CN113076402A - Comment data analysis method and system, electronic device and storage medium - Google Patents
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Abstract
The invention provides a comment data analysis method, a comment data analysis system, electronic equipment and a storage medium, wherein the comment data analysis method comprises the following steps: acquiring a target judgment index tree of a user, wherein the target judgment index tree comprises a plurality of target judgment indexes; obtaining comment data in a set time period; performing text recognition on each comment in the comment data, and matching a target comment index corresponding to each comment; inputting each comment in the comment data into a trained satisfaction model to obtain the satisfaction grade of each comment; and obtaining the satisfaction data of each target evaluation comment index in a set time period according to the satisfaction level of the matched comment with each target evaluation comment index. The comment data analysis method of the invention realizes that the satisfaction degree of the user to the object to be commented and the change relation of the satisfaction degree are accurately obtained from the comment data; the commented object can obtain the satisfaction degree change relation in the specific time of combining the comment hotspot to adjust the business of the commented object.
Description
Technical Field
The invention relates to the field of data processing, in particular to a comment data analysis method, a comment data analysis system, electronic equipment and a storage medium.
Background
The existing society is a society developing at a high speed, has developed technology and information circulation, and people can communicate with each other more and more closely and live more and more conveniently. The data is collected at any time by the e-commerce terminal, the online shopping terminal or some data collection terminals (such as intelligent sound boxes). These data have the following 5V characteristics: large Volume (Volume), high speed (Velocity), multiple (Variety), high Value (Value), authenticity (Veracity).
In the prior art, the original reported data volume is huge, the number of reported data of the system can reach trillion, and the reported data format is disordered and lacks content dimension information, user portrait information and the like. The downstream cannot use the data directly. According to the business scene of information flow, the association of content dimensions, the association of user figures and the aggregation of various granularities are carried out, and how to provide real-time data which is convenient to use at downstream becomes a problem to be solved urgently.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present invention and therefore may include information that does not constitute prior art known to a person of ordinary skill in the art.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide a comment data analysis method, a comment data analysis system, electronic equipment and a storage medium, wherein the comment data analysis method accurately acquires the satisfaction degree of a user to a commented object and the change relation of the satisfaction degree from comment data; meanwhile, the commented object can obtain negative comment data in a specific time combined with the comment hotspot.
The embodiment of the invention also provides a comment data analysis method, which comprises the following steps:
s100: acquiring a target judgment index tree of a user, wherein the target judgment index tree comprises a plurality of target judgment indexes;
s200: obtaining comment data in a set time period;
s300: performing text recognition on each comment in the comment data, and matching a target comment index corresponding to each comment;
s400: inputting each comment in the comment data into a trained satisfaction model to obtain the satisfaction grade of each comment;
s500: and obtaining the satisfaction data of each target evaluation comment index in a set time period according to the satisfaction level of the matched comment with each target evaluation comment index.
According to some examples of the present invention, the S500 obtaining satisfaction data of each target evaluation comment index for a set period of time from the satisfaction level of the matched comment with the each target evaluation comment index includes the steps of:
the satisfaction level comprises positive comments, neutral comments and negative comments;
acquiring the number of positive comments matched with the target evaluation comment index and the total number of comments matched with the target evaluation comment index;
the ratio of the number of positive comments to the total number of comments matching the target evaluation comment index is the satisfaction data of each target evaluation comment index for the set time period.
According to some examples of the present invention, the step of S300 performing text recognition on each comment in the comment data and matching a target comment index corresponding to each comment includes the following steps:
performing word segmentation processing on each comment;
obtaining at least one keyword of each comment;
and matching target comment indexes corresponding to all comments according to the keywords.
According to some examples of this invention, the review data analysis method further comprises the steps of:
repeating the steps S200 to S500 to obtain satisfaction data of each target judgment comment index in a plurality of set time periods;
and obtaining the satisfaction degree change relation of each target evaluation and comment index in a plurality of set time periods.
According to some examples of the present invention, after obtaining the comment data in the set time period, S200 further includes the following steps:
performing word segmentation processing on each comment to obtain a plurality of words in each comment;
obtaining the word frequency-inverse text frequency of each vocabulary in the vocabulary of each comment;
and obtaining a plurality of hot words in the comment data according to the word frequency-inverse text frequency of each word.
According to some examples of this invention, the review data analysis method further comprises the steps of:
obtaining the correlation between each target evaluation and comment index and a plurality of hot words;
and pushing a satisfaction degree change relation of a plurality of target judgment and comment indexes which are relevant to a plurality of hot words to the user.
According to some examples of this invention, the review data analysis method further comprises the steps of:
s600: and obtaining the overall satisfaction data of the set time period according to the satisfaction data of each target evaluation and comment index of the set time period.
According to some examples of the invention, the step S600 of obtaining the overall satisfaction data of the set time period according to the satisfaction data of the respective target evaluation comment indexes of the set time period comprises the steps of:
obtaining the correlation between each target evaluation and comment index and a plurality of hot words;
determining the weight of each target evaluation comment index in a target evaluation index tree according to the correlation between each target evaluation comment index and a plurality of hot words;
and obtaining the overall satisfaction data according to the weight of each target evaluation and comment index and the satisfaction data of each target evaluation and comment index.
The embodiment of the invention also provides a comment data analysis system, which is used for realizing the steps of the comment data analysis method and comprises a data acquisition module, a text module and a satisfaction comment module, wherein:
the data acquisition module is used for acquiring a target judgment index tree of a user, wherein the target judgment index tree comprises a plurality of target judgment indexes; the comment data acquisition unit is used for acquiring comment data in a set time period;
the text module is used for performing text recognition on each comment in the comment data and matching a target comment index corresponding to each comment;
the satisfaction comment module is used for inputting all comments in the comment data into the trained satisfaction model to obtain the satisfaction levels of all comments, and obtaining the satisfaction data of all target evaluation comment indexes in a set time period according to the satisfaction levels of the comments matched with all the target evaluation comment indexes.
An embodiment of the present invention further provides an electronic device, including:
a processor;
a memory having stored therein executable instructions of the processor;
wherein the processor is configured to perform the steps of the review data analysis method via execution of the executable instructions.
An embodiment of the present invention also provides a computer-readable storage medium storing a program, characterized in that the program, when executed, implements the steps of the comment data analysis method.
The comment data analysis method provided by the invention realizes the analysis of big data, and accurately obtains the satisfaction degree of the user to the object to be commented and the change relation of the satisfaction degree from the comment data; meanwhile, the commented object can obtain the satisfaction degree change relation in the specific time of the comment hotspot to adjust the business of the commented object.
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Other features, objects, and advantages of the invention will be apparent from the following detailed description of non-limiting embodiments, which proceeds with reference to the accompanying drawings and which is incorporated in and constitutes a part of this specification, illustrating embodiments consistent with the present application and together with the description serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a flow chart of a review data analysis method in accordance with an embodiment of the present invention;
FIG. 2 is a diagram illustrating a relationship between satisfaction changes of target evaluation criteria according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating satisfaction change relationships corresponding to hot words according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a review data analysis system according to an embodiment of the invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the invention;
fig. 6 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
Fig. 1 is a flowchart of a comment data analysis method according to an embodiment of the present invention, and specifically, the comment data analysis method may include the following steps:
s100: acquiring a target judgment index tree of a user, wherein the target judgment index tree comprises a plurality of target judgment indexes;
s200: obtaining comment data in a set time period;
s300: performing text recognition on each comment in the comment data, and matching a target comment index corresponding to each comment;
s400: inputting each comment in the comment data into a trained satisfaction model to obtain the satisfaction grade of each comment;
s500: and obtaining the satisfaction data of each target evaluation comment index in a set time period according to the satisfaction level of the matched comment with each target evaluation comment index.
In the step S100 of the present invention, the target evaluation index tree obtained from the user may be an index tree of an industry to which the user belongs or a user-defined index tree, and the target evaluation index tree includes a plurality of target evaluation indexes. In some embodiments, the target evaluation index tree may further include a plurality of mapping relationships between the target evaluation indexes, and data of the evaluation index corresponding to the mapping relationship may be further obtained through the mapping relationships between the plurality of target evaluation indexes.
The time period in the step S200 may be set according to different user industries or requirements, and may be a week, a month, a quarter, a year, or the like. The comment data in the step S200 may be obtained from various data sources, for example, the comment data in a set time period is obtained from a user database, a business data system, a document database, a crawler database, or a voice database, and the comment data is preprocessed by data cleaning, missing value processing, abnormal value elimination, or the like.
Because the data source can be accessed, before the satisfaction data of each target evaluation comment index is obtained, the step S300 is used for matching each comment in the comment data with the corresponding target evaluation comment index, the step S400 is used for obtaining the satisfaction grade of each comment, and finally the step S500 is used for obtaining the satisfaction data of each target evaluation comment index in the set time period. The comment data analysis method provided by the invention can be used for accurately acquiring the satisfaction degree of the user on the object to be commented from the comment data.
In one embodiment, further, the step S500 of obtaining the satisfaction data of each target evaluation comment index of the set time period according to the satisfaction level of the matched comment with each target evaluation comment index includes the following steps:
the satisfaction level comprises positive comments, neutral comments and negative comments;
acquiring the number of positive comments matched with the target evaluation comment index and the total number of comments matched with the target evaluation comment index;
the ratio of the number of positive comments to the total number of comments matching the target evaluation comment index is the satisfaction data of each target evaluation comment index for the set time period. That is, in the above-described embodiment, the satisfaction data of the target evaluation comment index is set as the ratio of the number of positive comments to the total number of comments. In other embodiments, the satisfaction data for the target judgment review indicator may also be set to the number of positive reviews and the number of negative reviews. The satisfaction degree grade can adopt a system with more grades, and final positive evaluation or negative evaluation data can be obtained through the weight of each grade and the like.
It should be noted that, in S300, performing text recognition on each comment in the comment data, and matching a target comment index corresponding to each comment, the step may include the following steps:
performing word segmentation processing on each comment; the word segmentation processing can use Jieba word segmentation processing or HanLP word segmentation processing, and can also adopt a self-defined word segmentation algorithm.
Obtaining at least one keyword of each comment;
and matching target comment indexes corresponding to all comments according to the keywords. If the keyword in a comment is 'dinner plate' or 'seafood', the comment is matched with the index 'dining'.
In other embodiments, the review data analysis method of the present invention may further include the steps of:
repeating the steps S200 to S500 to obtain satisfaction data of each target judgment comment index in a plurality of set time periods; and obtaining the satisfaction degree change relation of each target evaluation and comment index in a plurality of set time periods. Fig. 2 is a graph illustrating a relationship between satisfaction changes of target evaluation indicators according to an embodiment of the present invention, wherein a time period set by a user is one week. The comment data analysis method realizes dynamic reflection of the change of the satisfaction degree of the commented object in the comment through the steps, and if the commented object is the service of a merchant, the merchant can improve the service of the merchant according to the change relation of the satisfaction degree of the target comment index.
In other embodiments, after obtaining the comment data in the set time period, the step S200 may further include the following steps:
performing word segmentation processing on each comment to obtain a plurality of words in each comment; the word segmentation processing can use Jieba word segmentation processing or HanLP word segmentation processing, and can also adopt a self-defined word segmentation algorithm.
Obtaining the word frequency-inverse text frequency of each vocabulary in the vocabulary of each comment;
and obtaining a plurality of hot words in the comment data according to the word frequency-inverse text frequency of each word. If the object being reviewed is a hotel, the possible hot words available are "location", "price", "dining", "hygiene", etc. The above steps are used for counting the participles of each comment, so that the hotspot of the comment in the set time period is obtained. The number of hot words can be set according to actual requirements of the user in the industry and the like.
The comment data analysis method of the present invention may further include the steps of:
obtaining the correlation between each target evaluation and comment index and a plurality of hot words; the step can be regarded as a process that the hot words are matched with the corresponding target evaluation and comment indexes;
and pushing a satisfaction degree change relation of a plurality of target judgment and comment indexes which are relevant to a plurality of hot words to the user. In the process, the target evaluation and comment indexes are combined with the comment hotspots, the satisfaction degree data of the target evaluation and comment indexes belonging to the comment hotspots are selected and pushed to the user, and the user can more accurately know the target evaluation and comment indexes needing attention in the process.
It should be noted that, after the correlation between each target evaluation and review index and a plurality of hot words is obtained, the satisfaction data corresponding to the plurality of hot words can be obtained through the satisfaction data of each target evaluation and review index. Correspondingly, obtaining satisfaction degree data corresponding to a plurality of hot spot vocabularies; and acquiring the satisfaction degree change relation corresponding to a plurality of hot words in a plurality of set time periods, as shown in fig. 3. The business can adjust the business according to the satisfaction degree change relation corresponding to the hot words.
The comment data analysis method of the present invention may further include the steps of:
s600: and obtaining the overall satisfaction data of the set time period according to the satisfaction data of each target evaluation and comment index of the set time period. The step of obtaining the overall satisfaction data of the set time period according to the satisfaction data of each target evaluation and review index of the set time period in S600 may further include the steps of:
obtaining the correlation between each target evaluation and comment index and a plurality of hot words;
determining the weight of each target evaluation comment index in a target evaluation index tree according to the correlation between each target evaluation comment index and a plurality of hot words;
and obtaining the overall satisfaction data according to the weight of each target evaluation and comment index and the satisfaction data of each target evaluation and comment index. The overall satisfaction data of the set time period is related to the satisfaction data of each target evaluation and review index in the time period, and the weight of each target evaluation and review index is determined according to the relevance of each target evaluation and review index and the hot words, so that the obtained overall satisfaction data can be more accurately reflected to the evaluation data.
Similarly, the method of the invention can also repeat the steps from S200 to S600 to obtain the overall satisfaction data of each target evaluation comment index in a plurality of set time periods; and acquiring the overall satisfaction degree change relation of each target evaluation and comment index in a plurality of set time periods.
The embodiment of the present invention further provides a comment data analysis system, configured to implement the steps of the comment data analysis method, where fig. 4 is a schematic structural diagram of the comment data analysis system according to the embodiment of the present invention, and the comment data analysis system includes a data acquisition module M100, a text module M200, and a satisfaction comment module M300, where:
the data obtaining module M100 is configured to obtain a target evaluation index tree of a user, where the target evaluation index tree includes a plurality of target evaluation indexes and a plurality of mapping relationships of the target evaluation indexes; the comment data acquisition unit is used for acquiring comment data in a set time period;
the text module M200 is configured to perform text recognition on each comment in the comment data, and match a target comment index corresponding to each comment;
the satisfaction comment module M300 is configured to input each comment in the comment data into a trained satisfaction model to obtain a satisfaction level of each comment, and obtain satisfaction data of each target evaluation comment index in a set time period according to the satisfaction level of the comment matched with each target evaluation comment index.
The functional implementation manner of each functional module in the comment data analysis system of the embodiment can be implemented by adopting the specific implementation manner of each step in the comment data analysis method. For example, the data obtaining module M100, the text module M200, and the satisfaction comment module M300 may respectively implement their functions by adopting the specific implementation manners of the above steps S100 to S500, which are not described herein again.
An electronic device 600 according to this embodiment of the invention is described below with reference to fig. 5. The electronic device 600 shown in fig. 5 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 5, the electronic device 600 is embodied in the form of a general purpose computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one memory unit 620, a bus 630 connecting the different platform components (including the memory unit 620 and the processing unit 610), a display unit 640, etc.
Wherein the storage unit stores program code which can be executed by the processing unit 610 such that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention as described in the above-mentioned method section of the present specification. For example, processing unit 610 may perform the steps as shown in fig. 1.
The storage unit 620 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)6201 and/or a cache memory unit 6202, and may further include a read-only memory unit (ROM) 6203.
The memory unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 600, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 600 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 650. Also, the electronic device 600 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via the bus 630. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, to name a few.
An embodiment of the present invention further provides a computer-readable storage medium for storing a program, where the program is executed to implement the steps of the comment data analysis method. In some possible embodiments, the various aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to the various exemplary embodiments of the invention described in the method part above of this description when said program product is run on the terminal device.
Referring to fig. 6, a program product 800 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, the present invention provides a comment data analysis method, a comment data analysis system, an electronic device, and a storage medium, where the method includes: acquiring a target judgment index tree of a user, wherein the target judgment index tree comprises a plurality of target judgment indexes and a mapping relation of the plurality of target judgment indexes; obtaining comment data in a set time period; performing text recognition on each comment in the comment data, and matching a target comment index corresponding to each comment; inputting each comment in the comment data into a trained satisfaction model to obtain the satisfaction grade of each comment; and obtaining the satisfaction data of each target evaluation comment index in a set time period according to the satisfaction level of the matched comment with each target evaluation comment index. The comment data analysis method of the invention realizes that the satisfaction degree of the user to the object to be commented and the change relation of the satisfaction degree are accurately obtained from the comment data; the commented object can obtain the satisfaction degree change relation in the specific time of combining the comment hotspot to adjust the business of the commented object.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application 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 application 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. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Claims (11)
1. A comment data analysis method is characterized by comprising the following steps:
s100: acquiring a target judgment index tree of a user, wherein the target judgment index tree comprises a plurality of target judgment indexes;
s200: obtaining comment data in a set time period;
s300: performing text recognition on each comment in the comment data, and matching a target comment index corresponding to each comment;
s400: inputting each comment in the comment data into a trained satisfaction model to obtain the satisfaction grade of each comment;
s500: and obtaining the satisfaction data of each target evaluation comment index in a set time period according to the satisfaction level of the matched comment with each target evaluation comment index.
2. The comment data analysis method of claim 1, wherein the step S500 of obtaining the satisfaction data of each target evaluation comment index for a set period of time from the satisfaction level of the comment matching with the each target evaluation comment index comprises the steps of:
the satisfaction level comprises positive comments, neutral comments and negative comments;
acquiring the number of positive comments matched with the target evaluation comment index and the total number of comments matched with the target evaluation comment index;
the ratio of the number of positive comments to the total number of comments matching the target evaluation comment index is the satisfaction data of each target evaluation comment index for the set time period.
3. The comment data analysis method of claim 1, wherein the step of S300 performing text recognition on each comment in the comment data and matching a target comment index corresponding to each comment comprises the steps of:
performing word segmentation processing on each comment;
obtaining at least one keyword of each comment;
and matching target comment indexes corresponding to all comments according to the keywords.
4. The review data analysis method of claim 1, further comprising the steps of:
repeating the steps S200 to S500 to obtain satisfaction data of each target judgment comment index in a plurality of set time periods;
and obtaining the satisfaction degree change relation of each target evaluation and comment index in a plurality of set time periods.
5. The comment data analysis method of claim 4, wherein after the comment data within the set time period is acquired at S200, the method further comprises the following steps:
performing word segmentation processing on each comment to obtain a plurality of words in each comment;
obtaining the word frequency-inverse text frequency of each vocabulary in the vocabulary of each comment;
and obtaining a plurality of hot words in the comment data according to the word frequency-inverse text frequency of each word.
6. The review data analysis method of claim 5, further comprising the steps of:
obtaining the correlation between each target evaluation and comment index and a plurality of hot words;
and pushing a satisfaction degree change relation of a plurality of target judgment and comment indexes which are relevant to a plurality of hot words to the user.
7. The review data analysis method of claim 5, further comprising the steps of:
s600: and obtaining the overall satisfaction data of the set time period according to the satisfaction data of each target evaluation and comment index of the set time period.
8. The comment data analysis method of claim 7, wherein the step S600 of obtaining the overall satisfaction data of the set time period from the satisfaction data of the respective target comment indicators of the set time period includes the steps of:
obtaining the correlation between each target evaluation and comment index and a plurality of hot words;
determining the weight of each target evaluation comment index in a target evaluation index tree according to the correlation between each target evaluation comment index and a plurality of hot words;
and obtaining the overall satisfaction data according to the weight of each target evaluation and comment index and the satisfaction data of each target evaluation and comment index.
9. A comment data analysis system for implementing the steps of the comment data analysis method of any one of claims 1 to 8, characterized by comprising a data acquisition module, a text module, and a satisfaction comment module, wherein:
the data acquisition module is used for acquiring a target judgment index tree of a user, wherein the target judgment index tree comprises a plurality of target judgment indexes; the comment data acquisition unit is used for acquiring comment data in a set time period;
the text module is used for performing text recognition on each comment in the comment data and matching a target comment index corresponding to each comment;
the satisfaction comment module is used for inputting all comments in the comment data into the trained satisfaction model to obtain the satisfaction levels of all comments, and obtaining the satisfaction data of all target evaluation comment indexes in a set time period according to the satisfaction levels of the comments matched with all the target evaluation comment indexes.
10. An electronic device, comprising:
a processor;
a memory having stored therein executable instructions of the processor;
wherein the processor is configured to perform the steps of the review data analysis method of any of claims 1-8 via execution of the executable instructions.
11. A computer-readable storage medium storing a program, wherein the program, when executed by a processor, implements the steps of the comment data analyzing method of any one of claims 1 to 8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113836410A (en) * | 2021-09-22 | 2021-12-24 | 中国第一汽车股份有限公司 | Vehicle sound quality evaluation method, device, evaluation equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106126499A (en) * | 2016-06-22 | 2016-11-16 | 青岛海信传媒网络技术有限公司 | User satisfaction and loyalty analyze method and device |
| CN108009726A (en) * | 2017-12-04 | 2018-05-08 | 上海财经大学 | A kind of things evaluation system of combination user comment |
| CN111080055A (en) * | 2019-11-06 | 2020-04-28 | 邱素容 | Hotel scoring method, hotel recommendation method, electronic device and storage medium |
| WO2021016760A1 (en) * | 2019-07-26 | 2021-02-04 | 深圳市欢太科技有限公司 | Application pushing method and related device |
-
2021
- 2021-04-13 CN CN202110393612.1A patent/CN113076402A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106126499A (en) * | 2016-06-22 | 2016-11-16 | 青岛海信传媒网络技术有限公司 | User satisfaction and loyalty analyze method and device |
| CN108009726A (en) * | 2017-12-04 | 2018-05-08 | 上海财经大学 | A kind of things evaluation system of combination user comment |
| WO2021016760A1 (en) * | 2019-07-26 | 2021-02-04 | 深圳市欢太科技有限公司 | Application pushing method and related device |
| CN111080055A (en) * | 2019-11-06 | 2020-04-28 | 邱素容 | Hotel scoring method, hotel recommendation method, electronic device and storage medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113836410A (en) * | 2021-09-22 | 2021-12-24 | 中国第一汽车股份有限公司 | Vehicle sound quality evaluation method, device, evaluation equipment and storage medium |
| CN113836410B (en) * | 2021-09-22 | 2024-03-15 | 中国第一汽车股份有限公司 | Vehicle sound quality evaluation method, device, evaluation equipment and storage medium |
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