A method, device, electronic device and storage medium for processing scenic spot review data

Abstract

The embodiment of the present invention discloses a method, device, electronic device and storage medium for processing scenic spot comment data. The method comprises: determining the current comment keyword in the current user comment data; determining the current keyword type to which the current comment keyword belongs from at least two candidate keyword types; determining the reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined according to the historical user comment data. By running the technical solution provided by the embodiment of the present invention, the problem that tourists mainly obtain other tourists' evaluations of the scenic spot from the comment area corresponding to the scenic spot, and cannot actively understand the corresponding information of the scenic spot, and therefore the acquisition of scenic spot information is one-sided and ambiguous can be solved, thereby achieving the effect of improving the accuracy and pertinence of scenic spot information acquisition.

Description

Technical Field

[0001] The embodiments of the present invention relate to computer technology, and in particular to a scenic spot review data processing method, device, electronic device and storage medium. Background Art

[0002] With the development of transportation and the improvement of living standards, more and more people choose tourism as a travel option, and the reputation of scenic spots has become an important reference for tourists when choosing a travel destination.

[0003] In the prior art, tourists mainly obtain other tourists' comments on the scenic spot from the comment area corresponding to the scenic spot, and cannot actively learn the corresponding information of the scenic spot. Therefore, the acquisition of scenic spot information is one-sided and vague. Summary of the invention

[0004] The embodiments of the present invention provide a scenic spot review data processing method, device, electronic device and storage medium to improve the accuracy and pertinence of scenic spot information acquisition.

[0005] In a first aspect, an embodiment of the present invention provides a method for processing scenic spot review data, the method comprising:

[0006] Determine the current comment keyword in the current user comment data;

[0007] Determine the current keyword type to which the current comment keyword belongs from at least two candidate keyword types;

[0008] Determine reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined according to the historical user comment data.

[0009] In a second aspect, an embodiment of the present invention further provides a scenic spot review data processing device, the device comprising:

[0010] A current comment keyword determination module is used to determine the current comment keywords in the current user comment data;

[0011] A current keyword type determination module, used to determine the current keyword type to which the current comment keyword belongs from at least two candidate keyword types;

[0012] A reply information determination module is used to determine reply information to the user comment data based on the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined based on historical user comment data.

[0013] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0014] one or more processors;

[0015] a storage device for storing one or more programs,

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the scenic spot review data processing method as described above.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the scenic spot review data processing method as described above.

[0018] The embodiment of the present invention determines the current comment keyword in the current user comment data; determines the current keyword type to which the current comment keyword belongs from at least two candidate keyword types; and determines the reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined according to the historical user comment data. This solves the problem that tourists mainly obtain other tourists' evaluations of scenic spots from the comment area corresponding to the scenic spot, and cannot actively understand the corresponding information of the scenic spot, so the acquisition of scenic spot information is one-sided and vague, thereby achieving the effect of improving the accuracy and pertinence of scenic spot information acquisition. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flowchart of a scenic spot review data processing method provided in Embodiment 1 of the present invention;

[0020] Figure 2 A flowchart of a scenic spot review data processing method provided in Embodiment 2 of the present invention;

[0021] Figure 3 A schematic diagram of the structure of a scenic spot review data processing device provided in Embodiment 3 of the present invention;

[0022] Figure 4 A schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0023] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0024] Embodiment 1

[0025] Figure 1 This is a flowchart of a scenic spot comment data processing method provided in the first embodiment of the present invention. This embodiment is applicable to the case of replying to a user's comment on a scenic spot. The method can be executed by the scenic spot comment data processing device provided in the embodiment of the present invention, and the device can be implemented in software and / or hardware. Figure 1 The scenic spot review data processing method provided in this embodiment includes:

[0026] Step 110: Determine the current comment keywords in the current user comment data.

[0027] The current user comment data is the comment data posted by the user on the scenic spot, which can be text data, voice or picture data; the acquisition method can be obtained from the scenic spot comment area, which is not limited in this embodiment. The current comment keywords are words with practical meaning in the current comment. For example, if the comment is "the ticket price of the scenic spot is very affordable", then "scenic spot", "ticket price" and "affordable" may be keywords.

[0028] The Kettle tool may be used to clean and filter the current user comment data and then perform word segmentation to obtain keywords, which is not limited in this embodiment.

[0029] In this embodiment, optionally, determining the current comment keyword in the current user comment data includes:

[0030] Filtering the current user comment data according to a pre-constructed stop word list;

[0031] The current comment keywords are determined by performing word segmentation processing on the filtered current user comment data.

[0032] Among them, the stop word list is a table composed of certain characters or words that are automatically filtered out when processing text data. Frequently used irregular characters and meaningless words can be summarized in advance to form a stop word list.

[0033] The current user comment data is filtered in text form through a stop word list, and the filtered current user comment data is segmented, and the words obtained after segmentation are used as keywords. Among them, the segmentation method can be Jieba segmentation, which is not limited in this embodiment. The current comment data is filtered through a stop word list, thereby improving the efficiency and accuracy of obtaining the current comment keywords.

[0034] Step 120: Determine the current keyword type to which the current comment keyword belongs from at least two candidate keyword types.

[0035] The candidate keyword type is a type that the keyword may belong to, such as price, service, environment, safety, transportation, toilet, facility, catering, information technology, project, etc. For example, when the current keyword is "discount", "cost-effectiveness", "loss", etc., the current keyword type to which the current comment keyword belongs is "price".

[0036] According to the recognition of the current comment keywords, the current comment keywords may be stored in a file corresponding to the current keyword type according to the category to which the keywords belong.

[0037] Step 130: Determine reply information to the user comment data based on the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined based on historical user comment data.

[0038] Among them, the overall review result of the current keyword type is the overall review result under the current keyword type. The review result can be presented in the form of a score or evaluation, which is not limited in this embodiment. Exemplarily, the corresponding overall review result is obtained for each keyword type, for example, the overall review result of the price is 95 points, the overall review result of the service is 90 points, etc. The overall review result of the current keyword type is determined based on the historical user review data on the keyword type.

[0039] According to the overall review results of the current user comment data and the current keyword type, the reply information to the user comment data is jointly determined, wherein the reply information is a reply to the user comment data. For example, when the user's comment data is an evaluation, the reply information can be a thank you for the user's evaluation, and when the user's comment data is a question, the reply information can be an answer to the user's question. For example, the user's current comment data is "How is the catering in the scenic area?", and according to the current user comment data, it is determined that the corresponding current keyword type is catering, then the reply information to the user comment data can be determined in combination with the overall review results of the catering type and the specific content of the current keyword. For example, the reply information is "The rating of the catering in this scenic area is 95 points" and so on.

[0040] The method for obtaining reply information is to pre-construct a question-and-answer knowledge graph based on scenic spots and store it in a database, such as a neo4j database. When a user makes a comment, the user's question is converted into a query statement to access the database to query the pre-constructed knowledge graph, and combined with the overall comment results of the current keyword type, the reply information is obtained, thereby improving the efficiency and accuracy of obtaining question-and-answer information.

[0041] In this embodiment, optionally, determining reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type includes:

[0042] Obtain the keyword code of the current comment keyword;

[0043] Inputting the keyword encoding into a pre-built question-answering model;

[0044] According to the output result of the question-answering model, reply information to the user comment data is determined; wherein the question-answering model is trained based on a sequence2sequence network structure.

[0045] Among them, the keyword encoding is a code pre-associated with the keyword. The specific encoding method can be to collect common comments in advance, and then encode the comment keywords through the embedding layer. The specific encoding can be to sort according to the frequency of occurrence of the keywords. The higher the frequency of occurrence, the higher the order. The encoding is in sequence according to the sorting. This embodiment does not impose any restrictions on this.

[0046] Determine the corresponding answer for the comment, and then train the comments and answers based on the sequence2sequence model through the encoder encoder and decoder decoder to generate a question-answering model. The encoder is used to understand the comments and convert them into content vectors, and the decoder is used to decode the vectors of the understood comments to obtain output.

[0047] After obtaining the current user comment data, the keywords in the current user comment are encoded accordingly and input into the question-answering model to obtain reply information, thereby improving the efficiency and accuracy of obtaining question-answering information.

[0048] The technical solution provided in this embodiment determines the current comment keyword in the current user comment data; determines the current keyword type to which the current comment keyword belongs from at least two candidate keyword types; and determines the reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined according to the historical user comment data. This solves the problem that tourists mainly obtain other tourists' evaluations of the scenic spot from the comment area corresponding to the scenic spot, and cannot actively understand the corresponding information of the scenic spot, so the acquisition of scenic spot information is one-sided and vague, and achieves the effect of improving the accuracy and pertinence of scenic spot information acquisition.

[0049] Embodiment 2

[0050] Figure 2 This is a flowchart of a scenic spot review data processing method provided in Embodiment 2 of the present invention. This technical solution is to supplement the process of determining the overall review result of the current keyword type. Compared with the above solution, this solution is specifically optimized to determine the overall review result of the current keyword type, including:

[0051] Determine historical review keywords in historical user review data;

[0052] Determine the historical keyword type to which the historical review keyword belongs from at least two candidate keyword types;

[0053] According to the historical keyword part of speech of the historical comment keyword and the historical keyword type, the overall comment result of the current keyword type is determined. Specifically, the flowchart of the method for processing user scenic spot comment data is as follows Figure 2 As shown:

[0054] Step 210: Determine historical review keywords in the historical user review data.

[0055] Among them, the historical user comment data maintains the historical comment data posted by users on the scenic spot, which can be text data, or voice or picture data; the acquisition method can be obtained from the scenic spot comment area, and all historical comments can be obtained, or historical comments of a specific time can be obtained as required, such as historical comments in 2019, etc. This embodiment does not limit this.

[0056] Step 220: Determine the historical keyword type to which the historical review keyword belongs from at least two candidate keyword types.

[0057] The candidate keyword types are types that the historical keywords may belong to, such as price, service, environment, safety, transportation, toilet, facility, catering, informationization, project, etc.

[0058] Step 230: Determine the overall review result of the current keyword type according to the historical keyword part of speech of the historical review keyword and the historical keyword type.

[0059] The parts of speech of historical keywords can include positive, negative and neutral. Under a single historical review keyword type, the overall review result of the historical keyword type is determined according to the parts of speech of all historical keywords, and the overall review result of the historical keyword type is used as the overall review result of the current keyword type. Exemplarily, all historical review keywords of the catering type are obtained from the historical user review data, and the overall review result of the catering type is determined according to the parts of speech of all historical review keywords of the catering type. If it is 95 points, then when the current keyword type is catering, the overall review result of the current keyword type is 95 points.

[0060] The frequency of occurrence of historical comment keywords in each historical keyword type and the keyword parts of speech of the historical comment keywords can be counted to generate a set of positive and negative high-frequency keywords for each keyword type in each scenic spot for display.

[0061] In this embodiment, optionally, determining the overall review result of the current keyword type according to the keyword part of speech of the historical review keyword and the historical keyword type includes:

[0062] Determining the historical review score of the historical review keyword according to the historical keyword part of speech;

[0063] According to the historical comment scores and the historical keyword set corresponding to the historical keyword type, the overall comment score of the historical keyword type is determined, and the overall comment score is used as the overall comment result of the current keyword type.

[0064] The historical comment score is the score corresponding to the historical comment keyword. For example, the positive keyword score is 1, the neutral keyword score is 0, and the negative keyword score is -1. This embodiment does not limit this. The historical keyword set is all historical keywords corresponding to a single historical keyword type in the historical user comment data.

[0065] Determine the overall review score of the historical keyword type, and use the overall review score as the overall review result of the current keyword type. For example, if there are 100 keywords in the facility type after identifying the historical user review data, then add up the scores corresponding to all keywords to obtain the total score as the overall review result. By using the overall review score as the overall review result of the current keyword type, the intuitiveness of the overall review result display is improved.

[0066] Optionally, the overall review results corresponding to all keyword types can be presented in the form of a radar chart to improve the intuitiveness of the result presentation.

[0067] In this embodiment, optionally, after determining the overall review result of the current keyword type, the method further includes:

[0068] According to the historical overall review results of the current keyword type, a change trend of the overall review results is determined.

[0069] The historical overall review results of the current keyword type are the review results corresponding to the keyword type before the current time point. For example, the overall review results are obtained in months. Then, the overall change trend can be generated based on the overall review results of each month in the past. It can be presented in the form of a line graph to improve the intuitiveness of the display of changes in the overall review results corresponding to each keyword type, thereby improving the accuracy and pertinence of users' acquisition of scenic spot information.

[0070] The embodiment of the present invention determines the overall review result of the current keyword type according to the historical keyword part of speech and the historical keyword type of the historical review keyword, thereby improving the accuracy of determining the overall review result.

[0071] Embodiment 3

[0072] Figure 3 This is a schematic diagram of the structure of a scenic spot review data processing device provided in the third embodiment of the present invention. The device can be implemented by hardware and / or software, can execute a scenic spot review data processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. Figure 3 As shown, the device comprises:

[0073] A current comment keyword determination module 310 is used to determine the current comment keyword in the current user comment data;

[0074] A current keyword type determination module 320, used to determine the current keyword type to which the current comment keyword belongs from at least two candidate keyword types;

[0075] The reply information determination module 330 is used to determine the reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined according to the historical user comment data.

[0076] The technical solution provided in this embodiment determines the current comment keyword in the current user comment data; determines the current keyword type to which the current comment keyword belongs from at least two candidate keyword types; and determines the reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined according to the historical user comment data. This solves the problem that tourists mainly obtain other tourists' evaluations of the scenic spot from the comment area corresponding to the scenic spot, and cannot actively understand the corresponding information of the scenic spot, so the acquisition of scenic spot information is one-sided and vague, and achieves the effect of improving the accuracy and pertinence of scenic spot information acquisition.

[0077] On the basis of the above technical solutions, optionally, the reply information determination module includes:

[0078] A keyword code acquisition unit, used to acquire the keyword code of the comment keyword;

[0079] A question-answering model input unit is used to input the keyword encoding into a pre-built question-answering model; wherein the question-answering model is trained based on a sequence2sequence network structure

[0080] A reply information determination unit determines reply information to the user comment data according to the output result of the question-answer model.

[0081] Based on the above technical solutions, an optional overall review result module includes:

[0082] A historical review keyword unit, used to determine historical review keywords in historical user review data;

[0083] A historical keyword type determination unit, used to determine the historical keyword type to which the historical review keyword belongs from at least two candidate keyword types;

[0084] The overall review result determination unit is used to determine the overall review result of the current keyword type according to the historical keyword part of speech of the historical review keyword and the historical keyword type.

[0085] On the basis of the above technical solutions, optionally, the overall review result determination unit includes:

[0086] A historical review score determination subunit, used to determine the historical review score of the historical review keyword according to the historical keyword part of speech;

[0087] The overall review score determination subunit is used to determine the overall review score of the historical keyword type according to the historical review score and the historical keyword set corresponding to the historical keyword type, and use the overall review score as the overall review result of the current keyword type.

[0088] On the basis of the above technical solutions, optionally, the device further includes:

[0089] The result change trend determination unit is used after the overall review result determination unit to determine the change trend of the overall review result according to the historical overall review results of the current keyword type.

[0090] On the basis of the above technical solutions, optionally, the current comment keyword determination module includes:

[0091] A current user comment data filtering unit, used to filter the current user comment data according to a pre-constructed stop word list;

[0092] The current comment keyword determination unit is used to determine the current comment keyword by performing word segmentation processing on the filtered current user comment data.

[0093] Embodiment 4

[0094] Figure 4 A schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention is shown in FIG. Figure 4As shown, the electronic device includes a processor 40, a memory 41, an input device 42 and an output device 43; the number of processors 40 in the electronic device can be one or more. Figure 4 A processor 40 is taken as an example; the processor 40, the memory 41, the input device 42 and the output device 43 in the electronic device can be connected by a bus or other means. Figure 4 The example of connecting through bus is taken in the following.

[0095] The memory 41 is a computer-readable storage medium that can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the scenic spot review data processing method in the embodiment of the present invention. The processor 40 executes various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the memory 41, that is, implements the above-mentioned scenic spot review data processing method.

[0096] The memory 41 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 41 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 41 may further include a memory remotely arranged relative to the processor 40, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0097] Embodiment 5

[0098] Embodiment 5 of the present invention further provides a storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute a scenic spot review data processing method when executed by a computer processor, the method comprising:

[0099] Determine the current comment keyword in the current user comment data;

[0100] Determine the current keyword type to which the current comment keyword belongs from at least two candidate keyword types;

[0101] Determine reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined according to the historical user comment data.

[0102] Of course, the storage medium containing computer executable instructions provided in an embodiment of the present invention is not limited to the method operations described above, and can also execute related operations in the scenic spot review data processing method provided in any embodiment of the present invention.

[0103] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0104] It is worth noting that in the above-mentioned embodiment of the scenic spot review data processing device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0105] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for processing scenic spot review data, characterized in that: include: Determine the current comment keyword in the current user comment data; Determine the current keyword type to which the current comment keyword belongs from at least two candidate keyword types; Determine reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined according to the historical user comment data; Wherein, determining the overall review result of the current keyword type includes: Determine historical review keywords in historical user review data; Determine the historical keyword type to which the historical review keyword belongs from at least two candidate keyword types; Determine the overall review result of the current keyword type according to the historical keyword part of speech of the historical review keyword and the historical keyword type; wherein the historical keyword part of speech includes positive, negative and neutral; Wherein, determining the overall review result of the current keyword type according to the keyword part of speech of the historical review keyword and the historical keyword type includes: Determining the historical review score of the historical review keyword according to the historical keyword part of speech; According to the historical comment score and the historical keyword set corresponding to the historical keyword type, determine the overall comment score of the historical keyword type, and use the overall comment score as the overall comment result of the current keyword type; wherein the historical keyword set is all historical keywords corresponding to a single historical keyword type in the historical user comment data; The overall review result of the current keyword type is the overall review result under the current keyword type, and the review result is presented in the form of score or evaluation; After determining the overall review result of the current keyword type, the method further includes: According to the historical overall review results of the current keyword type, a change trend of the overall review results is determined.

2. The method according to claim 1, characterized in that Determining reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type includes: Obtain the keyword code of the current comment keyword; Inputting the keyword encoding into a pre-built question-answering model; According to the output result of the question-answering model, reply information to the user comment data is determined; wherein the question-answering model is trained based on a sequence2sequence network structure.

3. The method according to claim 1, characterized in that Determine the current comment keywords in the current user comment data, including: Filtering the current user comment data according to a pre-constructed stop word list; The current comment keywords are determined by performing word segmentation processing on the filtered current user comment data.

4. A scenic spot review data processing device, characterized in that: include: A current comment keyword determination module is used to determine the current comment keywords in the current user comment data; A current keyword type determination module, used to determine the current keyword type to which the current comment keyword belongs from at least two candidate keyword types; A reply information determination module, used to determine reply information to the user comment data according to the current user comment data and the overall comment result of the current keyword type; wherein the overall comment result of the current keyword type is determined according to the historical user comment data; Among them, the overall review result module includes: A historical review keyword unit, used to determine historical review keywords in historical user review data; A historical keyword type determination unit, used to determine the historical keyword type to which the historical review keyword belongs from at least two candidate keyword types; The overall review result determination unit is used to determine the overall review result of the current keyword type according to the historical keyword part of speech of the historical review keyword and the historical keyword type; wherein the historical keyword part of speech includes positive, negative and neutral; wherein the overall review result determination unit includes: A historical review score determination subunit, used to determine the historical review score of the historical review keyword according to the historical keyword part of speech; The overall review score determination subunit is used to determine the overall review score of the historical keyword type according to the historical review score and the historical keyword set corresponding to the historical keyword type, and use the overall review score as the overall review result of the current keyword type; wherein the historical keyword set is all historical keywords corresponding to a single historical keyword type in the historical user review data; The overall review result of the current keyword type is the overall review result under the current keyword type, and the review result is presented in the form of score or evaluation; The device also includes: The result change trend determination unit is used after the overall review result determination unit to determine the change trend of the overall review result according to the historical overall review results of the current keyword type.

5. The device according to claim 4, characterized in that The reply information determination module includes: A keyword code acquisition unit, used to acquire the keyword code of the comment keyword; A question-answering model input unit is used to input the keyword encoding into a pre-built question-answering model; wherein the question-answering model is trained based on a sequence2sequence network structure A reply information determination unit determines reply information to the user comment data according to the output result of the question-answer model.

6. An electronic device, characterized in that: The electronic device comprises: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the scenic spot review data processing method as described in any one of claims 1-3.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the scenic spot review data processing method as described in any one of claims 1-3 is implemented.

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