CN112507213B - Method for recommending optimized system scheme based on behavior big data analysis - Google Patents
Method for recommending optimized system scheme based on behavior big data analysis Download PDFInfo
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Abstract
The invention discloses a method for recommending and optimizing a system scheme based on behavior big data analysis, which comprises the following steps: the system automatically records the behavior path of the user in the system; analyzing the recorded behavior path; integrating the behavior paths according to the analysis result; optimizing the user operation step through a recommendation form according to the integration result; and recommending the optimized system to the user, and the user can save or replace the optimized system. According to the technical scheme, similar segment paths in the behavior paths are found through statistical analysis of behavior path records of the user, and a new system scheme optimized and integrated by the user is given, so that the updating system is optimized in a targeted manner, the use habits of the user in the use process of the user are better fitted, and the working efficiency of the user is improved.
Description
Technical Field
The invention relates to the technical field of big data processing, in particular to a method for recommending an optimized system scheme based on behavior big data analysis.
Background
With the development of cloud computing technology, various data-intensive applications are produced, and data management of data centers becomes more and more important. How to enable the data center to fully consider energy consumption and consider the service capacity of the heterogeneous nodes and the real-time problem of processing complex connection queries is a very urgent problem. The data placement strategy of the existing data center is still in a very extensive stage, thereby causing a great deal of investment waste and energy waste.
The production and operation activities of each enterprise currently comprise a great number of business processes, the business processes have both general management processes and unique management logics of a single enterprise among the enterprises, and the expression of the business management processes of the enterprises in an information system is the circulation of form data. In the form data circulation process, the application system records the corresponding relation between the data source form and the target form, other constraint conditions, the consistency requirement required to be met by form data and the like.
Chinese patent document CN107122363A discloses a "smart form system". Various individualized intelligent data analysis forms required by a user are formed by being embedded into an information system of a third party, so that the data use efficiency is improved. The technical scheme requires the user to set by himself, the user behavior is high in cost and low in efficiency, and intelligent optimization updating of the form system and data is lacked.
Disclosure of Invention
The invention mainly solves the technical problem that the original form system is lack of intelligent optimization updating of the form system and data, and provides a method for recommending an optimized system scheme based on behavior big data analysis.
The technical problem of the invention is mainly solved by the following technical scheme: the invention comprises the following steps:
(1) the system automatically records the behavior path of the user in the system;
(2) analyzing the recorded behavior path;
(3) integrating the behavior paths according to the analysis result;
(4) optimizing the user operation step through a recommendation form according to the integration result;
(5) and recommending the optimized system to the user, and the user can save or replace the optimized system.
Preferably, the behavior path in step 1 specifically includes: and taking a system home page opened by a user as a behavior path starting point, recording a series of clicking and inputting operations after the user as behavior nodes, and determining a behavior user path end point when the time for the user to close the operation page and return to the system home page or stop operating the operation page and return to the home page is more than or equal to 30 min.
Preferably, the system in step 1 automatically records the behavior path of the user, takes the opening and closing of the system as the starting and ending time, and marks the behavior path in the starting and ending time as the same time period to be stored in the cloud platform.
Preferably, the step 2 of analyzing the behavior path specifically includes:
(2.1) segmenting and simplifying each behavior path;
(2.2) comparing and finding similar segment behaviors, and then finding other similar behavior segments in the string by taking the similar segment behaviors as starting points;
(2.3) similar complete overall behavior segments are combined.
Preferably, the criterion for segmenting each behavior path includes segmenting according to events, conditions and results, and the criterion for simplifying each behavior path includes simplifying unnecessary operations between two effective operations and only reserving the effective operations to form a simplified new behavior path.
Preferably, the effective operation comprises: clicking operation with feedback and input operation without deletion; the optional operations include: the click operation is carried out at a blank position or a position without clicking keys, the click operation which does not carry out effective operation on the opened page after the page is opened is carried out, and the operation is immediately deleted after the page is input.
Preferably, after the behavior paths are simplified and segmented in step 3, similar segment behaviors are found through comparison, the comparison is performed along the behavior paths according to the segment behaviors, overlapping nodes which are more than 10 times in the similar behavior paths are recorded, the summarized overlapping nodes form a standard path of the similar behavior paths, the similar path is compared with the standard path, and if the overlapping degree is more than or equal to 80%, the similar path is regarded as the same path.
Preferably, in the step 4, the behavior path with the frequency exceeding 10 times in the last ten days is regarded as a common path, and the common path is recommended in the user operation process.
Preferably, the behavior node recommendation method includes the following specific steps: when any effective operation is carried out by a user, a recommendation frame appears below the system, the recommendation frame is sorted according to the appearance frequency of the common paths, the next effective behavior node in the common paths sequentially appears, and the effective behavior nodes comprise click contents which are effectively clicked and input contents which are effectively input.
Preferably, the step 5 counts the click frequency of the effective behavior nodes in the recommendation box, recommends the segment behaviors of the common paths three times before the click frequency in the last ten days to the system home page, recommends the optimized system to the user, and the user can save or replace the common path behaviors by himself.
The invention has the beneficial effects that: through statistical analysis of the behavior path records of the user, similar segment paths in the behavior paths are found out, and a new system scheme optimized and integrated by the user is given, so that the updating system is optimized in a targeted manner, the use habits of the user in the use process of the user are better fitted, and the working efficiency of the user is improved.
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FIG. 1 is a block flow diagram of the present invention.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings. The embodiment is as follows: the method for recommending an optimized system scheme based on behavior big data analysis, as shown in fig. 1, of the embodiment includes the following steps:
(1) the system automatically records the behavioral path of the user in using the system. The behavior path specifically includes: and taking a system home page opened by a user as a behavior path starting point, recording a series of clicking and inputting operations after the user as behavior nodes, and determining a behavior user path end point when the time for the user to close the operation page and return to the system home page or stop operating the operation page and return to the home page is more than or equal to 30 min. The system automatically records the behavior path of the user, the behavior path is used as the starting and stopping time according to the opening and closing of the system, and the behavior path in the starting and stopping time is marked as the same time period to be stored in the cloud platform.
(2) Analyzing the recorded behavior path; the specific steps of analyzing the behavior path include:
and (2.1) segmenting and simplifying each behavior path. The criterion for segmenting each behavior path comprises segmentation according to events, conditions and results. The standard for simplifying each behavior path comprises the steps of simplifying unnecessary operations between two effective operations and only reserving the effective operations to form a simplified new behavior path.
Wherein the effective operation comprises: clicking operation with feedback and input operation without deletion; the optional operations include: the click operation is carried out at a blank position or a position without clicking keys, the click operation which does not carry out effective operation on the opened page after the page is opened is carried out, and the operation is immediately deleted after the page is input.
(2.2) comparing and finding similar segment behaviors, and then finding other similar behavior segments in the string by taking the similar segment behaviors as a starting point.
(2.3) similar complete overall behavior segments are combined.
(3) Integrating the behavior paths according to the analysis result; after simplifying and segmenting each behavior path, finding out similar segment behaviors through comparison, prolonging and comparing along the behavior path according to the segment behaviors, recording coincident nodes which are more than 10 times in the similar behavior path, forming a standard path of the similar behavior path by the collected coincident nodes, comparing the similar path with the standard path, and if the coincidence degree is more than or equal to 80%, determining the similar path as the same path. The behavior path with the frequency of more than 10 occurrences in the last ten days is regarded as the common path.
(4) And optimizing the user operation steps in a recommendation form according to the integration result, and recommending the behavior nodes of the common paths in the user operation process. The behavior node recommendation method comprises the following specific steps: when any effective operation is carried out by a user, a recommendation frame appears below the system, the recommendation frame is sorted according to the appearance frequency of the common paths, the next effective behavior node in the common paths sequentially appears, and the effective behavior nodes comprise click contents which are effectively clicked and input contents which are effectively input.
(5) And counting the click frequency of the effective behavior nodes in the recommendation frame, recommending the segment behaviors of the common paths three before the click frequency in the last ten days to a system home page, recommending an optimized system to a user, and allowing the user to decide to save or replace.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments, or alternatives may be employed, by those skilled in the art, without departing from the spirit or ambit of the invention as defined in the appended claims.
Although the terms action path, action node, common path, etc. are used more often herein, the possibility of using other terms is not excluded. These terms are used merely to more conveniently describe and explain the nature of the present invention; they are to be construed as being without limitation to any additional limitations that may be imposed by the spirit of the present invention.
Claims (7)
1. A method for recommending optimized system solutions based on behavior big data analysis is characterized by comprising the following steps:
(1) the system automatically records the behavior path of the user in the system;
(2) analyzing the recorded behavior path, and the specific steps comprise:
(2.1) segmenting and simplifying each behavior path;
(2.2) comparing and finding similar segment behaviors, and then finding other similar behavior segments in the string by taking the similar segment behaviors as starting points;
(2.3) combining similar complete integral behavior segments;
the standard for segmenting each behavior path comprises segmenting according to events, conditions and results, and the standard for simplifying each behavior path comprises the steps of simplifying unnecessary operations between two effective operations and only reserving the effective operations to form a simplified new behavior path;
(3) integrating behavior paths according to the analysis result, simplifying and segmenting each behavior path, finding similar segment behaviors through comparison, prolonging and comparing along the behavior paths according to the segment behaviors, recording coincident nodes which exceed 10 times in the similar behavior paths, forming a standard path of the similar behavior paths by the summarized coincident nodes, comparing the similar path with the standard path, and regarding the similar path as the same path if the coincidence degree is more than or equal to 80%;
(4) optimizing the user operation step through a recommendation form according to the integration result;
(5) and recommending the optimized system to the user, and the user can save or replace the optimized system.
2. The method for recommending an optimized system scenario based on behavior big data analysis according to claim 1, wherein the behavior path in step 1 specifically comprises: and taking a system home page opened by a user as a behavior path starting point, recording a series of clicking and inputting operations after the user as a behavior node, and determining as a behavior user path end point when the time for the user to close the operation page and return to the system home page or stop operating the operation page and return to the home page is more than or equal to 30 min.
3. The method for recommending optimized system solutions based on behavior big data analysis according to claim 1, wherein the step 1 system automatically records behavior paths of users and takes the opening and closing of the system as starting and stopping time, and the behavior paths in the starting and stopping time are marked as the same time slot to be stored in the cloud platform.
4. The method for recommending an optimized system scenario based on behavioral big data analysis according to claim 1, wherein the effective operation comprises: clicking operation with feedback and input operation without deletion; optional operations include: the click operation is carried out at a blank position or a position without clicking keys, the click operation which does not carry out effective operation on the opened page after the page is opened is carried out, and the operation is immediately deleted after the page is input.
5. The method for recommending optimized system solutions based on behavior big data analysis according to claim 1, wherein the step 4 regards behavior paths with frequency more than 10 times in the last ten days as common paths, and performs behavior node recommendation on the common paths during the user operation process.
6. The method for recommending an optimized system solution based on behavior big data analysis according to claim 5, wherein the behavior node recommending comprises the following specific steps: when any effective operation is carried out by a user, a recommendation frame appears below the system, the recommendation frame is sorted according to the appearance frequency of the common paths, the next effective behavior node in the common paths sequentially appears, and the effective behavior nodes comprise click contents which are effectively clicked and input contents which are effectively input.
7. The method for recommending optimized system solutions based on behavior big data analysis according to claim 6, wherein the step 5 counts the click frequency of the effective behavior nodes in the recommendation box, recommends the segment behaviors of the common paths of the first three click frequencies in the last ten days to the system home page, recommends the optimized system to the user, and the user decides to save or replace by himself.
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| CN106293795A (en) * | 2015-06-09 | 2017-01-04 | 冠捷投资有限公司 | Startup method |
| CN106503022A (en) * | 2015-09-08 | 2017-03-15 | 北京邮电大学 | The method and apparatus for pushing recommendation information |
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| US8751481B2 (en) * | 2008-04-16 | 2014-06-10 | Iac Search & Media, Inc. | Adaptive multi-channel content selection with behavior-aware query analysis |
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| CN103544313A (en) * | 2013-11-04 | 2014-01-29 | 北京国双科技有限公司 | Data processing method and device for webpage recommendation |
| CN103823883A (en) * | 2014-03-06 | 2014-05-28 | 焦点科技股份有限公司 | Analysis method and system for website user access path |
| CN103823904A (en) * | 2014-03-19 | 2014-05-28 | 广东绿瘦健康信息咨询有限公司 | Webpage browsing path optimization method and system |
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