CN113282556A - Data mining method and system for software use log - Google Patents

Data mining method and system for software use log Download PDF

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Publication number
CN113282556A
CN113282556A CN202011352399.1A CN202011352399A CN113282556A CN 113282556 A CN113282556 A CN 113282556A CN 202011352399 A CN202011352399 A CN 202011352399A CN 113282556 A CN113282556 A CN 113282556A
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log information
software
registration
information
registration log
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顾黎明
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Suzhou Lyudian Information Technology Co ltd
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Suzhou Lyudian Information Technology Co ltd
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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
    • G06F16/10—File systems; File servers
    • G06F16/18—File system types
    • G06F16/1805—Append-only file systems, e.g. using logs or journals to store data
    • G06F16/1815—Journaling file systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F16/00 and subgroups
    • G06F2216/03—Data mining

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  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
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  • General Engineering & Computer Science (AREA)
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Abstract

The embodiment of the invention provides a data mining method and a system for software use logs, which respectively extract set log element information of software label registration log information and software label non-registration log information in the software use log information to form first software label registration log information and first software label non-registration log information, integrate complete first mining log information, respectively extract other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information, integrate complete second mining log information, and perform software portrait mining on the first mining log information and the second mining log information in a time-sharing manner to obtain a target software portrait. Therefore, by distinguishing idle running information and non-idle running information and based on the operation of data fusion by excavation and waiting for excavation, the excavation difficulty can be reduced and the excavation efficiency can be improved.

Description

Data mining method and system for software use log
Technical Field
The invention relates to the technical field of data mining of software use logs, in particular to a data mining method and system of software use logs.
Background
At present, the data structure of the log information used by the software collected actually is complex, so that the mining difficulty is high and the efficiency is low.
Disclosure of Invention
In view of this, embodiments of the present invention provide a data mining method and system for a software usage log, which can reduce mining difficulty and improve mining efficiency.
According to an aspect of the embodiments of the present invention, there is provided a data mining method for a software usage log, applied to a server, where the server is communicatively connected to a software service terminal, the method including:
according to the software use log information transmitted by each software service terminal, respectively extracting the software label registration log information and the set log element information of the software label non-registration log information in the software use log information to form first software label registration log information and first software label non-registration log information;
taking the first software label registration log information as log information to be mined, taking the first software label non-registration log information as log information to be fused, fusing complete first mining log information, and respectively extracting other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information;
and taking the second software label registered log information as log information to be mined, taking the second software label non-registered log information as log information to be fused, fusing complete second mined log information, and mining the software portrait of the first mined log information and the second mined log information in a time-sharing manner to obtain a target software portrait.
In one possible example, the method further comprises:
and the first mining log information and the second mining log information which contain all the information of the software label non-registration log information are formed in a data processing mode of extracting and combining the software label registration log information and the software label non-registration log information, and then the first mining log information and the second mining log information are output in a time-sharing mode to output the mining log information.
In one possible example, the step of extracting the setting log element information of the software tag registration log information and the software tag non-registration log information to form the first software tag registration log information and the first software tag non-registration log information, respectively, includes:
traversing and extracting set log element information of software label registration log information and software label non-registration log information to form first software label registration log information and first software label non-registration log information;
the step of extracting other set log element information of the software tag registration log information and the software tag non-registration log information respectively to form second software tag registration log information and second software tag non-registration log information includes:
and traversing and extracting other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
In one possible example, the step of traversing to extract the set log element information of the software tag registration log information and the software tag non-registration log information to form the first software tag registration log information and the first software tag non-registration log information includes:
respectively extracting mineable information of software label registration log information and software label non-registration log information to form first software label registration log information and first software label non-registration log information;
the step of traversing and extracting other set log element information of the software tag registration log information and the software tag non-registration log information to form second software tag registration log information and second software tag non-registration log information includes:
and respectively extracting information to be mined of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
In one possible example, the step of traversing to extract the set log element information of the software tag registration log information and the software tag non-registration log information to form the first software tag registration log information and the first software tag non-registration log information includes:
respectively extracting the information to be mined of the diggable information of the software label registration log information and the information to be mined of the software label non-registration log information to form first software label registration log information and first software label non-registration log information;
the step of traversing and extracting other set log element information of the software tag registration log information and the software tag non-registration log information to form second software tag registration log information and second software tag non-registration log information includes:
and respectively extracting the information to be mined of the software label registration log information and the mineable information of the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
According to another aspect of the embodiments of the present invention, there is provided a data mining system for a software usage log, applied to a server, the server being in communication connection with a software service terminal, the system including:
the extraction module is used for respectively extracting the software label registration log information and the set log element information of the software label non-registration log information in the software use log information according to the software use log information transmitted by each software service terminal to form first software label registration log information and first software label non-registration log information;
the first fusion module is used for taking the first software label registration log information as log information to be mined, taking the first software label non-registration log information as the log information to be fused, fusing complete first mining log information, and respectively extracting other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information;
and the second fusion module is used for taking the second software label registered log information as log information to be mined, taking the second software label unregistered log information as the log information to be fused, fusing complete second mined log information, and mining the software portrait of the first mined log information and the second mined log information in a time-sharing manner to obtain a target software portrait.
According to another aspect of the embodiments of the present invention, there is provided a readable storage medium, on which a computer program is stored, which when executed by a processor can perform the steps of the above-mentioned data mining method for software usage logs.
Compared with the prior art, the data mining method and system for the software use log provided by the embodiment of the invention respectively extract the set log element information of the software tag registration log information and the software tag non-registration log information in the software use log information to form the first software tag registration log information and the first software tag non-registration log information, then integrate the first mining log information, respectively extract other set log element information of the software tag registration log information and the software tag non-registration log information, form the second software tag registration log information and the second software tag non-registration log information, integrate the second mining log information, and perform software portrait mining on the first mining log information and the second mining log information in a time-sharing manner to obtain the target software. Therefore, by distinguishing idle running information and non-idle running information and based on the operation of data fusion by excavation and waiting for excavation, the excavation difficulty can be reduced and the excavation efficiency can be improved.
In order to make the aforementioned objects, features and advantages of the embodiments of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 illustrates a component diagram of a server provided by an embodiment of the invention;
FIG. 2 is a flow chart illustrating a data mining method for a software usage log according to an embodiment of the present invention;
FIG. 3 shows a functional block diagram of a data mining system for software usage logs provided by an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood by the scholars in the technical field, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the 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, 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.
The terms "first," "second," "third," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 shows an exemplary component schematic of a server 100. The server 100 may include one or more processors 104, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The server 100 may also include any storage media 106 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, storage medium 106 may include any one or more of the following in combination: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any storage medium may use any technology to store information. Further, any storage medium may provide volatile or non-volatile retention of information. Further, any storage medium may represent a fixed or removable component of server 100. In one case, when the processor 104 executes the associated instructions stored in any storage medium or combination of storage media, the server 100 may perform any of the operations of the associated instructions. The server 100 further comprises one or more drive units 108 for interacting with any storage medium, such as a hard disk drive unit, an optical disk drive unit, etc.
The server 100 also includes input/output 110 (I/O) for receiving various inputs (via input unit 112) and for providing various outputs (via output unit 114)). One particular output mechanism may include a presentation device 116 and an associated Graphical User Interface (GUI) 118. The server 100 may also include one or more network interfaces 120 for exchanging data with other devices via one or more communication units 122. One or more communication buses 124 couple the above-described components together.
The communication unit 122 may be implemented in any manner, such as over a local area network, a wide area network (e.g., the internet), a point-to-point connection, etc., or any combination thereof. The communication unit 122 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers 100, and so forth, governed by any protocol or combination of protocols.
Fig. 2 is a flowchart illustrating a data mining method for a software usage log according to an embodiment of the present invention, which may be executed by the server 100 shown in fig. 1, and the detailed steps of the data mining method for a software usage log are described as follows.
Step S110, according to the software usage log information transmitted by each software service terminal, respectively extracting the set log element information of the software tag registration log information and the software tag non-registration log information in the software usage log information, and forming first software tag registration log information and first software tag non-registration log information.
Step S120, using the first software label registration log information as log information to be mined, using the first software label non-registration log information as log information to be fused, fusing complete first mining log information, and respectively extracting other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
And step S130, using the second software label registered log information as log information to be mined, using the second software label non-registered log information as log information to be fused, fusing complete second mined log information, and mining the software portrait of the first mined log information and the second mined log information in a time-sharing manner to obtain a target software portrait.
Based on the above steps, in this embodiment, the software uses the set log element information of the software tag registration log information and the software tag non-registration log information in the log information to respectively extract the first software tag registration log information and the first software tag non-registration log information, then the complete first mining log information is fused, and the other set log element information of the software tag registration log information and the software tag non-registration log information is respectively extracted to form the second software tag registration log information and the second software tag non-registration log information, so as to fuse the complete second mining log information, and perform software portrait mining on the first mining log information and the second mining log information in a time-sharing manner, thereby obtaining the target software portrait. Therefore, by distinguishing idle running information and non-idle running information and based on the operation of data fusion by excavation and waiting for excavation, the excavation difficulty can be reduced and the excavation efficiency can be improved.
In a possible example, the present embodiment may further form the first mining log information and the second mining log information including all information of the software tag non-registration log information by a data processing manner of extracting and combining the software tag registration log information and the software tag non-registration log information, and then output the first mining log information and the second mining log information in a time-sharing manner, and output the mining log information.
In one possible example, for step S110, the first software tag registration log information and the first software tag non-registration log information may be formed by traversing the set log element information of the extracted software tag registration log information and software tag non-registration log information.
For example, the first software tag registration log information and the first software tag non-registration log information may be formed by extracting mineable information of the software tag registration log information and the software tag non-registration log information, respectively.
For example, the first software tag registration log information and the first software tag non-registration log information may be formed by extracting the mineable information of the software tag registration log information and the information to be mined of the software tag non-registration log information.
For step S120, the second software tag registration log information and the second software tag non-registration log information may be formed by traversing other set log element information that extracts the software tag registration log information and the software tag non-registration log information.
For example, the information to be mined of the software tag registration log information and the software tag non-registration log information may be extracted to form the second software tag registration log information and the second software tag non-registration log information, respectively.
For example, the information to be mined in the software tag registration log information and the mineable information in the software tag non-registration log information may be extracted to form the second software tag registration log information and the second software tag non-registration log information.
Fig. 3 shows a functional block diagram of the data mining system 200 for software usage logs according to an embodiment of the present invention, where the functions implemented by the data mining system 200 for software usage logs may correspond to the steps executed by the foregoing method. The data mining system 200 for using logs by software may be understood as the server 100, or a processor of the server 100, or may be understood as a component that is independent from the server 100 or the processor and implements the functions of the present invention under the control of the server 100, as shown in fig. 3, and the functions of the functional modules of the data mining system 200 for using logs by software are described in detail below.
An extracting module 210, configured to extract, according to the software usage log information transmitted by each software service terminal, set log element information of software tag registration log information and software tag non-registration log information in the software usage log information, respectively, to form first software tag registration log information and first software tag non-registration log information.
The first fusion module 220 is configured to use the first software tag registration log information as log information to be mined, use the first software tag non-registration log information as log information to be fused, fuse complete first mined log information, and respectively extract other set log element information of the software tag registration log information and the software tag non-registration log information to form second software tag registration log information and second software tag non-registration log information.
And the second fusion module 230 is configured to use the second software tag registered log information as log information to be mined, use the second software tag unregistered log information as log information to be fused, fuse complete second mined log information, and perform software portrait mining on the first mined log information and the second mined log information in a time-sharing manner to obtain a target software portrait.
In a possible example, the extraction module 210 is further configured to form the first mining log information and the second mining log information including all information of the software tag non-registration log information by a data processing manner of extracting and combining the software tag registration log information and the software tag non-registration log information, and then output the first mining log information and the second mining log information in a time-sharing manner, so as to output the mining log information.
In one possible example, the extraction module 210 extracts the setting log element information of the software tag registration log information and the software tag non-registration log information to form first software tag registration log information and first software tag non-registration log information by:
and traversing and extracting the set log element information of the software label registration log information and the software label non-registration log information to form first software label registration log information and first software label non-registration log information.
In one possible example, the extraction module 210 extracts other setting log element information of the software tag registration log information and the software tag non-registration log information to form second software tag registration log information and second software tag non-registration log information by:
and traversing and extracting other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
In one possible example, the extraction module 210 forms the first software tag registration log information and the first software tag non-registration log information by traversing the set log element information of the extracted software tag registration log information and software tag non-registration log information by:
and respectively extracting mineable information of the software label registration log information and the software label non-registration log information to form first software label registration log information and first software label non-registration log information.
In one possible example, the extraction module 210 forms the second software tag registration log information and the second software tag non-registration log information by traversing other set log element information of the extracted software tag registration log information and software tag non-registration log information by:
and respectively extracting information to be mined of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
In one possible example, the extraction module 210 forms the first software tag registration log information and the first software tag non-registration log information by traversing the set log element information of the extracted software tag registration log information and software tag non-registration log information by:
and respectively extracting the information to be mined of the diggable information of the software label registration log information and the information to be mined of the software label non-registration log information to form first software label registration log information and first software label non-registration log information.
In one possible example, the extraction module 210 forms the second software tag registration log information and the second software tag non-registration log information by traversing other set log element information of the extracted software tag registration log information and software tag non-registration log information by:
and respectively extracting the information to be mined of the software label registration log information and the mineable information of the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
Alternatively, all or part of the implementation may be in software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
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 drawing credit or debit acknowledgement in the claims should not be construed as limiting the claim concerned.

Claims (10)

1. A data mining method for software use logs is applied to a server, the server is in communication connection with a software service terminal, and the method comprises the following steps:
according to the software use log information transmitted by each software service terminal, respectively extracting the software label registration log information and the set log element information of the software label non-registration log information in the software use log information to form first software label registration log information and first software label non-registration log information;
taking the first software label registration log information as log information to be mined, taking the first software label non-registration log information as log information to be fused, fusing complete first mining log information, and respectively extracting other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information;
and taking the second software label registered log information as log information to be mined, taking the second software label non-registered log information as log information to be fused, fusing complete second mined log information, and mining the software portrait of the first mined log information and the second mined log information in a time-sharing manner to obtain a target software portrait.
2. The method of data mining of software usage logs of claim 1, further comprising:
and the first mining log information and the second mining log information which contain all the information of the software label non-registration log information are formed in a data processing mode of extracting and combining the software label registration log information and the software label non-registration log information, and then the first mining log information and the second mining log information are output in a time-sharing mode to output the mining log information.
3. The method for mining data of a software usage log according to claim 1, wherein the step of extracting set log element information of software tag registration log information and software tag non-registration log information to form first software tag registration log information and first software tag non-registration log information, respectively, includes:
traversing and extracting set log element information of software label registration log information and software label non-registration log information to form first software label registration log information and first software label non-registration log information;
the step of extracting other set log element information of the software tag registration log information and the software tag non-registration log information respectively to form second software tag registration log information and second software tag non-registration log information includes:
and traversing and extracting other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
4. The data mining method of software usage log according to claim 3, wherein the step of forming the first software tag registration log information and the first software tag non-registration log information by extracting the set log element information of the software tag registration log information and the software tag non-registration log information through traversal comprises:
respectively extracting mineable information of software label registration log information and software label non-registration log information to form first software label registration log information and first software label non-registration log information;
the step of traversing and extracting other set log element information of the software tag registration log information and the software tag non-registration log information to form second software tag registration log information and second software tag non-registration log information includes:
and respectively extracting information to be mined of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
5. The data mining method of software usage log according to claim 3, wherein the step of forming the first software tag registration log information and the first software tag non-registration log information by extracting the set log element information of the software tag registration log information and the software tag non-registration log information through traversal comprises:
respectively extracting the information to be mined of the diggable information of the software label registration log information and the information to be mined of the software label non-registration log information to form first software label registration log information and first software label non-registration log information;
the step of traversing and extracting other set log element information of the software tag registration log information and the software tag non-registration log information to form second software tag registration log information and second software tag non-registration log information includes:
and respectively extracting the information to be mined of the software label registration log information and the mineable information of the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
6. A data mining system for software usage logs is applied to a server, the server is in communication connection with a software service terminal, and the system comprises:
the extraction module is used for respectively extracting the software label registration log information and the set log element information of the software label non-registration log information in the software use log information according to the software use log information transmitted by each software service terminal to form first software label registration log information and first software label non-registration log information;
the first fusion module is used for taking the first software label registration log information as log information to be mined, taking the first software label non-registration log information as the log information to be fused, fusing complete first mining log information, and respectively extracting other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information;
and the second fusion module is used for taking the second software label registered log information as log information to be mined, taking the second software label unregistered log information as the log information to be fused, fusing complete second mined log information, and mining the software portrait of the first mined log information and the second mined log information in a time-sharing manner to obtain a target software portrait.
7. The system of claim 6, wherein the extraction module is further configured to extract and combine the software tag registration log information and the software tag non-registration log information to form the first mining log information and the second mining log information that include all the information of the software tag non-registration log information, and then output the first mining log information and the second mining log information in a time-sharing manner to output the mining log information.
8. The data mining system of software usage log of claim 6, wherein the extraction module extracts the set log element information of the software tag registration log information and the software tag non-registration log information, respectively, to form first software tag registration log information and first software tag non-registration log information by:
traversing and extracting set log element information of software label registration log information and software label non-registration log information to form first software label registration log information and first software label non-registration log information;
the extraction module respectively extracts other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information by the following modes:
and traversing and extracting other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
9. The data mining system of software usage log of claim 8, wherein the extraction module forms the first software tag registration log information and the first software tag non-registration log information by traversing the set log element information of the extracted software tag registration log information and software tag non-registration log information by:
respectively extracting mineable information of software label registration log information and software label non-registration log information to form first software label registration log information and first software label non-registration log information;
the extraction module traversably extracts other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information in the following way:
and respectively extracting information to be mined of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
10. The data mining system of software usage log of claim 8, wherein the extraction module forms the first software tag registration log information and the first software tag non-registration log information by traversing the set log element information of the extracted software tag registration log information and software tag non-registration log information by:
respectively extracting the information to be mined of the diggable information of the software label registration log information and the information to be mined of the software label non-registration log information to form first software label registration log information and first software label non-registration log information;
the extraction module traversably extracts other set log element information of the software label registration log information and the software label non-registration log information to form second software label registration log information and second software label non-registration log information in the following way:
and respectively extracting the information to be mined of the software label registration log information and the mineable information of the software label non-registration log information to form second software label registration log information and second software label non-registration log information.
CN202011352399.1A 2020-11-27 2020-11-27 Data mining method and system for software use log Withdrawn CN113282556A (en)

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