WO2018040067A1 - 用户指导系统及方法 - Google Patents

用户指导系统及方法 Download PDF

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Publication number
WO2018040067A1
WO2018040067A1 PCT/CN2016/097942 CN2016097942W WO2018040067A1 WO 2018040067 A1 WO2018040067 A1 WO 2018040067A1 CN 2016097942 W CN2016097942 W CN 2016097942W WO 2018040067 A1 WO2018040067 A1 WO 2018040067A1
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WIPO (PCT)
Prior art keywords
user
user path
knowledge map
path
knowledge
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PCT/CN2016/097942
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English (en)
French (fr)
Inventor
张海宏
陶志伟
Original Assignee
浙江核新同花顺网络信息股份有限公司
核新金融信息服务公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by 浙江核新同花顺网络信息股份有限公司, 核新金融信息服务公司 filed Critical 浙江核新同花顺网络信息股份有限公司
Priority to PCT/CN2016/097942 priority Critical patent/WO2018040067A1/zh
Priority to CN201680088918.3A priority patent/CN109690581B/zh
Publication of WO2018040067A1 publication Critical patent/WO2018040067A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor

Definitions

  • the present application relates to a user guidance system and method, and in particular, generates a teaching material through machine learning based on the acquired user path, thereby providing a teaching material to the user.
  • the problem that this application wants to solve is how to introduce the knowledge and decision logic of users who use financial management software well to those who do not use well.
  • This problem can be decomposed into: (1) how to obtain the knowledge and decision logic of a well-used user; (2) how to process the acquired knowledge and decision logic to form a textbook; and (3) how to use a user who is not well used
  • the ability to use is taught in accordance with the aptitude and guided in a way that is more acceptable to the user.
  • the knowledge and decision-making logic of a well-used user is implied in the user's operation of the software or system, but if only the guidance of the software operation is provided, the user cannot understand the knowledge, investment thinking and investment logic behind the operation. Therefore, it needs to be solved from good use.
  • the acquired knowledge and investment logic may simply imitate the operation of the well-used user, but not the knowledge and investment logic.
  • the same knowledge and investment logic does not apply to different users and actual scenarios. Therefore, the acquired knowledge and investment logic needs to be processed to make it a user-acceptable textbook.
  • the present application relates to a user guidance system.
  • the system includes: a processor; a computer readable storage medium, the computer storage medium carrying instructions when executed by the processor The instructions cause the processor to: acquire a first user path, the user path comprising a flow consisting of operations of the user on the communication terminal for two or more nodes; based at least in part on the first user The path generates a teaching material that includes an optimized user path or at least one knowledge point; the teaching material is provided to the user.
  • the method includes: acquiring a first user path, where the user path includes a user's operation on two or more nodes on the communication terminal. And generating a teaching material based at least in part on the first user path, the teaching material including an optimized user path or at least one knowledge point; providing the teaching material to a user.
  • Another aspect of the present application is directed to a computer readable storage medium, according to one embodiment, the computer storage medium carrying instructions that, when executed by the processor, cause the processor to execute: acquire a user path comprising a flow of operations by a user on two or more nodes on the communication terminal; generating a textbook based at least in part on the first user path, the textbook including an optimized user path Or at least one knowledge point; providing the textbook to the user.
  • FIG. 1 is a schematic diagram of an example system configuration of a user guidance system, in accordance with some embodiments of the present application.
  • FIG. 2 is a schematic diagram showing an example structure of a user guidance system according to some embodiments of the present application.
  • FIG. 3 is a schematic block diagram of an example of a user guidance system shown in accordance with some embodiments of the present application.
  • FIG. 4 is a schematic diagram showing an example structure of a data processing module according to some embodiments of the present application.
  • Figure 5 is a diagram showing user guidance as shown in some embodiments of the present application. Example flow chart
  • FIG. 6 is an example flow diagram of generating a user path library and a knowledge map library, shown in some embodiments of the present application;
  • FIG. 7 is an example flow diagram of a method of generating a teaching material, shown in accordance with some embodiments of the present application.
  • FIG. 8 is an example flow diagram of a method of generating a teaching material, shown in accordance with some embodiments of the present application.
  • FIG. 9 is an example flow diagram of a method of dividing user ratings, in accordance with some embodiments of the present application.
  • the user guidance method described in this specification refers to a method of providing a teaching material to a user by acquiring a user path and generating a teaching material through machine learning based on the acquired user path.
  • the present application is directed to a user guidance system.
  • the user guidance system can include a processor; a computer readable storage medium carrying instructions that, when executed by the processor, cause the processor to execute: acquire a first user a path, the user path comprising a process consisting of operations of two or more nodes on the communication terminal by the user; at least part of the basis Generating a teaching material to the first user path, the teaching material including an optimized user path or at least one knowledge point; providing the teaching material to a user.
  • Different embodiments of the present application are applicable to a variety of fields including, but not limited to, investments in finance and derivatives (including but not limited to stocks, bonds, gold, paper gold, silver, foreign exchange, precious metals, futures, money funds, etc.), Technology (including but not limited to mathematics, physics, chemistry and chemical engineering, biology and bioengineering, electrical engineering, communication systems, internet, internet of things, etc.), politics (including but not limited to politicians, political events, countries), news ( From the regional perspective, including but not limited to regional news, domestic news, international news; from the main body of the news, including but not limited to political news, sports news, science and technology news, economic news, life news, weather news, etc.).
  • the form of the teaching material may also include a short message, a QQ voice, a WeChat voice, and a system push information. Wait. Replacements or modifications or variations similar to this are still within the scope of the present application.
  • the drawings are briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can apply the present application to other similarities according to these drawings without any creative work. scene. Unless otherwise apparent from the language environment or otherwise stated, the same reference numerals in the drawings represent the same structure and operation.
  • Figure 1 is a schematic diagram of an example system configuration of a user guidance system.
  • the example system configuration 100 can include, but is not limited to, one or more user guidance systems 110, one or more networks 120, and one or more information sources 130.
  • the user guidance system 110 can be used to perform data processing on the acquired information and generate teaching materials to guide the user.
  • the user guidance system 110 can be a server or a server group. Server groups can be centralized, such as data centers. Server groups can also be distributed, such as a distributed system.
  • User guidance system 110 can be local or remote.
  • Network 120 can provide a conduit for information exchange.
  • Network 120 can be a single network or a combination of multiple networks.
  • Network 120 may include, but is not limited to, one or more combinations of a local area network, a wide area network, a public network, a private network, a wireless local area network, a virtual network, a metropolitan area network, a public switched telephone network, and the like.
  • Network 120 may include a variety of network access points, such as wired or wireless access points, base stations, or network switching points, through which the data sources connect to network 120 and receive and transmit information over the network.
  • Information source 130 can provide and obtain various information.
  • Information source 130 may include, but is not limited to, a server, a communication terminal.
  • the server (part of the information source 130) may be a web server, a file server, a database server, or an FTP service. , application server, proxy server, etc., or any combination of the above.
  • the communication terminal (part of the information source 130) may be a mobile phone, a personal computer, a wearable device, a tablet computer, a smart TV, or the like, or any combination of the above communication terminals.
  • Information source 130 may send or/and collect information through network 120 to user guidance system 110, which may be information entered by the user or may be information provided by other databases or sources of information.
  • User guidance system 110 may include, but is not limited to, one or more processors 210, one or more input output devices 220, one or more memories 230, one or more network interfaces 240. Some or all of the above devices may be connected to the network 120. The above devices may be centralized or distributed. One or more of the above devices may be local or remote.
  • the processor 210 can control the operation of the user guidance system 110 by computer program instructions. These computer program instructions can be stored on one or more memories 230.
  • the one or more processors 210 may include, but are not limited to, a microcontroller, a simplified instruction system computer (RISC), an application specific integrated circuit (ASIC), an application specific instruction set processor (ASIP), a central processing unit (CPU), graphics Processor (GPU), physical processor (PPU), microprocessor unit, digital signal processor (DSP), field programmable gate array (FPGA), or other circuit or processor capable of executing computer program instructions or a combination thereof .
  • RISC simplified instruction system computer
  • ASIC application specific integrated circuit
  • ASIP application specific instruction set processor
  • CPU central processing unit
  • GPU graphics Processor
  • PPU physical processor
  • DSP digital signal processor
  • FPGA field programmable gate array
  • Input output device 220 may enable user interaction with user guidance system 110.
  • the input and output device 220 can be from the network via the network 120
  • the source 130 collects information.
  • input and output device 220 can transmit information to information source 130 over network 120.
  • the manner in which the input and output device 220 sends information to the user guidance system 110 may include, but is not limited to, one or more of keyboard input, touch screen input, mouse input, camera, scanner, tablet input, voice input, and the like. combination.
  • the way in which the input and output device 220 outputs information may include, but is not limited to, one or more combinations of display display, printer printing, speaker playback, and the like.
  • the form of the output may include, but is not limited to, one or more combinations of numbers, characters, pictures, audio, and video.
  • Memory 230 can be used to store various information, such as computer program instructions and data that control user guidance system 110, and the like.
  • the one or more memories 230 may be devices that store information by means of electrical energy, such as various memories, random access memory (RAM), read only memory (ROM), and the like.
  • the random access memory includes but is not limited to a decimal counter tube, a selection tube, a delay line memory, a Williams tube, a dynamic random access memory (DRAM), a static random access memory (SRAM), a thyristor random access memory (T-RAM), and a zero capacitor.
  • DRAM dynamic random access memory
  • SRAM static random access memory
  • T-RAM thyristor random access memory
  • Z-RAM random access memory
  • Read-only memory includes, but is not limited to, bubble memory, magnetic button line memory, thin film memory, magnetic plate line memory, magnetic core memory, drum memory, optical disk drive, hard disk, magnetic tape, early non-volatile memory (NVRAM), phase change Memory, magnetoresistive random storage memory, ferroelectric random access memory, nonvolatile SRAM, flash memory, electronic erasable rewritable read only memory, erasable programmable read only memory, programmable read only memory, shielded Heap read memory, floating connection gate random access memory, nano random access memory, track memory, variable power A combination of one or more of a resistive memory, a programmable metallization unit, and the like.
  • the one or more memories 230 may be devices that store information using magnetic energy, such as a hard disk, a floppy disk, a magnetic tape, a magnetic core memory, a magnetic bubble memory, a USB flash drive, a flash memory, or the like.
  • the one or more memories 230 described above may be devices that optically store information, such as CDs or DVDs.
  • the one or more memories 230 may be devices that store information using magneto-optical means, such as magneto-optical disks.
  • the access mode of the one or more memories 230 may be one or more combinations of random storage, serial access storage, read-only storage, and the like.
  • the one or more memories 230 may be non-permanent memory or permanent memory.
  • the memory 230 mentioned above is a list of examples, and the memory 230 that the user guidance system 110 can use is not limited thereto.
  • the one or more memories 230 may be local, remote, or on a cloud server.
  • Network interface 240 may enable communication between some or all of the devices of user guidance system 110 and information source 130 via network 120. In some embodiments, network interface 240 may enable communication between some or all of the devices of user guidance system 110 via network 120.
  • Network interface 240 can be a wired network interface or a wireless network interface.
  • Network interface 240 may include, but is not limited to, a metal cable, an optical fiber, a hybrid cable, a connection circuit, or other wired network interface, or a combination of one or more.
  • Network interface 240 may include, but is not limited to, a wireless local area network (WLAN) interface, a local area network (LAN) interface, a wide area network (WAN) interface, a Bluetooth connection, a wireless sensor network (ZigBee) interface, a near field communication (NFC) interface.
  • WLAN wireless local area network
  • LAN local area network
  • WAN wide area network
  • Bluetooth a wireless sensor network
  • ZigBee wireless sensor network
  • NFC near field communication
  • FIG. 3 Shown in FIG. 3 is a schematic block diagram of an example of a user guidance system 110.
  • User guidance system 110 may include, but is not limited to, one or more acquisition modules 310, one or more databases 320, one or more data processing modules 330, one or more user guidance modules 340.
  • Module in this application refers to logic or a set of software instructions stored in hardware, firmware.
  • a “module” as referred to herein can be executed by software and/or hardware modules, or can be stored in any computer-readable non-transitory medium or other storage device.
  • a software module can be compiled and linked into an executable program. The software modules herein can respond to information conveyed by themselves or other modules and/or can respond when certain events or interruptions are detected.
  • a software module arranged to perform operations on a computing device may be provided on a computer readable medium (e.g., memory 230), which may be an optical disc, a digital optical disc, a flash drive , disk or any other kind of tangible medium; software modules can also be obtained through the digital download mode (the digital download here also includes the data stored in the compressed package or the installation package, which needs to be decompressed or decoded before execution).
  • the software code herein may be stored, in part or in whole, in a storage device of a computing device that performs the operations and applied to the operation of the computing device.
  • Software instructions can be embedded in firmware, such as Erasable Programmable Read Only Memory (EPROM).
  • EPROM Erasable Programmable Read Only Memory
  • a hardware module can include logic elements that are connected together, such as a gate, a flip-flop, and/or include a programmable unit, such as a programmable gate array or processor.
  • the functions of the modules or computing devices described herein are preferably implemented as software modules, but may also be represented in hardware or firmware.
  • the module mentioned here is a logic module, not subject to its specific object. The form or memory limit.
  • a module can be combined with other modules or separated into a series of sub-modules.
  • the above modules may be connected to the network 120.
  • the above modules can be centralized or distributed.
  • One or more of the above modules may be local or remote.
  • the functionality of one or more of the above modules may be implemented by one or more processors 210.
  • the functions of one or more of the above modules may also be performed by one or more processors 210, one or more input and output devices 220, one or more memories 230, one or more network interfaces 240, and the like. A combination of one or more of them is implemented.
  • the acquisition module 310 can be used to obtain the required information in a variety of ways.
  • the manner in which the information is obtained may be direct (eg, directly from the one or more information sources 130 via the network 120) or indirectly (eg, via the database 320, the data processing module 330, or the user guidance module 340).
  • the information that the acquisition module 310 can obtain includes, but is not limited to, one or more combinations of user paths, user performance, knowledge maps, and the like.
  • the term "user path" may be used in this application to refer to the operational flow of a user's operation at one or more nodes, where at least one node is a node on the user's communication terminal.
  • User paths can include clicking through knowledge points and conducting trading operations.
  • the user path may be an operational flow in which the user clicks and browses the K-line, news, and the like provided by the user guidance system 110 and then proceeds.
  • the user path may be an operational flow in which the user directly conducts the transaction.
  • node in this application may refer to a user's communication terminal or other device that can be provided with User interface or component of the interface.
  • the node may be a combination of one or more of K-line, moving average, company announcements, research reports, news, performance changes, etc. provided by user guidance system 110.
  • the node may be a combination of one or more of a button, a text box, a password box, a radio button, a check box, a drop-down selection box, and the like corresponding to the selection target, investment, sell cash, and the like.
  • Process results may include, but are not limited to, selection of targets (ie, determining which stocks should focus on investing), analysis of current trending environments (ie, determining that the current trending environment is inappropriate for investment), and timing of investment (ie, investing now) It is still a combination of one or more types, such as the judgment that the price is backward and the profit is sold.
  • the final result may include, but is not limited to, a combination of one or more of the amount of revenue for a single transaction, the total amount of revenue for each transaction day, and the like.
  • Database 320 can be used to store data or information, and/or generate one or more sub-databases and the like.
  • one or more sub-databases may include a user path library and a knowledge map library.
  • Database 320 may include, but is not limited to, one or more combinations of hierarchical databases, networked databases, and relational databases.
  • the term "knowledge map” may refer to the range of knowledge that the user understands in this application.
  • the knowledge map may refer to the statistical integration of the user prior to the transaction (short term) and the knowledge points that have been in contact for a long time.
  • the knowledge map may refer to one or more knowledge points (K lines, moving averages, company information, such as announcements, research reports, news, performance changes, etc.) obtained from the user guidance system 110 since the user registered the account. a collection of combinations).
  • Database 320 can communicate or exchange information with information source 130.
  • Database 320 can receive information from information source 130 and store it in database 320. Based on the received instructions, the information stored in database 320 can be extracted and passed to information source 130.
  • the instructions may be directly from the information source 130, or may be from other modules, such as the acquisition module 310, the data processing module 330, and/or the user guidance module 340.
  • Database 320 can communicate or exchange information with acquisition module 310.
  • the database 320 can receive the information acquired by the acquisition module 310, such as the user path, user performance, etc., and store it in the database 320. Based on the received instructions, the information stored in database 320 can be extracted and passed to acquisition module 310.
  • the instructions may be directly from the acquisition module 310, or may be from other modules, such as the data processing module 330 and/or the user guidance module 340.
  • Database 320 can communicate or exchange information with data processing module 330.
  • Database 320 can receive information from data processing module 330 and store it in database 320. Based on the received instructions, the information stored in database 320 can be extracted and passed to data processing module 330.
  • the instruction may be directly from the data processing module 330, or may be from other modules, such as the obtaining module 310 and the user guiding module 340.
  • Database 320 can communicate or exchange information with user guidance module 340.
  • Database 320 can receive information from user guidance module 340 and store it in database 320. Based on the received instructions, the information stored in database 320 can be extracted and passed to user guidance module 340.
  • the instructions may be directly from the user guidance module 340, or may be from other modules, such as the acquisition module 310 and the data processing module 330.
  • the database 320 is sent to other modules of the user guidance system 110 (eg, acquisition mode)
  • the information of block 310, data processing module 330, and/or user coaching module 340) may be information obtained directly from information source 130 or may be data processed information.
  • the data processed information may be information stored in the database 320 after being processed by the data processing module 330.
  • the information transfer between the database 320 and other modules may be wired or wireless, and may be direct or indirect, and may be performed simultaneously or sequentially, and may be periodic or aperiodic. Wait.
  • the data processing module 330 can be configured to perform data processing on the acquired information and generate a teaching material.
  • the acquired information may include, but is not limited to, one or more combinations of user paths, knowledge maps, user performance, and the like.
  • Sources of the acquired information may include, but are not limited to, an acquisition module 310, a database 320, and the like.
  • the acquisition module 310 can obtain the user's user path and/or from the user's communication terminal (a part of the information source 130, such as a mobile phone, a personal computer, a wearable device, a tablet, a smart TV, etc.) directly through the network 120. Or user performance.
  • data processing module 330 can send a request and receive a user path sent by acquisition module 310.
  • the obtaining module 310 may transmit the information stored in the obtaining module 310 to the data processing module 330 after receiving the request sent from the data processing module 330.
  • textbook may refer to a partial or complete optimized user path or at least one knowledge point generated by manual or machine learning in this application.
  • a textbook may refer to a collection of knowledge points generated by manual or machine learning.
  • the textbook may refer to a user path in a real transaction case.
  • the textbook may refer to a new use generated after learning through machine learning. User path.
  • the data processing module 330 can communicate bidirectionally with the acquisition module 310.
  • the data processing module 330 can process the information transmitted by the acquisition module 310, which can include, but is not limited to, one or more combinations of selecting a user path, generating a knowledge map, comparing and generating a textbook, and the like.
  • the data processing module 330 may send information to the obtaining module 310, where the information may include, but is not limited to, data processed information and control information, which may include, but is not limited to, information collection mode control information and information collection time control information. , control information of the source of information collection, etc.
  • Data processing module 330 can communicate bi-directionally with database 320.
  • the data processing module 330 can process the information transmitted by the database 320, which can include, but is not limited to, one or more combinations of selecting a user path, generating a knowledge map, comparing and generating a textbook, and the like.
  • the data processing module 330 may transmit the data processed information to the database 320 for storage, or may send the request information to the database 320 and receive the information transmitted by the database 320.
  • Data processing module 330 can communicate bi-directionally with user guidance module 340.
  • the data processing module 330 may transmit the data processed information to the user guidance module 340, and may also receive the information sent by the user guidance module 340.
  • User guidance module 340 can be used to provide teaching materials to the user.
  • the user coaching module 340 can send a request to the data processing module 330 and receive the textbook sent by the data processing module 330.
  • the data processing module 330 may transmit the teaching materials stored in the data processing module 330 to the user guidance module 340.
  • the teaching materials provided to the user by the user guidance module 340 may include, but are not limited to, software operations of the user guidance system 110, expanding knowledge. One or more combinations of map recommendations, financial knowledge such as stock futures, and investment logic.
  • Ways to provide teaching materials may include, but are not limited to, system pop-ups, system notifications, system demonstrations, software push information, SMS, MMS, QQ messages, WeChat voice, video teaching of video sites, customer service phone guidance, and other applications for human-computer communication or The way people communicate with others and is easily accepted by users.
  • the degree of guidance may be based on the user's ability to use the user guidance system 110, from shallow to deep, in a manner that is more acceptable to the user.
  • the user guidance system 110 can rank according to the user's ability to use the user guidance system 110 and then match the corresponding guidance based on the level. For example, for a newly registered user, the user guidance system 110 divides it into a primary user after being evaluated, and matches the knowledge point of the primary user (such as a K-line, announcement, etc. before the investment); for a skilled user who has used for many years. The user guidance system 110 divides it into advanced users and matches the knowledge points of advanced users (such as the trend theory behind, wave theory).
  • the user guidance module 340 can send a request to the acquisition module 310, and the acquisition module 310 can access the database 320 according to the request to obtain the required information. After the required information is obtained, the acquisition module 310 transmits the information to the user guidance module 340. In some embodiments, the acquisition module 310 may also transmit the information stored in the acquisition module 310 to the user guidance module 340 after receiving the request sent from the user guidance module 340. In some embodiments, the user coaching module 340 can directly access the database 320 and send a request to the database 320 to obtain the required information, which can be transmitted to the user coaching module 340. In some embodiments, database 320 can be The information is sent to the user guidance module 340 without receiving the request.
  • the user guidance module 340 can send a request to the data processing module 330, and the data processing module 330 can access the database 320 according to the request to obtain the required information. After the required information is obtained, the data processing module 330 transmits the information to the user guidance module 340. In some embodiments, the data processing module 330 may also transmit the information stored in the data processing module 330 to the user guidance module 340 after receiving the request from the user guidance module 340.
  • the input information received by the user guidance module 340 may include, but is not limited to, a set of knowledge points generated by manual finishing or machine learning, a user path in some real transaction cases, a new user generated by manual finishing or machine learning. Path, etc.
  • the modules may be arbitrarily combined without any deviation from the principle, or the subsystems may be connected with other modules.
  • the obtaining module 310, the database 320, the data processing module 330, and the user guiding module 340 may be different modules embodied in one system, or may be integrated into one module to implement the functions of two or more modules described above, similar. Modifications are still within the scope of the claims of the present application.
  • FIG. 4 is a schematic diagram showing an example structure of the data processing module 330.
  • Data processing module 330 may include, but is not limited to, one or more selection units 410, one or more knowledge map generation units 420, one or more comparison units 430, and one Or a plurality of textbook units 440. Some or all of the above units may be connected to the network 120. The above units may be centralized or distributed. One or more of the above units may be local or remote. In some embodiments, the functionality of one or more of the above-described units may be implemented by one or more processors 210.
  • the functions of one or more of the above units may also be performed by one or more processors 210, one or more input and output devices 220, one or more memories 230, one or more network interfaces 240, and the like. A combination of one or more of them is implemented.
  • selection unit 410 can perform a selection operation on a user path library and/or a knowledge map library.
  • the selection unit 410 can perform a selection operation (such as the acquisition module 310, the database 320) by accessing other modules in the user guidance system 110.
  • the selection unit 410 can select the information stored in the acquisition module 310 by the access acquisition module 310.
  • selection unit 410 can select information stored in database 320 by accessing database 320.
  • the selection indicator used by the selection unit 410 to select the user path may include, but is not limited to, the similarity of the user path, the number of nodes of the user path (user path length), and the user performance corresponding to the user path (eg, One or more combinations of the amount of revenue of the pen transaction).
  • selection unit 410 may select one or more user paths that are fuzzy matched to a certain user path (eg, a similarity between 70% and 80%).
  • selection unit 410 can select one or more user paths that are exactly similar to a user path (eg, a similarity greater than 90%).
  • selection unit 410 can select the exact phase of a user's path. It appears that (eg, the similarity is greater than 90%) and the user performs one or more user paths that are better than the user path.
  • the selection indicator used by the selection unit 410 to select the knowledge map may include, but is not limited to, the similarity of the knowledge map, the knowledge point type of the knowledge map, a certain class or a certain kind provided by the user to the user guidance system 110. The number of clicks of several types of knowledge points (K line, moving average, company information, etc.). In some embodiments, selection unit 410 can select one or more knowledge maps that are exactly similar to a knowledge map (eg, a similarity greater than 90%).
  • the selection unit 410 can use a ranking algorithm when selecting a knowledge map.
  • the sorting algorithm that can be used by the selection unit 410 includes, but is not limited to, bubble sorting, cocktail sorting, insert sorting, bucket sorting, count sorting, merge sorting, in-place merge sorting, binary sorting tree sorting, pigeon nesting, cardinal sorting, Gnome.
  • the knowledge map generation unit 420 can be configured to generate a knowledge map according to the user path.
  • the source of the user path may include, but is not limited to, one or more combinations of other modules (eg, acquisition module 310, database 320) or other units of the data processing module (eg, selection unit 410) in the user guidance system 110.
  • the knowledge map generation unit 420 can send a request to the acquisition module 310, and the acquisition module 310 can transmit the user path to the knowledge map generation unit 420 according to the request.
  • the acquisition module 310 can send the user path to the knowledge map generation unit 420 without receiving the request.
  • the indicators used by the knowledge map generation unit 420 to generate the knowledge map may include, but are not limited to, the user's knowledge background, surrounding industry distribution, promotion status, risk education status, K-line, moving average, company announcement, research One or more combinations of newspapers, news, performance changes, etc.
  • the representation form of the knowledge map generated by the knowledge map generation unit 420 may be a combination of one or more of a multidimensional radar map, a knowledge point map, a multidimensional vector, a column chart, a pie chart, a table, and the like.
  • Comparison unit 430 can be used to compare two or more knowledge maps to arrive at a comparison result.
  • the term "comparison result" may refer to a difference between two or more knowledge maps obtained by comparison in this application.
  • the comparison result may refer to different degrees of acquisition (eg, acquisition amount, acquisition frequency, etc.) of different knowledge points or the same knowledge points between two or more knowledge maps obtained by the comparison algorithm.
  • the source of the knowledge map may include, but is not limited to, one or more combinations of other modules in the user guidance system 110 (eg, database 320) or other units of data processing module 330 (eg, knowledge map generation unit 420).
  • the comparison unit 430 can send a request to the knowledge map generation unit 420, and the knowledge map generation unit 420 can transmit the knowledge map to the comparison unit 430 according to the request. In some embodiments, the knowledge map generation unit 420 can transmit the knowledge map to the comparison unit 430 without receiving the request.
  • the indicators used by the comparing unit 430 to compare two or more knowledge maps may include, but are not limited to, the user's knowledge background, surrounding industry distribution, promotion status, risk education status, K-line, moving average, company One or more combinations of announcements, research reports, news, performance changes, etc.
  • Textbook unit 440 can be used to generate textbooks.
  • the source of the generated teaching material may include, but is not limited to, other modules in the user guidance system 110 (such as the acquisition module 310 and/or the database 320) or other units of the data processing module (such as the selection unit 410 and/or the comparison unit 430). Or a combination of multiples.
  • textbook unit 440 can send a request to selection unit 410, which can transmit the material to textbook unit 440 upon request.
  • the selection unit 410 can transmit the material for generating the teaching material to the teaching material unit 440 without receiving the request.
  • the textbook unit 440 can generate a textbook based on the selected one or more user paths or comparison results of the two knowledge maps.
  • the content of the textbook may include, but is not limited to, a collection of knowledge points, a user path in a real transaction case, a new user path generated through machine learning, or the like.
  • Textbooks can be generated by manual or machine learning.
  • Algorithms for generating teaching materials through machine learning may include, but are not limited to, classification decision tree algorithm, K-average algorithm, support vector machine, Apriori algorithm, maximum expectation (EM) algorithm, PageRank, AdaBoost iterative algorithm, K nearest neighbor classification algorithm, Naosu Bay A combination of one or more of a Yesi model, a classification, and a regression tree.
  • the data processing module is merely a specific example and should not be considered as the only feasible implementation.
  • various modifications and changes may be made to the content of the required information without departing from the principle, but these corrections And changes are still within the scope of the above description.
  • the selection unit 410, the knowledge map generation unit 420, the comparison unit 430, and/or the teaching material unit 440 may be embodied in one mode.
  • Different units in the block may also be integrated into one unit to implement the functions of the two or more units described above, and similar modifications are still within the scope of the claims of the present application.
  • the first user path is obtained at step 510. This step can be done by the acquisition module 310.
  • the user path can originate from information source 130 or database 320.
  • Information source 130 may include, but is not limited to, a server, a communication terminal.
  • the communication terminal may be a mobile phone, a personal computer, a wearable device, a tablet computer, a smart TV, or the like, or any combination of the above communication terminals.
  • the user guidance system 110 can obtain a user path from a communication terminal, such as a smart phone, through the acquisition module 310.
  • the user guidance system 110 can obtain the user path from the user path repository stored in the database 320 via the acquisition module 310.
  • the user path obtained from the user path library of the database 320 may be the user's own historical user path or the user path of other users.
  • the textbook can be generated in step 520. This step can be accomplished by data processing module 330.
  • step 520 can also include the steps of selecting a user path, generating a knowledge map, and comparing.
  • the generation of the textbook is based on the selected one or more user paths.
  • the generation of the textbook is based on a comparison of the two knowledge maps.
  • the generation of the textbook may be based in part on the first user path obtained.
  • the generation of the textbook may be based in part on a user rating divided according to the user's knowledge map.
  • the teaching materials may include web pages, software push information, voice, video tutorials, text messages, One or a combination of MMS, QQ message, WeChat voice, etc.
  • Textbooks can be generated by manual or machine learning.
  • the user guidance system 110 can machine learn the selected one or more user paths through machine learning algorithms (such as naive Bayesian models, decision tree algorithms, etc.) to generate an optimized user path. .
  • the optimized user path can be similar to the user, but the number of nodes is reduced (shorter user path) or the user path is similar, but the user performs better (eg, the single transaction has a higher revenue).
  • the user guidance system 110 can machine learn the results of the comparison of the two knowledge maps through a machine learning algorithm to generate a collection of knowledge points. This collection of knowledge points can be used to guide the user in augmenting the knowledge map.
  • the user guidance system 110 provides the user with the textbook generated in step 520.
  • Step 530 can be completed by user guidance module 340.
  • the teaching materials can be provided in any way that can be used for human-computer communication or human-to-human communication, and is easy for users to accept, such as system pop-ups, system notifications, system demonstrations, software push information, SMS, MMS, QQ messages, WeChat voice, video sites.
  • the user guidance system 110 can provide optimization suggestions to the user's user path in the manner of customer service voice.
  • the user guidance system 110 can recommend knowledge points to the user in a manner that pushes information.
  • Figure 6 shows a flow chart of an example method of generating a user path library and a knowledge map library.
  • the user path is obtained at step 610. This step can be done by the acquisition module 310.
  • the user path can originate from database 320 or information source 130 (eg, cell phone, Personal computers, wearables, tablets, smart TVs, etc.).
  • the user guidance system 110 can obtain a user path from a communication terminal, such as a cell phone, through the acquisition module 310.
  • the obtained user path may be a user path corresponding to the current operation of the user, or may be a historical user path of the user.
  • user guidance system 110 can obtain one or more user paths for multiple users.
  • User performance is obtained at step 620. This step can be done by the acquisition module 310.
  • User performance can be derived from information sources 130 (eg, cell phones, personal computers, wearable devices, tablets, smart TVs, etc.).
  • the correspondence between the obtained user performance and the user path may be one-to-one correspondence or multiple user representations corresponding to one user path.
  • the user performance corresponding to the user path acquired in step 610 may be a selection of a target, an analysis result of a current trend environment, a judgment of an investment timing, a revenue amount of a single transaction, and a transaction amount per transaction day. One or more of the total amount of income, etc.
  • the user guidance system 110 can generate a user path library based on the acquired user path and user performance. This step can be done by database 320.
  • the generated user path library may be stored in the database 320, and the storage methods include, but are not limited to, a sequential storage method, a link storage method, an index storage method, a hash storage method, and the like.
  • the user guidance system 110 may separately generate a user path library for the user according to the user account, or may integrate the user path library of the plurality of users into one user path library.
  • the user guidance system 110 can integrate a plurality of users' user path libraries into one user path library and separately generate a user path library for the user based on the user account.
  • the user guidance system 110 can obtain according to step 610.
  • the user path generates a knowledge map. This step can be accomplished by knowledge map generation unit 420 in data processing module 330.
  • User guidance system 110 can generate a knowledge map based on user paths of one or more users. In some embodiments, the user guidance system 110 can generate a knowledge map corresponding to the user based on a historical user path of the user.
  • the user guidance system 110 can generate a knowledge map library from the generated knowledge map. This step can be done by database 320.
  • the generated knowledge map library may be stored in the database 320, and the storage methods include, but are not limited to, a sequential storage method, a link storage method, an index storage method, a hash storage method, and the like.
  • the user guidance system 110 can separately generate a knowledge map library for the user according to the user account, or integrate the knowledge map libraries of the plurality of users into one knowledge map library.
  • the user guidance system 110 can generate a knowledge map library based on the correspondence between the knowledge map and the user path upon which the knowledge map is generated. In some embodiments, the knowledge map in the generated knowledge map library and the user path upon which the knowledge map is generated are in a one-to-many relationship.
  • step 520 can be implemented by the example generating textbook method illustrated in Figure 7.
  • the user guidance system 110 can select a second user path in the user path library based on the first user path obtained in step 510.
  • This step can be accomplished by selection unit 410 in data processing module 330.
  • the selected indicator may include, but is not limited to, one or more combinations of the similarity of the user path, the number of nodes of the user path (user path length), the user performance corresponding to the user path (eg, the amount of revenue of a single transaction), and the like.
  • the selection unit 410 can choose to match the first user path fuzzyly (eg, the similarity is between 70% and 80%) The second user path.
  • selection unit 410 may select a second user path that is exactly similar to the first user path (eg, a similarity greater than 90%). In some embodiments, selection unit 410 may select a second user path that is exactly similar to the first user path (eg, the similarity is greater than 90%) and the user behaves better than the user path.
  • the user guidance system 110 can generate a first knowledge map based on the first user path. This step can be accomplished by knowledge map generation unit 420 in data processing module 330.
  • the indicators used by the user guidance system 110 to generate the knowledge map may include, but are not limited to, the user's knowledge background, surrounding industry distribution, promotion, risk education, K-line, moving average, company announcements, research reports, news, performance changes. One or more combinations.
  • the representation form of the knowledge map generated by the knowledge map generation unit 420 may be a combination of one or more of a multidimensional radar map, a knowledge point map, a multidimensional vector, a column chart, a pie chart, a table, and the like.
  • user guidance system 110 may generate a first knowledge map based on the first user path prior to step 710.
  • steps 710 and 720 can occur simultaneously.
  • steps 720 and 730 can occur simultaneously.
  • step 720 can be performed prior to step 730.
  • Step 730 can also be completed by knowledge map generation unit 420 in data processing module 330.
  • the user guidance system 110 can obtain a comparison result by comparing the first knowledge map with the second knowledge map. This step can be done by the comparison unit 430 in the data processing module 330. User guidance system 110 compares the first and
  • the indicators used in the second knowledge map may include, but are not limited to, the user's knowledge background, surrounding industry distribution, promotion, risk education, K-line, moving average, company announcements, research reports, news, performance changes, etc. Combination of species or multiples.
  • the textbook can be generated in step 750.
  • the generation of the textbook can be based on the comparison of the first knowledge map and the second knowledge map. This step can be accomplished by textbook unit 440 in data processing module 330.
  • the manner in which the user guidance system 110 generates the teaching materials may be manual finishing or machine learning.
  • Algorithms for generating teaching materials through machine learning may include, but are not limited to, classification decision tree algorithm, K-average algorithm, support vector machine, Apriori algorithm, maximum expectation (EM) algorithm, PageRank, AdaBoost iterative algorithm, K nearest neighbor classification algorithm, Naosu Bay A combination of one or more of a Yesi model, a classification, and a regression tree.
  • the content of the textbook may include, but is not limited to, a collection of knowledge points (K line, moving average, company information, etc., one or more combinations), a user path in a real transaction case, and a new user generated through machine learning. A combination of one or more of the paths.
  • step 520 can be implemented by the method of generating textbooks shown in Figure 8.
  • a first knowledge map can be generated from the first user path. This step can be accomplished by knowledge map generation unit 420 in data processing module 330.
  • the indicators used by the user guidance system 110 to generate the knowledge map may include, but are not limited to, the user's knowledge background, surrounding industry distribution, promotion, risk education, K-line, moving average, company announcements, research reports, news, performance changes. One or more combinations.
  • the representation of the knowledge map generated by the knowledge map generation unit 420 may be a multi-dimensional radar map, a knowledge point map, a multi-dimensional vector, a column chart, a sector chart, A combination of one or more of the forms.
  • the user guidance system 110 can select a second knowledge map from the knowledge map library based on the first knowledge map.
  • This step can be accomplished by selection unit 410 in data processing module 330.
  • the selection indicators used when selecting the knowledge map from the knowledge map library may include, but are not limited to, the similarity of the knowledge map, the knowledge point type of the knowledge map, and a certain category or categories of knowledge points provided by the user to the user guidance system 110 (K) Clicks, etc. of one or more combinations of lines, moving averages, company information, etc.)
  • selection unit 410 can select a second knowledge map that is exactly similar to the first knowledge map (eg, a similarity greater than 90%).
  • the user guidance system 110 may acquire a plurality of user paths corresponding to the second knowledge map from the knowledge map library according to the second knowledge map. This step can be done by the acquisition module 310.
  • the user guidance system 110 may acquire one or more user paths corresponding to the second knowledge map according to the correspondence between the knowledge map and the user path according to which the knowledge map is generated.
  • the user path corresponding to the second knowledge map may be from the historical user path of the same user, or may be from one or more user paths of multiple users.
  • the user guidance system 110 can select a second user path from the plurality of user paths acquired in step 830 based on the first user path.
  • This step can be accomplished by selection unit 410 in data processing module 330.
  • the selected indicator may include, but is not limited to, one or more combinations of the similarity of the user path, the number of nodes of the user path (user path length), the user performance corresponding to the user path (eg, the amount of revenue of a single transaction), and the like.
  • selection unit 410 can select and The first user path is exactly similar (eg, the similarity is greater than 90%) and the user performs one or more user paths that are better than the user path.
  • selection unit 410 may select one or more user paths that are similar to the user of the first user path and that have fewer nodes (the user path length is shorter).
  • the user guidance system 110 can generate a textbook based on the second user path selected in step 840. This step can be accomplished by textbook unit 440 in data processing module 330.
  • the manner in which the user guidance system 110 generates the teaching materials may be manual finishing or machine learning.
  • Algorithms for generating teaching materials through machine learning may include, but are not limited to, classification decision tree algorithm, K-average algorithm, support vector machine, Apriori algorithm, maximum expectation (EM) algorithm, PageRank, AdaBoost iterative algorithm, K nearest neighbor classification algorithm, Naosu Bay A combination of one or more of a Yesi model, a classification, and a regression tree.
  • the content of the teaching material may include, but is not limited to, a collection of knowledge points (such as a company's research report, news), a user path in a real transaction case, a new user path generated through machine learning, and the like. A combination of one or more.
  • user guidance system 110 may generate a new user path through machine learning based on one or more user paths selected in step 840.
  • Figure 9 is a flow chart of an example method of dividing user ratings.
  • the user guidance system 110 can rank according to the user's ability to use the user guidance system 110 and then generate a corresponding textbook based on the rating.
  • the user's knowledge map can be obtained in step 910. This step can be done by the acquisition module 310.
  • the source of the knowledge map may include, but is not limited to, an information source 130, a database 320, and a data processing module 330 (such as the knowledge map generation unit 420 therein).
  • the acquisition module 310 can send a request to the knowledge map generation unit 420 in the data processing module 330, and the knowledge map generation unit 420 can transmit the knowledge map to the acquisition module 310 according to the request.
  • the manner of obtaining the knowledge map may include, but is not limited to, reading registration information, questionnaires, and performing one or more combinations of user interviews by means of voice, instant messaging, and the like.
  • the user guidance system 110 can again retrieve the user's knowledge map. This step can be done by the acquisition module 310.
  • the acquisition module 310 can send a request to the database 320, and the database 320 can transmit the knowledge map to the acquisition module 310 upon request.
  • the frequency at which the user guidance system 110 retrieves the knowledge map of the user again may be set by the user guidance system 110 or user defined.
  • the frequency at which the user guidance system 110 acquires the knowledge map of the user again may be once a year, once a quarter, once a month, once a week, once a day, once a time.
  • One or more combinations such as post-easy.
  • the user guidance system 110 can adjust the user level based on the knowledge map acquired in step 930. In some embodiments, the user guidance system 110 adjusts the user level to be based on the knowledge map size requirements set by the user guidance system 110. The user level can be promoted or maintained when the requirements of the knowledge map size set by the user guidance system 110 are met. In some embodiments, the user guidance system 110 can also adjust the user level based on the size of the knowledge map and other factors such as user performance, registration time.
  • the user guidance system 110 can generate a corresponding textbook based on the user level.
  • the generation of textbooks can be based in part on comparisons between knowledge maps (eg, different knowledge points between two knowledge maps) and based in part on user ratings.
  • the generation of textbooks can be based in part on the user path obtained (eg, the user path of other users) and based in part on the user level.
  • the user guidance system 110 can provide corresponding textbooks based on user ratings. For example, for a newly registered user, the user guidance system 110 divides it into a primary user after being evaluated, and matches the knowledge point of the primary user (such as a K-line, announcement, etc. before the investment); for a skilled user who has used for many years. The user guidance system 110 divides it into advanced users and matches the knowledge points of advanced users (such as the trend theory behind, wave theory).

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Abstract

一种用户指导方法和系统。该方法包括：获取第一个用户路径(510)，所述用户路径包括一个用户在通信终端上对两个或多个节点的操作组成的流程。该方法还包括至少部分基于所述第一个用户路径生成教材(520)，所述教材包括优化的用户路径或至少一个知识点，以及向用户提供所述教材(530)。

Description

用户指导系统及方法 技术领域
本申请涉及一种用户指导系统及方法，尤其是基于获取的用户路径通过机器学习生成教材，从而向用户提供教材。
背景技术
不同知识背景的人从事同样的工作，表现因人而异。在金融投资领域中，不同用户使用相同的金融理财类软件，由于其知识背景的差异，往往会有收益结果上的差异。相似知识背景的用户使用相同的金融理财类软件，因为其投资思维、投资逻辑的差异同样会带来不同的收益结果。现有技术中的金融理财类软件有的可能以软件说明书的方式提供了对软件操作的指导。而实际应用中用户更需要对操作背后蕴藏的知识和投资思维、投资逻辑的指导。
本申请想要解决的问题是如何把金融理财类软件用得好的用户的知识和决策逻辑介绍给用得不好的人。这个问题可以分解为：(1)如何获取用得好的用户的知识和决策逻辑；(2)如何将获取的知识和决策逻辑处理之后形成教材；以及(3)如何根据用得不好的用户的使用能力因材施教，采用用户更容易接受的方式进行指导。
用得好的用户的知识和决策逻辑蕴含在用户对软件或系统的操作中，但如果只是提供软件操作的指导，用户不能理解操作背后蕴藏的知识、投资思维和投资逻辑。因此，需要解决从用得好的 用户操作中获取该用户或该类用户的知识和投资逻辑的问题。
如果直接使用获得的知识和投资逻辑进行用户指导，用户可能只是简单的模仿用得好的用户的操作，而不能真正获得这种知识和投资逻辑。另外，针对不同的用户和实际场景，同样的知识和投资逻辑并不是都适用。因此，需要对获得的知识和投资逻辑进行处理，使之成为用户容易接受的教材。
由于受教育水平、生活阅历、工作经历和软件使用能力的差别，不同用户对于同一教材的接受水平是有差别的。如何根据用户的使用能力匹配以相应的教材也是本申请要解决的问题之一。
简述
本申请一方面是关于一个用户指导系统，根据其中一个实施例，该系统包括：一个处理器；一个计算机可读存储介质，所述计算机存储介质承载指令，当由所述处理器执行所述指令时，所述指令使处理器执行：获取第一个用户路径，所述用户路径包括一个用户在通信终端上对两个或多个节点的操作组成的流程；至少部分基于所述第一个用户路径生成教材，所述教材包括优化的用户路径或至少一个知识点；向用户提供所述教材。
本申请另一方面是关于一个用户指导方法，根据其中一个实施例，该方法包括：获取第一个用户路径，所述用户路径包括一个用户在通信终端上对两个或多个节点的操作组成的流程；至少部分基于所述第一个用户路径生成教材，所述教材包括优化的用户路径或至少一个知识点；向用户提供所述教材。
本申请另一方面是关于一个计算机可读存储介质，根据其中一个实施例，所述计算机存储介质承载指令，当由所述处理器执行所述指令时，所述指令使处理器执行：获取第一个用户路径，所述用户路径包括一个用户在通信终端上对两个或多个节点的操作组成的流程；至少部分基于所述第一个用户路径生成教材，所述教材包括优化的用户路径或至少一个知识点；向用户提供所述教材。
附图描述
为了更清楚地说明本申请实施例的技术方案，下面将对实施例描述中所需要使用的附图作简单的介绍。显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域的普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图将本申请应用于其它类似情景。除非从语言环境中显而易见或另做说明，图中相同标号代表相同结构和操作。
图1是根据本申请的一些实施例所示的用户指导系统的一种示例系统配置的示意图；
图2是根据本申请的一些实施例所示的用户指导系统的一种示例结构示意图；
图3是根据本申请的一些实施例所示的用户指导系统的一种示例模块示意图；
图4是根据本申请的一些实施例所示的数据处理模块的一种示例结构示意图；
图5是根据本申请的一些实施例所示的提供用户指导的一 种示例流程图；
图6是根据本申请的一些实施例所示的生成用户路径库和知识图谱库的示例流程图；
图7是根据本申请的一些实施例所示的生成教材方法的示例流程图；
图8是根据本申请的一些实施例所示的生成教材方法的示例流程图；
图9是根据本申请的一些实施例所示的划分用户等级方法的示例流程图。
具体描述
如本说明书和权利要求书中所示，除非上下文明确提示例外情形，“一”、“一个”、“一种”和/或“该”等词并非特指单数，也可包括复数。一般说来，术语“包括”与“包含”仅提示包括已明确标识的步骤和元素，而这些步骤和元素不构成一个排它性的罗列，方法或者设备也可能包含其它的步骤或元素。
本说明书所述的用户指导方法是指通过获取用户路径，基于获取的用户路径通过机器学习生成教材，向用户提供所述教材的方法。在一些实施例中，本申请涉及一种用户指导系统。该用户指导系统可以包括一个处理器；一个计算机可读存储介质，所述计算机存储介质承载指令，当由所述处理器执行所述指令时，所述指令使处理器执行：获取第一个用户路径，所述用户路径包括一个用户在通信终端上对两个或多个节点的操作组成的流程；至少部分基 于所述第一个用户路径生成教材，所述教材包括优化的用户路径或至少一个知识点；向用户提供所述教材。
本申请的不同实施例可适用于多种领域，包括但不限于金融及其衍生物投资(包括但不限于股票、债券、黄金、纸黄金、白银、外汇、贵金属、期货、货币基金等)、科技(包括但不限于数学、物理、化学及化学工程、生物及生物工程、电子工程、通信系统、互联网、物联网等)、政治(包括但不限于政治人物、政治事件、国家)、新闻(从区域而言，包括但不限于地区新闻、国内新闻、国际新闻；从新闻主体而言，包括但不限于政治新闻、体育新闻、科技新闻、经济新闻、生活新闻、气象新闻等)等。本申请的不同实施例应用场景包括但不限于网页、浏览器插件、客户端、定制系统、企业内部分析系统、人工智能机器人等一种或多种组合。以上对适用领域的描述仅仅是具体的示例，不应被视为是唯一可行的实施方案。显然，对于本领域的专业人员来说，在了解一种基于用户路径的用户指导方法和系统的基本原理后，可能在不背离这一原理的情况下，对实施上述方法和系统的应用领域形式和细节上的各种修正和改变，但是这些修正和改变仍在以上描述的范围之内。例如，在本申请的一个实施例中，向用户提供的教材可以是网页、视频等形式，对于本领域的专业人员来说，教材的形式也可以包括短信、QQ语音、微信语音、系统推送信息等。与此类似的替换或修正或改变，仍在本申请的保护范围之内。为了更清楚地说明本申请实施例的技术方案，下面将对实施例描述中所需要使用的 附图作简单的介绍。显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域的普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图将本申请应用于其它类似情景。除非从语言环境中显而易见或另做说明，图中相同标号代表相同结构和操作。
图1所示的是用户指导系统的一种示例系统配置的示意图。示例系统配置100可以包含但不限于一个或多个用户指导系统110、一个或多个网络120和一个或多个信息源130。用户指导系统110可以用于对获取的信息进行数据处理、生成教材以指导用户。用户指导系统110可以是一个服务器，也可以是一个服务器群组。服务器群组可以是集中式的，例如数据中心。服务器群组也可以是分布式的，例如一个分布式系统。用户指导系统110可以是本地的，也可以是远程的。
网络120可以提供信息交换的渠道。网络120可以是单一网络，也可以是多种网络组合的。网络120可以包括但不限于局域网、广域网、公用网络、专用网络、无线局域网、虚拟网络、都市城域网、公用开关电话网络等一种或多种组合。网络120可以包括多种网络接入点，如有线或无线接入点、基站或网络交换点，通过以上接入点使数据源连接网络120并通过网络接受和发送信息。
信息源130可以提供和获取各种信息。信息源130可以包括但不限于服务器、通信终端。进一步地，服务器(信息源130的一部分)可以是web服务器、文件服务器、数据库服务器、FTP服务 器、应用程序服务器、代理服务器器等，或者上述服务器的任意组合。通信终端(信息源130的一部分)可以是手机、个人电脑、可穿戴设备、平板电脑、智能电视等，或则上述通信终端的任意组合。信息源130可以通过网络120发送或/和收集信息到用户指导系统110，信息源130可以是用户输入的信息，也可以是其他数据库或信息源提供的信息。
图2所示的是用户指导系统110的一种示例结构的示意图。用户指导系统110可以包含但不限于一个或多个处理器210、一个或多个输入输出设备220、一个或多个存储器230、一个或多个网络接口240。上述设备中部分或全部可以与网络120连接。上述设备可以是集中式的也可以是分布式的。上述设备中的一个或多个设备可以是本地的也可以是远程的。
处理器210可以通过计算机程序指令控制用户指导系统110的运作。这些计算机程序指令可以存储在一个或多个存储器230上。上述一个或多个处理器210可以包含但不限于微控制器、简化指令系统计算机(RISC)、专用集成电路(ASIC)、特定应用指令集处理器(ASIP)、中央处理器(CPU)、图形处理器(GPU)、物理处理器(PPU)、微处理器单元、数字信号处理器(DSP)、现场可编程门阵列(FPGA)，或者其他能够执行计算机程序指令的电路或处理器或其组合。
输入输出设备220可以实现用户与用户指导系统110的交互。在一些实施例中，输入输出设备220可以通过网络120从信 息源130收集信息。在一些实施例中，输入输出设备220可以通过网络120向信息源130发送信息。在一些实施例中，输入输出设备220向用户指导系统110发送信息的途径可以包含但不限于键盘输入、触摸屏输入、鼠标输入、摄像头、扫描仪、手写板输入、语音输入等一种或多种组合。在一些实施例中，输入输出设备220输出信息的途径可以包含但不限于显示器显示、打印机打印、扬声器播放等一种或多种组合。输出的形式可以包含但不限于数字、字符、图片、音频和视频等一种或多种组合。
存储器230可以用来存放各种信息，例如控制用户指导系统110的计算机程序指令和数据等。上述一个或多个存储器230可以是利用电能方式存储信息的设备，例如各种存储器、随机存取存储器(Random Access Memory,RAM)、只读存储器(Read Only Memory,ROM)等。其中随机存储器包括但不限于十进计数管、选数管、延迟线存储器、威廉姆斯管、动态随机存储器(DRAM)、静态随机存储器(SRAM)、晶闸管随机存储器(T-RAM)、零电容随机存储器(Z-RAM)等中的一种或几种的组合。只读存储器包括但不限于磁泡存储器、磁钮线存储器、薄膜存储器、磁镀线存储器、磁芯内存、磁鼓存储器、光盘驱动器、硬盘、磁带、早期非易失存储器(NVRAM)、相变化内存、磁阻式随机存储式内存、铁电随机存储内存、非易失SRAM、闪存、电子抹除式可复写只读存储器、可擦除可编程只读存储器、可编程只读存储器、屏蔽式堆读内存、浮动连接门随机存取存储器、纳米随机存储器、赛道内存、可变电 阻式内存、可编程金属化单元等中的一种或几种的组合。上述一个或多个存储器230可以是利用磁能方式存储信息的设备，例如硬盘、软盘、磁带、磁芯存储器、磁泡存储器、U盘、闪存等。上述一个或多个存储器230可以是利用光学方式存储信息的设备，例如CD或DVD等。上述一个或多个存储器230可以是利用磁光方式存储信息的设备，例如磁光盘等。上述一个或多个存储器230的存取方式可以是随机存储、串行访问存储、只读存储等一种或多种组合。上述一个或多个存储器230可以是非永久记忆存储器，也可以是永久记忆存储器。以上提及的存储器230是列举了一些例子，该用户指导系统110可以使用的存储器230并不局限于此。上述一个或多个存储器230可以是本地的，也可以是远程的，也可以是云服务器上的。
网络接口240可以通过网络120实现用户指导系统110的部分或全部设备与信息源130之间的通讯。在一些实施例中，网络接口240可以通过网络120实现用户指导系统110的部分或全部设备之间的通讯。网络接口240可以是有线网络接口或无线网络接口。网络接口240可以包含但不限于金属缆线、光纤、混合缆线、连接电路或其他有线网络接口或一种或多种的组合。网络接口240可以包含但不限于无线局域网(WLAN)接口、局域网络(LAN)接口、广域网(WAN)接口、蓝牙(Bluetooth)连接、无线传感器网络(ZigBee)接口、近距离无线通讯(NFC)接口等一种或多种的组合。
图3所示的是用户指导系统110的一种示例模块示意图。用户指导系统110可以包含但不限于一个或多个获取模块310、一个或多个数据库320、一个或多个数据处理模块330、一个或多个用户指导模块340。本申请中的“模块”指的是存储在硬件、固件中的逻辑或一组软件指令。这里所指的“模块”能够通过软件和/或硬件模块执行，也可以被存储于任何一种计算机可读的非临时媒介或其他存储设备中。在某些实施例中，一个软件模块可以被编译并连接到一个可执行的程序中。这里的软件模块可以对自身或其他模块传递的信息作出回应，并且/或者可以在检测到某些事件或中断时作出回应。可以在一个计算机可读媒介(例如存储器230)上提供一个被设置为可以在计算设备上(例如处理器210)执行操作的软件模块，这里的计算机可读媒介可以是光盘、数字光盘、闪存盘、磁盘或任何其他种类的有形媒介；也可以通过数字下载的模式获取软件模块(这里的数字下载也包括存储在压缩包或安装包内的数据，在执行之前需要经过解压或解码操作)。这里的软件代码可以被部分的或全部的储存在执行操作的计算设备的存储设备中，并应用在计算设备的操作之中。软件指令可以被植入在固件中，例如可擦可编程只读存储器(EPROM)。显然，硬件模块可以包含连接在一起的逻辑单元，例如门、触发器，以及/或包含可编程的单元，例如可编程的门阵列或处理器。这里所述的模块或计算设备的功能优选的作为软件模块实施，但是也可以被表示在硬件或固件中。一般情况下，这里所说的模块是逻辑模块，不受其具体的物 理形态或存储器的限制。一个模块能够与其他的模块组合在一起，或被分隔成为一系列子模块。
上述的模块中部分或全部可以与网络120连接。上述模块可以是集中式的也可以是分布式的。上述模块中的一个或多个模块可以是本地的也可以是远程的。在一些实施例中，上述一个或多个模块的功能可以由一个或多个处理器210实现。在一些实施例中，上述一个或多个模块的功能也可以由一个或多个处理器210、一个或多个输入输出设备220、一个或多个存储器230、一个或多个网络接口240等一种或多种的组合实现。
获取模块310可以用于以各种方式获取所需要的信息。获取信息的方式可以是直接的(例如直接通过网络120从一个或多个信息源130获取信息)，也可以是间接的(例如通过数据库320、数据处理模块330或者用户指导模块340来获取信息)。在一些实施例中，获取模块310可以获取的信息包含但不限于用户路径、用户表现、知识图谱等一种或多种组合。
术语“用户路径”在本申请中可以指用户在一个或多个节点的操作连成的操作流程，其中至少一个节点是在用户的通信终端上的节点。用户路径可以包括点击浏览知识点和进行交易操作。在一些实施例中，用户路径可以是用户点击并浏览用户指导系统110提供的K线、新闻等信息，然后进行交易的操作流程。在一些实施例中，用户路径可以是用户直接进行交易的操作流程。术语“节点”在本申请中可以指用户的通讯终端或其他设备提供的可以与 用户交互的界面或界面的组成部分。在一些实施例中，节点可以是用户指导系统110提供的K线、均线、公司的公告、研报、新闻、业绩变化情况等一种或多种的组合。在一些实施例中，节点可以是选择标的、投资、卖出变现等操作对应的按钮、文本框、密码框、单选框、复选框、下拉选择框等一种或多种的组合。
术语“用户表现”在本申请中可以指与用户路径对应的过程结果或者最终结果。过程结果可以包括但不限于对标的的选择(即判断哪些股票应该重点去投资)、对当前趋势环境的分析结果(即判断当前的趋势环境适不适合投资)、投资时机的判断(即现在投资还是等价格回落后获利卖掉变现的时机的判断)等一种或多种的组合。最终结果可以包括但不限于单笔交易的收益额、每个交易日的收益总额等一种或多种的组合。
数据库320可以用于存储数据或信息，和/或生成一个或多个子数据库等。在一些实施例中，一个或多个子数据库(图中未体现)可以包括用户路径库和知识图谱库。数据库320可以包括但不限于层次式数据库、网络式数据库和关系式数据库等其中一种或多种组合。
术语“知识图谱”在本申请中可以指用户了解的知识范围。在一些实施例中，知识图谱可以指用户在交易之前(短期)以及长久以来接触过的知识点的统计整合。在一些实施例中，知识图谱可以指用户自注册账户以来从用户指导系统110获取的知识点(K线，均线，公司信息，如公告、研报、新闻、业绩变化情况等一种或多 种的组合)的集合。
数据库320可以与信息源130传递或交换信息。数据库320可以接收信息源130的信息，将其存储在数据库320。根据收到的指令，数据库320中存储的信息可以被提取，传递给信息源130。该指令可以是直接来源于信息源130，也可以来自其他模块，如获取模块310、数据处理模块330和/或用户指导模块340等。数据库320可以与获取模块310传递或交换信息。数据库320可以接收获取模块310获取的信息，如用户路径、用户表现等，将其存储在数据库320。根据收到的指令，数据库320中存储的信息可以被提取，传递给获取模块310。该指令可以是直接来源于获取模块310，也可以来自其他模块，如数据处理模块330和/或用户指导模块340等。数据库320可以与数据处理模块330传递或交换信息。数据库320可以接收数据处理模块330的信息，将其存储在数据库320。根据收到的指令，数据库320中存储的信息可以被提取，传递给数据处理模块330。该指令可以是直接来源于数据处理模块330，也可以来自其他模块，如获取模块310和用户指导模块340等。数据库320可以与用户指导模块340传递或交换信息。数据库320可以接收用户指导模块340的信息，将其存储在数据库320。根据收到的指令，数据库320中存储的信息可以被提取，传递给用户指导模块340。该指令可以是直接来源于用户指导模块340，也可以来自其他模块，如获取模块310和数据处理模块330。
数据库320发送给用户指导系统110的其他模块(如获取模 块310、数据处理模块330和/或用户指导模块340)的信息可以是直接从信息源130获取的信息，也可以是经过数据处理后的信息。经过数据处理的信息，可以是经过数据处理模块330处理后储存在数据库320的信息。数据库320与其他模块信息传递的方式可以是有线的也可以是无线的，可以是直接的也可以是间接的，可以是同时进行的也可以是顺序进行的，可以是周期的也可以是非周期的等。
数据处理模块330可以用于对获取的信息进行数据处理、生成教材。获取的信息可以包括但不限于用户路径、知识图谱、用户表现等中的一种或多种组合。获取的信息的来源可以包括但不限于获取模块310、数据库320等。在一些实施例中，获取模块310可以直接通过网络120从用户的通信终端(信息源130的一部分，如手机、个人电脑、可穿戴设备、平板电脑、智能电视等)获取用户的用户路径和/或用户表现。在一些实施例中，数据处理模块330可以发送请求并接收获取模块310发送的用户路径。获取模块310在收到从数据处理模块330发来的请求之后，可以将存储在获取模块310中的信息传输给数据处理模块330。
术语“教材”在本申请中可以指通过人工整理或者机器学习生成的部分或完整的优化用户路径或至少一个知识点。在一些实施例中，教材可以指通过人工整理或者机器学习生成的知识点的集合。在一些实施例中，教材可以指某个现实的交易案例中的用户路径。在一些实施例中，教材可以指通过机器学习后产生的新的用 户路径。
数据处理模块330可以与获取模块310进行双向通信。数据处理模块330可以处理获取模块310传输的信息，信息处理可以包括但不限于选择用户路径、生成知识图谱、比较和生成教材等中的一种或多种组合。数据处理模块330可以向获取模块310发送信息，发送的信息可以包括但不限于经过数据处理的信息以及控制信息，该控制信息可以包括但不限于信息收集方式的控制信息、信息收集时间的控制信息、信息收集来源的控制信息等。数据处理模块330可以与数据库320进行双向通信。数据处理模块330可以处理数据库320传输的信息，信息处理可以包括但不限于选择用户路径、生成知识图谱、比较和生成教材等中的一种或多种组合。数据处理模块330可以将经过数据处理后的信息传输给数据库320进行储存，也可以向数据库320发送请求信息并接收数据库320发送的信息。数据处理模块330可以与用户指导模块340进行双向通信。数据处理模块330可以将经过数据处理后的信息传输给用户指导模块340，也可以接收用户指导模块340发送的信息。
用户指导模块340可以用于向用户提供教材。在一些实施例中，用户指导模块340可以向数据处理模块330发送请求并接收数据处理模块330发送的教材。数据处理模块330在收到从用户指导模块340发来的请求之后，可以将存储在数据处理模块330中的教材传输给用户指导模块340。用户指导模块340提供给用户的教材可以包括但不限于用户指导系统110的软件操作、扩充知识 图谱的建议、股票期货等金融知识、投资的思维逻辑等中的一种或多种组合。提供教材的方式可以包括但不限于系统弹窗、系统通知、系统演示、软件推送信息、短信、彩信、QQ留言、微信语音、视频网站的视频教学、客服电话指导以及其他可用于人机交流或人与人交流而且用户容易接受的方式。指导的程度可以是根据用户使用用户指导系统110的能力，由浅入深，以用户更容易接受的方式进行。
在一些实施例中，用户指导系统110可以根据用户使用用户指导系统110的能力进行等级划分，然后根据等级匹配相应的指导方式。例如，对刚注册的新用户，用户指导系统110对其评估后划分为初级用户，并匹配以初级用户的知识点(如投资前该看K线、公告等建议)；对于使用多年的熟练用户，用户指导系统110对其评估后划分为高级用户，并匹配以高级用户的知识点(如背后的趋势理论、波浪理论)。
用户指导模块340可以向获取模块310发送请求，获取模块310可以根据请求访问数据库320获取需要的信息。需要的信息被获取之后，获取模块310将该信息传输给用户指导模块340。在一些实施例中，获取模块310在收到从用户指导模块340发来的请求之后，也可以将存储在获取模块310中的信息传输给用户指导模块340。在一些实施例中，用户指导模块340可以直接访问数据库320，并向数据库320发送请求以获取需要的信息，该信息可以被传输给用户指导模块340。在一些实施例中，数据库320可以在 没有收到请求的情况下向用户指导模块340发送信息。用户指导模块340可以向数据处理模块330发送请求，数据处理模块330可以根据请求访问数据库320获取需要的信息。需要的信息被获取之后，数据处理模块330将该信息传输给用户指导模块340。在一些实施例中，数据处理模块330在收到从用户指导模块340发来的请求之后，也可以将存储在数据处理模块330中的信息传输给用户指导模块340。用户指导模块340收到的输入信息可以包括但不限于通过人工整理或者机器学习生成的知识点的集合、某些现实的交易案例中的用户路径、通过人工整理或者机器学习后产生的新的用户路径等。
显然，对于本领域的专业人员来说，在了解用户指导系统110及方法的原理后，可能在不背离这一原理的情况下，对各个模块进行任意组合，或者构成子系统与其它模块连接，对实施上述方法和系统的应用领域形式和细节上的各种修正和改变，但是这些修正和改变仍在以上描述的范围之内。例如，获取模块310、数据库320、数据处理模块330、用户指导模块340可以是体现在一个系统中的不同模块，也可以集成在一个模块实现上述的两个或两个以上模块的功能，类似的变形仍在本申请的权利要求保护范围之内。
图4所示的是数据处理模块330的一种示例结构示意图。数据处理模块330可以包含但不限于一个或多个选择单元410、一个或多个知识图谱生成单元420、一个或多个比较单元430和一个 或多个教材单元440。上述的单元中部分或全部可以与网络120连接。上述单元可以是集中式的也可以是分布式的。上述单元中的一个或多个单元可以是本地的也可以是远程的。在一些实施例中，上述一个或多个单元的功能可以由一个或多个处理器210实现。在一些实施例中，上述一个或多个单元的功能也可以由一个或多个处理器210、一个或多个输入输出设备220、一个或多个存储器230、一个或多个网络接口240等一种或多种的组合实现。
在一些实施例中，选择单元410可以对用户路径库和/或知识图谱库进行选择操作。选择单元410可以通过访问用户指导系统110中的其他模块进行选择操作(如获取模块310、数据库320)。在一些实施例中，选择单元410可以通过访问获取模块310对存储在获取模块310中的信息进行选择。在一些实施例中，选择单元410可以通过访问数据库320对存储在数据库320中的信息进行选择。
在一些实施例中，选择单元410对用户路径进行选择时使用的选择指标可以包含但不限于用户路径的相似度、用户路径的节点数(用户路径长度)、用户路径对应的用户表现(如单笔交易的收益额)等中的一种或多种组合。在一些实施例中，选择单元410可以选择与某用户路径模糊匹配(例如相似度介于70％-80％)的一个或多个用户路径。在一些实施例中，选择单元410可以选择与某用户路径精确相似(例如相似度大于90％)的一个或多个用户路径。在一些实施例中，选择单元410可以选择与某用户路径精确相 似(例如相似度大于90％)且用户表现优于该用户路径的一个或多个用户路径。
在一些实施例中，选择单元410对知识图谱进行选择时使用的选择指标可以包含但不限于知识图谱的相似度、知识图谱的知识点种类、用户对用户指导系统110提供的某一类或某几类知识点(K线，均线，公司信息等一种或多种的组合)的点击浏览量等。在一些实施例中，选择单元410可以选择与某知识图谱精确相似(例如相似度大于90％)的一个或多个知识图谱。
选择单元410对知识图谱进行选择时可以使用排序算法。选择单元410可以使用的排序算法包含但不限于冒泡排序、鸡尾酒排序、插入排序、桶排序、计数排序、合并排序、原地合并排序、二叉排序树排序、鸽巢排序、基数排序、Gnome排序、图书馆排序、选择排序、希尔排序、组合排序、堆排序、平滑排序、快速排序等一种或多种的组合。
知识图谱生成单元420可以用于根据用户路径生成知识图谱。用户路径的来源可以包含但不限于用户指导系统110中其他模块(如获取模块310、数据库320)或者数据处理模块的其他单元(如选择单元410)等一种或多种的组合。在一些实施例中，知识图谱生成单元420可以向获取模块310发送请求，获取模块310可以根据请求将用户路径传输给知识图谱生成单元420。在一些实施例中，获取模块310可以在没有收到请求的情况下向知识图谱生成单元420发送用户路径。
在一些实施例中，知识图谱生成单元420生成知识图谱时使用的指标可以包含但不限于用户的知识背景，周边的行业分布，促销情况，风险教育情况、K线，均线，公司的公告、研报、新闻、业绩变化情况等一种或多种的组合。知识图谱生成单元420生成的知识图谱的表现形式可以是多维雷达图、知识点地图、多维向量、柱形图、扇形图、表格等一种或多种的组合。
比较单元430可以用于比较两个或两个以上知识图谱，从而得出比较结果。术语“比较结果”在本申请中可以指通过比较得到的两个或两个以上知识图谱之间的区别。在一些实施例中，比较结果可以指通过比较算法得到的两个或两个以上知识图谱之间不同的知识点或相同知识点的不同获取程度(如获取量、获取频率等)。知识图谱的来源可以包含但不限于用户指导系统110中其他模块(如数据库320)或者数据处理模块330的其他单元(如知识图谱生成单元420)等一种或多种的组合。在一些实施例中，比较单元430可以向知识图谱生成单元420发送请求，知识图谱生成单元420可以根据请求将知识图谱传输给比较单元430。在一些实施例中，知识图谱生成单元420可以在没有收到请求的情况下向比较单元430发送知识图谱。
在一些实施例中，比较单元430比较两个或两个以上知识图谱时使用的指标可以包含但不限于用户的知识背景，周边的行业分布，促销情况，风险教育情况、K线，均线，公司的公告、研报、新闻、业绩变化情况等一种或多种的组合。
教材单元440可以用于教材的生成。生成教材的素材来源可以包含但不限于用户指导系统110中其他模块(如获取模块310和/或数据库320)或者数据处理模块的其他单元(如选择单元410和/或比较单元430)等一种或多种的组合。在一些实施例中，教材单元440可以向选择单元410发送请求，选择单元410可以根据请求将素材传输给教材单元440。在一些实施例中，选择单元410可以在没有收到请求的情况下向教材单元440发送生成教材的素材。
教材单元440可以基于选择得到的一个或多个用户路径或两个知识图谱的比较结果生成教材。教材的内容可以包含但不限于知识点的集合、某个现实的交易案例中的用户路径、通过机器学习后产生的新的用户路径等一种或多种的组合。教材的生成方式可以是人工整理或机器学习。通过机器学习生成教材的算法可以包含但不限于分类决策树算法、K-平均算法、支持向量机、Apriori算法、最大期望(EM)算法、PageRank、AdaBoost迭代算法、K最近邻分类算法、朴素贝叶斯模型、分类与回归树等一种或多种的组合。
以上对数据处理模块的描述仅仅是具体的示例，不应被视为是唯一可行的实施方案。显然，对于本领域的专业人员来说，在了解所需要的信息的基本原理后，可能在不背离这一原理的情况下，对所需要的信息的内容进行各种修正和改变，但是这些修正和改变仍在以上描述的范围之内。例如，选择单元410、知识图谱生成单元420、比较单元430和/或教材单元440可以是体现在一个模 块中的不同单元，也可以集成在一个单元实现上述的两个或两个以上单元的功能，类似的变形仍在本申请的权利要求保护范围之内。
图5所示的是一个示例用户指导方法500的流程图。第一个用户路径在步骤510被获取。该步骤可以由获取模块310完成。用户路径可以来源于信息源130或数据库320。信息源130可以包括但不限于服务器、通信终端。通信终端可以是手机、个人电脑、可穿戴设备、平板电脑、智能电视等，或者上述通信终端的任意组合。在一些实施例中，用户指导系统110可以通过获取模块310从通信终端(如智能手机)获取用户路径。在一些实施例中，用户指导系统110可以通过获取模块310从存储在数据库320的用户路径库中获取用户路径。从数据库320的用户路径库中获取的用户路径可以是用户本人的历史用户路径也可以是其他用户的用户路径。
教材可以在步骤520中生成。该步骤可以由数据处理模块330完成。在一些实施例中，步骤520还可以包括选择用户路径、生成知识图谱和比较等步骤。在一些实施例中，教材的生成基于选择得到的一个或多个用户路径。在一些实施例中，教材的生成基于两个知识图谱的比较结果。在一些实施例中，教材的生成可以部分基于获取的第一个用户路径。在一些实施例中，教材的生成可以部分基于根据所述用户的知识图谱划分的用户等级。在一些实施例中，教材可以包括网页、软件推送信息、语音、视频教程、短信、 彩信、QQ留言、微信语音等一种或几种的组合。
教材的生成方式可以是人工整理或机器学习。在一些实施例中，用户指导系统110可以通过机器学习的算法(如朴素贝叶斯模型、决策树算法等)对选择得到的一个或多个用户路径进行机器学习，从而生成优化后的用户路径。优化后的用户路径可以是用户表现相似，但节点数量减少(更短的用户路径)或用户路径相似，但用户表现更优(如单笔交易的收益额更高)。在一些实施例中，用户指导系统110可以通过机器学习的算法对两个知识图谱的比较结果进行机器学习，从而生成知识点的集合。该知识点的集合可以用于指导用户扩充知识图谱。
在步骤530中用户指导系统110向用户提供在步骤520中生成的教材。步骤530可以由用户指导模块340完成。提供教材可以以所有可用于人机交流或人与人交流而且用户容易接受的方式进行，例如系统弹窗、系统通知、系统演示、软件推送信息、短信、彩信、QQ留言、微信语音、视频网站的视频教学、客服电话指导等一种或几种的组合。在一些实施例中，用户指导系统110可以用客服语音的方式对用户的用户路径提出优化建议。在一些实施例中，用户指导系统110可以用推送信息的方式向用户推荐知识点。
图6所示的是一个示例生成用户路径库和知识图谱库方法的流程图。用户路径在步骤610被获取。该步骤可以由获取模块310完成。用户路径可以来源于数据库320或信息源130(如手机、 个人电脑、可穿戴设备、平板电脑、智能电视等)。在一些实施例中，用户指导系统110可以通过获取模块310从通信终端(如手机)获取用户路径。在一些实施例中，获取的用户路径可以是用户当前操作对应的用户路径，也可以是用户的历史用户路径。在一些实施例中，用户指导系统110可以获取多个用户的一个或多个用户路径。
用户表现在步骤620被获取。该步骤可以由获取模块310完成。用户表现可以来源于信息源130(如手机、个人电脑、可穿戴设备、平板电脑、智能电视等)。获取的用户表现与用户路径的对应关系可以是一一对应或多个用户表现对应一个用户路径。在一些实施例中，与步骤610中获取的用户路径对应的用户表现可以是对标的的选择、对当前趋势环境的分析结果、投资时机的判断、单笔交易的收益额、每个交易日的收益总额等中的一种或多种。
在步骤630中，用户指导系统110可以基于获取的用户路径和用户表现生成用户路径库。该步骤可以由数据库320完成。生成的用户路径库可以存储在数据库320中，存储方法包含但不限于顺序存储方法、链接存储方法、索引存储方法以及散列存储方法等。用户指导系统110可以根据用户账号为用户单独生成用户路径库，也可以将多个用户的用户路径库整合为一个用户路径库。在一些实施例中，用户指导系统110可以将多个用户的用户路径库整合为一个用户路径库并根据用户账号为用户单独生成用户路径库。
在步骤640中，用户指导系统110可以根据步骤610中获取 的用户路径生成知识图谱。该步骤可以由数据处理模块330中的知识图谱生成单元420完成。用户指导系统110可以基于一个或多个用户的用户路径生成知识图谱。在一些实施例中，用户指导系统110可以根据一个用户的历史用户路径生成该用户对应的知识图谱。
在步骤650中，用户指导系统110可以根据生成的知识图谱生成知识图谱库。该步骤可以由数据库320完成。生成的知识图谱库可以存储在数据库320，存储方法包含但不限于顺序存储方法、链接存储方法、索引存储方法以及散列存储方法等。用户指导系统110可以根据用户账号为用户单独生成知识图谱库，也可以将多个用户的知识图谱库整合为一个知识图谱库。用户指导系统110可以根据知识图谱和生成知识图谱时依据的用户路径之间的对应关系生成知识图谱库。在一些实施例中，生成的知识图谱库中知识图谱和生成知识图谱时依据的用户路径为一对多关系。
回到图5，步骤520可由图7所示的示例生成教材方法实现。如图7所示，在步骤710中，用户指导系统110可以根据在步骤510中获得的第一个用户路径在用户路径库中选择第二个用户路径。该步骤可以由数据处理模块330中的选择单元410完成。选择的指标可以包含但不限于用户路径的相似度、用户路径的节点数(用户路径长度)、用户路径对应的用户表现(如单笔交易的收益额)等中的一种或多种组合。在一些实施例中，选择单元410可以选择与第一个用户路径模糊匹配(例如相似度介于70％-80％) 的第二个用户路径。在一些实施例中，选择单元410可以选择与第一个用户路径精确相似(例如相似度大于90％)的第二个用户路径。在一些实施例中，选择单元410可以选择与第一个用户路径精确相似(例如相似度大于90％)且用户表现优于该用户路径的第二个用户路径。
在步骤720中，用户指导系统110可以根据第一个用户路径生成第一个知识图谱。该步骤可以由数据处理模块330中的知识图谱生成单元420完成。用户指导系统110生成知识图谱时使用的指标可以包含但不限于用户的知识背景，周边的行业分布，促销情况，风险教育情况、K线，均线，公司的公告、研报、新闻、业绩变化情况等一种或多种的组合。知识图谱生成单元420生成的知识图谱的表现形式可以是多维雷达图、知识点地图、多维向量、柱形图、扇形图、表格等一种或多种的组合。
在一些实施例中，用户指导系统110可以在步骤710之前根据第一个用户路径生成第一个知识图谱。在一些实施例中，步骤710和步骤720可以同时进行。在一些实施例中，步骤720和步骤730可以同时进行。在一些实施例中，步骤720可以先于步骤730进行。步骤730也可以由数据处理模块330中的知识图谱生成单元420完成。
在步骤740中，用户指导系统110可以通过比较第一个知识图谱和第二个知识图谱得到比较结果。该步骤可以由数据处理模块330中的比较单元430完成。用户指导系统110比较第一个和 第二个知识图谱时使用的指标可以包含但不限于用户的知识背景，周边的行业分布，促销情况，风险教育情况、K线，均线，公司的公告、研报、新闻、业绩变化情况等一种或多种的组合。
教材可以在步骤750中生成。教材的生成可以基于第一个知识图谱和第二个知识图谱的比较结果。该步骤可以由数据处理模块330中的教材单元440完成。用户指导系统110生成教材的方式可以是人工整理或机器学习。通过机器学习生成教材的算法可以包含但不限于分类决策树算法、K-平均算法、支持向量机、Apriori算法、最大期望(EM)算法、PageRank、AdaBoost迭代算法、K最近邻分类算法、朴素贝叶斯模型、分类与回归树等一种或多种的组合。教材的内容可以包含但不限于知识点(K线，均线，公司信息等一种或多种的组合)的集合、某个现实的交易案例中的用户路径、通过机器学习后产生的新的用户路径等一种或多种的组合。
再回到图5，步骤520可由图8所示的生成教材方法实现。如图8所示，在步骤810，可以根据第一个用户路径生成第一个知识图谱。该步骤可以由数据处理模块330中的知识图谱生成单元420完成。用户指导系统110生成知识图谱时使用的指标可以包含但不限于用户的知识背景，周边的行业分布，促销情况，风险教育情况、K线，均线，公司的公告、研报、新闻、业绩变化情况等一种或多种的组合。知识图谱生成单元420生成的知识图谱的表现形式可以是多维雷达图、知识点地图、多维向量、柱形图、扇形图、 表格等一种或多种的组合。
在步骤820中，用户指导系统110可以根据第一个知识图谱从知识图谱库中选择第二个知识图谱。该步骤可以由数据处理模块330中的选择单元410完成。从知识图谱库中选择知识图谱时使用的选择指标可以包含但不限于知识图谱的相似度、知识图谱的知识点种类、用户对用户指导系统110提供的某一类或某几类知识点(K线，均线，公司信息等一种或多种的组合)的点击浏览量等。在一些实施例中，选择单元410可以选择与第一个知识图谱精确相似(例如相似度大于90％)的第二个知识图谱。
在步骤830中，用户指导系统110可以根据第二个知识图谱从知识图谱库获取第二个知识图谱对应的多个用户路径。该步骤可以由获取模块310完成。用户指导系统110可以根据知识图谱和生成知识图谱时依据的用户路径之间的对应关系获取与第二个知识图谱对应的一个或多个用户路径。第二个知识图谱对应的用户路径可能来自同一用户的历史用户路径，也可能来自多个用户的一个或多个用户路径。
在步骤840中，用户指导系统110可以根据第一个用户路径从在步骤830中获取的多个用户路径中选择第二个用户路径。该步骤可以由数据处理模块330中的选择单元410完成。选择的指标可以包含但不限于用户路径的相似度、用户路径的节点数(用户路径长度)、用户路径对应的用户表现(如单笔交易的收益额)等中的一种或多种组合。在一些实施例中，选择单元410可以选择与 第一个用户路径精确相似(例如相似度大于90％)且用户表现优于该用户路径的一个或多个用户路径。在一些实施例中，选择单元410可以选择与第一个用户路径的用户表现相似且用户路径的节点数更少(用户路径长度更短)的一个或多个用户路径。
在步骤850中，用户指导系统110可以根据步骤840中选择的第二个用户路径生成教材。该步骤可以由数据处理模块330中的教材单元440完成。用户指导系统110生成教材的方式可以是人工整理或机器学习。通过机器学习生成教材的算法可以包含但不限于分类决策树算法、K-平均算法、支持向量机、Apriori算法、最大期望(EM)算法、PageRank、AdaBoost迭代算法、K最近邻分类算法、朴素贝叶斯模型、分类与回归树等一种或多种的组合。在一些实施例中，教材的内容可以包含但不限于知识点(如公司的研报、新闻)的集合、某个现实的交易案例中的用户路径、通过机器学习后产生的新的用户路径等一种或多种的组合。在一些实施例中，用户指导系统110可以根据步骤840中选择的一个或多个用户路径通过机器学习生成新的用户路径。
图9所示的是一个示例划分用户等级方法的流程图。在一些实施例中，用户指导系统110可以根据用户使用用户指导系统110的能力进行等级划分，然后基于等级生成相应的教材。
用户的知识图谱可以在步骤910中被获取。该步骤可以由获取模块310完成。知识图谱的来源可以包括但不限于信息源130、数据库320、数据处理模块330(如其中的知识图谱生成单元420) 等一种或多种的组合。在一些实施例中，获取模块310可以向数据处理模块330中的知识图谱生成单元420发送请求，知识图谱生成单元420可以根据请求将知识图谱传输给获取模块310。对于刚注册的初级用户，获取知识图谱的方式可以包括但不限于读取注册信息，问卷调查，通过语音、即时通讯等方式进行用户访谈等一种或多种的组合。
在步骤920中，用户指导系统110可以根据步骤910中获取的知识图谱划分用户等级。用户指导系统110可以根据用户知识图谱的大小对用户进行评级。评价知识图谱的大小的指标包括但不限于用户的知识背景，周边的行业分布，促销情况，风险教育情况、K线，均线，公司的公告、研报、新闻、业绩变化情况等一种或多种的组合。在一些实施例中，用户指导系统110还可以根据知识图谱的大小和其他因素(如用户表现，注册时间，教育背景，职业，其他炒股软件的使用情况等一种或多种的组合)对用户进行评级。
在步骤930中，用户指导系统110可以再次获取用户的知识图谱。该步骤可以由获取模块310完成。在一些实施例中，获取模块310可以向数据库320发送请求，数据库320可以根据请求将知识图谱传输给获取模块310。用户指导系统110再次获取用户的知识图谱的频率可以是用户指导系统110设定的或者用户自定义的。用户指导系统110再次获取用户的知识图谱的频率可以是每年一次、每季度一次、每个月一次、每周一次、每天一次、每次交 易后等一种或多种的组合。
在步骤940中，用户指导系统110可以根据步骤930中获取的知识图谱调整用户等级。在一些实施例中，用户指导系统110调整用户等级可以根据用户指导系统110设定的知识图谱大小的要求。当满足用户指导系统110设定的知识图谱大小的要求时，用户等级可以提升或者保持。在一些实施例中，用户指导系统110还可以根据知识图谱的大小和其他因素(如用户表现，注册时间)对用户等级进行调整。
在一些实施例中，用户指导系统110可以根据用户等级生成相应的教材。例如，教材的生成可以部分基于知识图谱之间的比较结果(如两个知识图谱之间不同的知识点)，并且部分基于用户等级。例如，教材的生成可以部分基于获取的用户路径(如其他用户的用户路径)，并且部分基于用户等级。
在一些实施例中，用户指导系统110可以根据用户等级提供相应的教材。例如，对刚注册的新用户，用户指导系统110对其评估后划分为初级用户，并匹配以初级用户的知识点(如投资前该看K线、公告等建议)；对于使用多年的熟练用户，用户指导系统110对其评估后划分为高级用户，并匹配以高级用户的知识点(如背后的趋势理论、波浪理论)。
以上对划分用户等级方法的描述仅仅是具体的示例，不应被视为是唯一可行的实施方案。显然，对于本领域的专业人员来说，在了解划分用户等级方法的基本原理后，可能在不背离这一原理 的情况下，对划分用户等级方法的步骤进行各种修正和改变，但是这些修正和改变仍在以上描述的范围之内。

Claims (20)

  1. 一个系统，包括：
    一个处理器；
    一个计算机可读存储介质，所述计算机存储介质承载指令，当由所述处理器执行所述指令时，所述指令使处理器执行：
    获取第一个用户路径，所述用户路径包括一个用户在通信终端上对两个或多个节点的操作组成的流程；
    至少部分基于所述第一个用户路径生成教材，所述教材包括优化的用户路径或至少一个知识点；
    向用户提供所述教材。
  2. 根据权利要求1所述的系统，所述的获取第一个用户路径包括获取所述用户的历史用户路径和其他用户的用户路径。
  3. 根据权利要求1所述的系统，所述的获取第一个用户路径进一步包括从用户路径库获得用户路径。
  4. 根据权利要求1所述的系统，所述的两个或多个节点包括至少一个在所述通信终端上的节点。
  5. 根据权利要求1所述的系统，所述的生成教材进一步包括：
    根据第一个用户路径在用户路径库中选择第二个用户路径；
    根据第一个用户路径生成第一个知识图谱；
    根据第二个用户路径生成第二个知识图谱；
    比较第一个知识图谱和第二个知识图谱得到比较结果；
    根据比较结果通过机器学习生成教材。
  6. 根据权利要求5，所述的比较结果包括第一个知识图谱和第二个知识图谱之间不同的知识点。
  7. 根据权利要求1所述的系统，所述的生成教材进一步包括：
    根据第一个用户路径生成第一个知识图谱；
    根据第一个知识图谱从知识图谱库中选择第二个知识图谱；
    获取第二个知识图谱对应的多个用户路径；
    根据第一个用户路径从所述多个用户路径选择第二个用户路径；
    根据第二个用户路径通过机器学习生成教材。
  8. 根据权利要求1所述的系统，所述的知识点包括至少一个K线，均线，或公司信息。
  9. 根据权利要求1所述的系统，所述的教材进一步包括系统操作的指导、金融知识、投资的思维逻辑的指导。
  10. 根据权利要求1所述的系统，所述的生成教材进一步包括：
    获取所述用户的知识图谱；
    根据所述知识图谱进行等级划分；
    至少部分基于用户等级生成教材。
  11. 一个方法，包括：
    获取第一个用户路径，所述用户路径包括一个用户在通信终端上对两个或多个节点的操作组成的流程；
    至少部分基于所述第一个用户路径生成教材，所述教材包括优化的用户路径或至少一个知识点；
    向用户提供所述教材。
  12. 根据权利要求11所述的方法，所述的获取第一个用户路径包括获取所述用户的历史用户路径和其他用户的用户路径。
  13. 根据权利要求11所述的方法，所述的获取第一个用户路径进一步包括从用户路径库获得用户路径。
  14. 根据权利要求11所述的方法，所述的生成教材进一步包括：
    根据第一个用户路径在用户路径库中选择第二个用户路径；
    根据第一个用户路径生成第一个知识图谱；
    根据第二个用户路径生成第二个知识图谱；
    比较第一个知识图谱和第二个知识图谱得到比较结果；
    根据比较结果通过机器学习生成教材。
  15. 根据权利要求14，所述的比较结果包括第一个知识图谱和第二个知识图谱之间不同的知识点。
  16. 根据权利要求11所述的方法，所述的生成教材进一步包括：
    根据第一个用户路径生成第一个知识图谱；
    根据第一个知识图谱从知识图谱库中选择第二个知识图谱；
    获取第二个知识图谱对应的多个用户路径；
    根据第一个用户路径从所述多个用户路径选择第二个用户路径；
    根据第二个用户路径通过机器学习生成教材。
  17. 根据权利要求11所述的方法，所述的知识点包括至少一个K线，均线，或公司信息。
  18. 根据权利要求11所述的方法，所述的教材进一步包括系统操作的指导、金融知识、投资的思维逻辑的指导。
  19. 根据权利要求11所述的方法，所述的生成教材进一步包括：
    获取所述用户的知识图谱；
    根据所述知识图谱进行等级划分；
    至少部分基于用户等级生成教材。
  20. 一个计算机可读存储介质，所述计算机存储介质承载指令，当由所述处理器执行所述指令时，所述指令使处理器执行：
    获取第一个用户路径，所述用户路径包括一个用户在通信终端上对两个或多个节点的操作组成的流程；
    至少部分基于所述第一个用户路径生成教材，所述教材包括优化的用户路径或至少一个知识点；
    向用户提供所述教材。
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