the associated corresponding time interval is the corresponding time interval between the formation time points of two adjacent associated information. It is determined whether the adjacent time intervals in the input time point queue have the associated corresponding time interval. If so, the corresponding associated corresponding time interval is defined as an abnormal time interval. If not, no registration is performed. For example, each input time point should belong to the associated corresponding time interval. If a pair of input time points still have the corresponding associated corresponding time interval, it indicates that after a time point, the input of the service prediction information is not performed at the corresponding time point, resulting in information loss, which is not conducive to the future service prediction information backtracking;

[0080] The abnormal correlation information corresponding to the abnormal time interval is transmitted to the abnormal window determination module.

[0081] In a preferred but non-restrictive implementation of the present invention, the abnormal window determination module identifies the location of the corresponding association based on the abnormal association information obtained, and identifies whether the location of the association is compatible with the corresponding business hall window through the service prediction information value. If compatible, the business hall window is defined as an abnormal window and transmitted to the external terminal. If not compatible, no registration is performed.

[0082] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0083] By judging the input related forms, and according to the specific length of different form data and the frequency of transformation between different forms, the corresponding transformation time range is determined, and then the calibration time range belonging to the corresponding link is determined according to the corresponding transformation time range determined by the corresponding link, and then the basic range is located in the calibration time range of different links to locate the final form to be transformed. The above processing method is used to determine its time range to ensure that during the data form transformation, the frequency of information form transformation is higher and the time is shorter, so as to minimize the extraction time and ensure the extraction frequency; to identify whether the service prediction information has any corresponding business hall windows that have not been input during the tracing period, and to perform centralized analysis in combination with the corresponding related time point line, the related business hall windows that have not been input can be efficiently located and displayed directly, so that the relevant control personnel can grasp the service prediction information input information in real time and facilitate the future service prediction information backtracking.

[0084] The present disclosure can be a system, method and / or computer program product. The computer program product can include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0085] A computer-readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium can be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the above. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (such as, a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0086] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0087] The computer program instructions for performing the operations of the present disclosure can be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine corresponding instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as "C" language or similar programming languages. The computer readable program instructions can be executed entirely on the processing time computer, partially on the processing time computer, as a separate software package, partially on the processing time computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the processing time computer through any set of networks, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (such as through the Internet using an Internet service provider). In some embodiments, the electronic circuit is personalized by using the state information of the computer-readable program instructions, such as a programmable logic circuit, a field programmable gate array (FPGA) or a programmable logic array (PLA), and the electronic circuit can execute the computer-readable program instructions to implement various aspects of the present disclosure.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for assisting a business hall in providing window services, characterized in that: include: Acquire audio stream information and video frame information when serving customers, so as to predict customer satisfaction with window services provided by auxiliary business halls, and the audio stream information or video frame information is the information used for service prediction; The service prediction information also performs backtracking, and its method includes: The binary stream of the service prediction information is identified and input, and the corresponding check code of the service prediction information and other related information are input synchronously, and actively input through the corresponding business hall window, and the different service prediction information input is transferred to the information table for storage.

2. The method for assisting a business hall in providing window services according to claim 1, characterized in that: The method for performing backtracking using service prediction information also includes: Extracting the service prediction information value of the corresponding service prediction information, and performing format conversion for the service prediction information values ​​of different business hall windows of different formats, and identifying the service prediction information values ​​with the same format; The input time point is identified in the service prediction information value, and an input time point queue is formed. Then, according to the associated information in the associated information, the corresponding associated time point line is identified. According to the input time point queue and the associated time point line, abnormal associated information is identified. Based on the abnormal association information obtained, the location of the corresponding association is identified, and the service prediction information value is used to identify whether the location of the association is compatible with the corresponding business hall window. If it is compatible, the business hall window is defined as an abnormal window and transmitted to the external terminal. If it is not compatible, no registration is performed.

3. A tool to assist business halls in providing window services, characterized in that: include: Information input module, information table, form transformation extraction module, time point information analysis module and abnormal window determination module; Here, the information input module, information table, form transformation extraction module, time point information analysis module and abnormal window determination module are sequentially communicated via their output interface to their input interface, and the form transformation extraction module is communicated with the input interface of the abnormal window determination module.

4. The tool for assisting business halls in providing window services according to claim 3, characterized in that: The information input module corresponds to different customer service consultation areas of the business hall windows, identifies and inputs the binary stream of the service prediction information, synchronously inputs the check code of the corresponding service prediction information and other related information, automatically inputs it through the corresponding business hall windows, and transmits the input different service prediction information to the information table for storage; When different business hall windows provide consultation for designated customers, they input relevant processing information of corresponding service forecast information, so as to perform traceability control on such service forecast information later, and the forms of corresponding service forecast information input by different business hall windows are different.

5. The tool for assisting business halls in providing window services according to claim 4, characterized in that: The information table is used to store different service prediction information values ​​inputted from different business hall windows, and the service prediction information values ​​include a verification code of the service prediction information and other related information. The information table is provided with a storage domain, which can store multiple service prediction information values ​​in different forms.

6. The tool for assisting business halls in providing window services according to claim 5, characterized in that: The form transformation extraction module is arranged in the remote server, and its operator can extract the service prediction information value of the corresponding service prediction information through the form transformation extraction module, and perform form transformation on the service prediction information values ​​of different business hall windows of different forms, identify the service prediction information values ​​of the same form, and transmit the identified service prediction information values ​​of the same form to the point-in-time information analysis module.

7. The tool for assisting business halls in providing window services according to claim 6, characterized in that: The method for performing the form transformation comprises: From the service prediction information values ​​of different business hall windows extracted, different service prediction information of different forms are identified, and the length values ​​S of different service prediction information are identified. j , where j represents different forms; First, a group of forms is selected as the main form, and the forms other than the main form are regarded as the associated forms. Through the past form transformation information, the highest and lowest transformation frequencies of the single cluster associated forms during the transformation to the main form are determined, and they are set as [Wl zd , Wl zg ], where l represents different association forms, according to the overall length value S of the main form j , determine the corresponding transformation time [Ul zd , Ul zg ]; Set the minimum and maximum time values ​​as the calibration time range for this link [U zd , U zg ]; Then define the other modes that have not been selected as the main mode in sequence, and determine the calibration time range of different links in sequence. zd , Ur zg ], where r represents different links, a basic range is set in a plurality of calibration time ranges, so as to locate the main form of the link corresponding to the corresponding basic range, and define it as the form to be transformed, transform the service prediction information of another form into the form to be transformed, and identify the service prediction information value with the same form; to identify the corresponding main form, so as to identify the calibration time range of different links; 8. The tool for assisting business halls in providing window services according to claim 7, characterized in that: Methods for determining the basic scope include: The time range of multiple group calibrations determined [Ur zd , Ur zg ], a cluster of calibration time ranges with the lowest value among multiple calibration time minimum values ​​is set as the main range, and whether other calibration time ranges have corresponding ranges belonging to the main range is identified: If not, the main range is taken as the base range; If it exists, define the corresponding range belonging to the main range as a sub-range, register the median of the main range, define it as AK, take the time interval before AK in the sub-range as the first time interval, take the time interval after AK in the sub-range as the last time interval, determine the amount AC obtained by subtracting the last time interval from the first time interval, where AC = the size of the first time interval - the size of the last time interval, and determine whether AC meets the requirement: AC≥0. If it meets the requirement, define the corresponding sub-range as the range to be determined. If it does not meet the requirement, delete the sub-range. If the desired range has one cluster, the desired range is defined as the basic range. If the desired range has multiple clusters, the highest value is set within the corresponding time ratio AC, and the desired range corresponding to the highest value is defined as the basic range.

9. The tool for assisting business halls in providing window services according to claim 8, characterized in that: The time point information analysis module determines the input time point from the service prediction information value and forms an input time point queue, then determines the corresponding associated time point line according to the associated information in the associated information, determines abnormal associated information according to the input time point queue and the associated time point line, and transmits the determined abnormal associated information to the abnormal window determination module; The method for determining abnormal correlation information includes: According to a plurality of input time points in the service prediction information value, a queue of input time points of corresponding service prediction information is contacted and identified in order of time points; The associated time point line is combined to identify the associated corresponding time interval, wherein the associated corresponding time interval is the corresponding time interval between the formation time points of two adjacent associated information, and it is determined whether the adjacent time intervals in the input time point queue have the associated corresponding time interval. If so, the corresponding associated corresponding time interval is defined as an abnormal time interval, and if not, no registration is performed; The abnormal correlation information corresponding to the abnormal time interval is transmitted to the abnormal window determination module.

10. The tool for assisting business halls in providing window services according to claim 9, characterized in that: The abnormal window determination module identifies the location of the corresponding association based on the abnormal association information obtained, and uses the service prediction information value to determine whether the location of the association is compatible with the corresponding business hall window. If compatible, the business hall window is defined as an abnormal window and transmitted to the external terminal. If not compatible, no registration is performed.

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