CN113516493A - Full-link multi-terminal supportable big data visualization analysis platform based on user behaviors - Google Patents
Full-link multi-terminal supportable big data visualization analysis platform based on user behaviors Download PDFInfo
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Abstract
The invention discloses a full-link multi-terminal supportable big data visual analysis platform based on user behaviors, which comprises a user terminal and a platform terminal, wherein the user terminal is in network connection with the platform terminal through a network connection end, the user terminal can be divided into a mobile phone end, a PC end and a Pad end, the mobile phone end and the Pad end can be independently divided into an IOS end and an Android end, the platform terminal is connected with the IOS end, the Android end, an applet end, a fast application end and an H5 end, and the user terminal and the platform terminal are in bidirectional internet connection through the network connection end. The invention can more conveniently analyze the operation process of behaviors and transactions for a business operation team, and can also reduce a part of complicated behavior data conventional development work for a big data team, so that the team can concentrate on more core data in the team and deep analysis and mining of the data, thereby improving the total enterprise value.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to a full-link multi-terminal supportable big data visualization analysis platform based on user behavior.
Background
In the existing visual analysis platform for big data, aiming at various current use terminals including mobile phones, pads, PCs and the like, and platforms including IOS, Android, various applets, fast applications and H5, the browsing and consumption analysis of a user full link cannot be carried out, and a business operation team cannot carry out operation process analysis of behaviors and transactions more conveniently. For a big data team, the difficulty of conventional development work of complex behavior data is increased, the team cannot concentrate on more core data inside and deep analysis and mining of the data, and therefore the total enterprise value is reduced.
Through mass retrieval, the prior art is found to be CN109191886A, and the invention discloses a fleet path planning method based on a big data analysis platform, which belongs to the technical field of commercial vehicle path optimization and relates to the fleet path planning method based on the big data analysis platform, and comprises the following steps: A. a plurality of T-BOX modules installed in a motorcade regularly acquire data of vehicle behaviors and driving behaviors; B. uploading the data of the vehicle behaviors and the driving behaviors collected by each T-BOX module to a network cloud through a wireless communication module; C. the big data analysis platform module trains and models the data of the cloud end to calculate key data; D. and the big data analysis platform module guides the vehicle-mounted terminal, visualizes data to a vehicle owner and prompts the vehicle owner to select an optimized path. The fleet path planning method based on the big data analysis platform can predict future road conditions through historical data, provide an optimized path, balance the relationship between reduced oil consumption and reduced vehicle loss, save transportation cost and improve transportation efficiency.
In summary, the existing big data analysis platform has the problem that data between devices cannot be split; the data among the platforms can not be intercommunicated and can not lead each department to analyze and use different service data based on the same data flow, and the requirement of actual use can not be met.
Disclosure of Invention
The invention aims to provide a full-link multi-terminal supportable big data visualization analysis platform based on user behaviors so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a big data visualization analysis platform based on user behavior full-link multi-end support comprises a user terminal and a platform terminal, wherein the user terminal is in network connection with the platform terminal through a network connection end.
Preferably, the user terminal can be divided into a mobile phone terminal, a PC terminal and a Pad terminal;
the mobile phone end and the Pad end can be independently divided into an IOS end and an Android end.
Preferably, the platform terminal is connected with an IOS terminal, an Android terminal, an applet terminal, a fast application terminal and an H5 terminal;
the user terminal and the platform terminal are connected through a network connection end to form a bidirectional internet connection, and the mobile phone end, the PC end and the Pad end in the user terminal are connected through the internet and are connected with the IOS end, the Android end, the applet end, the fast application end and the H5 end in the platform terminal to form corresponding network connections.
A method for using a full-link multi-terminal supportable big data visualization analysis platform based on user behaviors comprises the following steps:
the first step is as follows: the platform terminal carries out event point burying on the developed service;
the second step is that: the Event + User double-table model abstracts User behaviors;
the third step: the platform terminal builds and analyzes a model;
the fourth step: the user accesses the related data in the platform terminal through the network connection established by the mobile phone end, the network connection end and the platform terminal;
the fifth step: the related data can be used for analyzing and using different business data.
Compared with the prior art, the invention has the beneficial effects that: the invention can more conveniently analyze the operation process of the action and the transaction for the business operation team; for a big data team, a part of complicated conventional development work of behavior data can be reduced, the team can be more concentrated on internal more core data and deep analysis and mining of the internal more core data, and therefore the overall enterprise value is improved.
A user can directly access a platform terminal through the user terminal in an internet network connection mode, the platform terminal can split data through different sub-terminal types of an IOS terminal, an Android terminal, an applet terminal, a fast application terminal and an H5 terminal, the user terminal can establish corresponding network connection with the IOS terminal, the Android terminal, the applet terminal, the fast application terminal and the H5 terminal in the platform terminal through internet connection through a mobile phone terminal, a PC terminal and a Pad terminal to perform corresponding data access, so that browsing and consumption analysis of a user full link can be performed on various current mobile phones, pads, PCs and the like, the IOS, the Android, various applets, fast applications and the H5 terminal, and different service data analysis and use can be performed on the basis of the same data stream by various departments.
Drawings
FIG. 1 is a schematic structural diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "front", "rear", "both ends", "one end", "the other end", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the device or the element referred to must have a specific orientation, be constructed in a specific orientation, and operate, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly stated or limited, the terms "mounted," "disposed," "connected," and the like are to be construed broadly, and for example, "connected" may be fixedly, detachably, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. Specific meanings of the above terms in the present invention can be specifically understood by those of ordinary skill in the art.
Referring to fig. 1, an embodiment of the present invention:
the first embodiment is as follows:
a full-link multi-terminal supportable big data visualization analysis platform based on user behaviors comprises a user terminal and a platform terminal, wherein the user terminal is connected with the platform terminal through a network connection end.
The user terminal can be divided into a mobile phone end, a PC end and a Pad end, the definition of the user terminal is wide, and electronic equipment used by people can be divided into three categories, namely the mobile phone end, the PC end and the Pad end, so that the path queried by the user can be fully covered;
the mobile phone end and the Pad end can be independently divided into an IOS end and an Android end, and the mobile phone end and the Pad end can be classified into two types, namely an IOS system and an Android system; a user can directly access the platform terminal through the user terminal in an internet network connection mode, the platform terminal can split data through different sub-terminals of an IOS terminal, an Android terminal, an applet terminal, a fast application terminal and an H5 terminal, the user terminal can establish corresponding network connection with the IOS terminal, the Android terminal, the applet terminal, the fast application terminal and the H5 terminal in the platform terminal through a mobile phone terminal, a PC terminal and a Pad terminal through internet connection to perform corresponding data access, and therefore browsing and consumption analysis of all links of the user can be performed on various current mobile phones, pads, PCs and the like, the IOS, the Android, various applets, fast applications and the H5 terminal, and different service data analysis and use of all departments based on the same data flow are facilitated.
The platform terminal is provided with a plurality of sub-connection terminals for a user to access conveniently, and the IOS terminal and the Android terminal correspond to a mobile phone terminal and a Pad terminal of the user terminal;
the fast application framework is deeply integrated into mobile phone systems of various manufacturers, seamless connection between user requirements and application services can be achieved on the operating system level, user experience and conversion efficiency of the application services are improved, and meanwhile retention capabilities such as desktop icon generation and the like are supported. The front-end technology stack development is used, native rendering is carried out, and the dual advantages of the H5 page and native application are achieved. The quick application is a position establishing and searching entry which is intuitively perceived by users, such as a traditional notification bar, a negative screen, information flow and the like, and comprises short messages, photos, voice assistants, unloading scenes, card packages and the like. Based on artificial intelligence of the WYSIWYG mobile phone, more entrance scenes such as intelligent scene identification, authority calling of hardware functions, payment and the like are created.
H5 is an abbreviation of HTML5, HTML5 is a specification of core language HTML in the Web, and content viewed by a user when browsing a Web page by any means is originally in HTML format, and is converted into information recognizable in a browser through some technical process. HTML5 has been improved from the former HTML4.01, and although the technical personnel may not put these new technologies into use in the development process, the website development technical personnel must know the new characteristics of the technology; HTML5 is composed of different technologies that have found wide use in the internet, providing more standard machines for enhancing network applications. The syntactic characteristics of HTML5 are more pronounced than in conventional techniques, and incorporates the content of SVG. The content can be used in the webpage to process multimedia content more conveniently, and other elements are also combined in the HTML5 to adjust and modify the original functions and carry out standardization work.
The user terminal and the platform terminal establish bidirectional internet connection through a network connection end, and a mobile phone end, a PC end and a Pad end in the user terminal establish corresponding network connection with an IOS end, an Android end, an applet end, a fast application end and an H5 end in the platform terminal through internet connection; the platform terminal can split data through different sub-terminals of the IOS terminal, the Android terminal, the applet terminal, the fast application terminal and the H5 terminal, and the user terminal can be connected with corresponding network connections constructed by the IOS terminal, the Android terminal, the applet terminal, the fast application terminal and the H5 terminal in the platform terminal through the mobile phone terminal, the PC terminal and the Pad terminal through the Internet to access the corresponding data.
Example two:
a method for using a full-link multi-terminal supportable big data visualization analysis platform based on user behaviors comprises the following steps:
the first step is as follows: the platform terminal carries out event point burying on the developed service, marks and distributes data and events, and can split the data through different sub-terminals of an IOS terminal, an Android terminal, an applet terminal, a fast application terminal and an H5 terminal;
the second step is that: the Event + User double-table model abstracts User behaviors, and the Event + User double-table model can more intuitively display the distribution trend of data;
the third step: a platform terminal builds and analyzes a model, so that the operation process analysis of behaviors and transactions can be carried out more conveniently; for a big data team, a part of complicated conventional development work of behavior data can be reduced, and the team can concentrate on more core data in the team and carry out deep analysis and mining on the more core data, so that the total enterprise value is improved;
the fourth step: the user accesses the relevant data in the platform terminal through the network connection established by the mobile phone end, the network connection end and the platform terminal;
the fifth step: the related data can be analyzed and used for different service data, and the user terminal can be connected with the IOS terminal, the Android terminal, the small program terminal, the fast application terminal and the H5 terminal in the platform terminal through the Internet through a mobile phone terminal, a PC terminal and a Pad terminal to construct corresponding network connection for corresponding data access, so that the full-link browsing and consumption analysis of the user can be conveniently carried out aiming at various mobile phones, pads, PCs and the like, IOS, Android, various small programs, fast applications and H5 terminals at present, and the analysis and the use of different service data based on the same data flow of each department can be facilitated.
The working principle is as follows: the invention can more conveniently analyze the operation process of the action and the transaction for the business operation team; for a big data team, a part of complicated conventional development work of behavior data can be reduced, the team can be more concentrated on more core data inside and deep analysis and mining of the data, and therefore the value of the total enterprise is improved.
A user can directly access a platform terminal through the user terminal in an internet network connection mode, the platform terminal can split data through different sub-terminal types of an IOS terminal, an Android terminal, an applet terminal, a fast application terminal and an H5 terminal, the user terminal can establish corresponding network connection with the IOS terminal, the Android terminal, the applet terminal, the fast application terminal and the H5 terminal in the platform terminal through internet connection through a mobile phone terminal, a PC terminal and a Pad terminal to perform corresponding data access, so that browsing and consumption analysis of a user full link can be performed on various current mobile phones, pads, PCs and the like, the IOS, the Android, various applets, fast applications and the H5 terminal, and different service data analysis and use can be performed on the basis of the same data stream by various departments.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (4)
1. A big data visual analysis platform based on user behavior full-link multi-terminal support comprises a user terminal and a platform terminal, and is characterized in that: and the user terminal is connected with the platform terminal through a network connection end to establish network connection.
2. The full-link multi-terminal supportable big data visualization analysis platform based on user behavior according to claim 1, wherein: the user terminal can be divided into a mobile phone terminal, a PC terminal and a Pad terminal;
the mobile phone end and the Pad end can be independently divided into an IOS end and an Android end.
3. The full-link multi-terminal supportable big data visualization analysis platform based on user behavior according to claim 1, wherein: the platform terminal is connected with an IOS terminal, an Android terminal, an applet terminal, a fast application terminal and an H5 terminal;
the user terminal and the platform terminal are connected through a network connection end to form a bidirectional internet connection, and a mobile phone end, a PC end and a Pad end in the user terminal are connected through the internet to form a corresponding network connection with an IOS end, an Android end, an applet end, a fast application end and an H5 end in the platform terminal.
4. A method for using a full-link multi-terminal supportable big data visualization analysis platform based on user behaviors comprises the following steps:
the first step is as follows: the platform terminal carries out event point burying on the developed service;
the second step is that: the Event + User double-table model abstracts User behaviors;
the third step: the platform terminal builds and analyzes a model;
the fourth step: the user accesses the related data in the platform terminal through the network connection established by the mobile phone end, the network connection end and the platform terminal;
the fifth step: the related data can be used for analyzing and using different business data.
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| CN106548381A (en) * | 2016-12-19 | 2017-03-29 | 武汉理工数字传播工程有限公司 | Intelligent subscriber tag systems and implementation method |
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2020
- 2020-04-12 CN CN202010282666.6A patent/CN113516493A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100325206A1 (en) * | 2009-06-18 | 2010-12-23 | Umeshwar Dayal | Providing collaborative business intelligence |
| CN104573904A (en) * | 2014-09-29 | 2015-04-29 | 同济大学 | Data visualizing system for monitoring user and software behaviors during network transaction |
| CN106548381A (en) * | 2016-12-19 | 2017-03-29 | 武汉理工数字传播工程有限公司 | Intelligent subscriber tag systems and implementation method |
| CN110543474A (en) * | 2019-08-21 | 2019-12-06 | 河海大学 | User behavior analysis method and device based on full-buried point and potential factor model |
Non-Patent Citations (1)
| Title |
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