CN115660902A - Big data-based intelligent tourism evaluation system - Google Patents
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- CN115660902A CN115660902A CN202211275610.3A CN202211275610A CN115660902A CN 115660902 A CN115660902 A CN 115660902A CN 202211275610 A CN202211275610 A CN 202211275610A CN 115660902 A CN115660902 A CN 115660902A
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Abstract
The invention discloses a big data-based intelligent tourism evaluation system, which comprises the following operating methods: big data is used for obtaining evaluation information under a tourism system and carrying out primary selection processing; performing weight analysis on the selected index characteristics to construct an evaluation model; obtaining evaluation information under each tourism system through big data, and storing the evaluation information in a database after primary processing; selecting evaluation index words related to the intelligent tourism service; carrying out normalization processing on the data, and further determining the weight of each evaluation index by an analytic hierarchy process; weighting and summing the obtained index weight and the normalized data to obtain a neural network target value, and constructing an evaluation model through neural network training; analyzing the evaluation result through an evaluation model; recommending and optimizing the user, the merchant and the travel mode by combining the evaluation model results of all indexes; the invention has the characteristics of improving the intelligent tourism evaluation utilization rate and improving the satisfaction degree of tourists.
Description
Technical Field
The invention relates to the technical field of intelligent tourism, in particular to an intelligent tourism evaluation system based on big data.
Background
Smart tourism, also called intelligent tourism, utilizes new technologies such as cloud computing, thing networking, and the information of the relevant aspect of initiative perception and tourism, in time releases reaches intelligent perception to various tourism information, creates convenient effect for life. With the rapid development of new travel modes such as self-driving travel and global travel, the travel activity space and distance of tourists are greatly expanded, and correspondingly, with the increase of the dependence of tourists on informatization, tourists pay more and more attention to the level and quality of travel service, and need to obtain more accurate, effective, convenient and active service to meet the travel requirement of the tourists. The current wisdom tourism service construction lacks the standardization theory, and the disappearance of the aspect of the service evaluation index system makes the development direction of wisdom tourism service deviate to a certain extent, has reduced the effective utilization of visitor's evaluation content to the intellectuality process of city tourism development has been hindered to a certain extent. Therefore, it is necessary to design a big data-based intelligent tourism evaluation system for improving the utilization rate of the intelligent tourism evaluation and the satisfaction degree of tourists.
Disclosure of Invention
The invention aims to provide an intelligent tourism evaluation system based on big data to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the intelligent tourism evaluation system based on big data comprises the following operation methods:
big data is used for obtaining evaluation information under a tourism system and carrying out primary selection processing;
performing weight analysis on the selected index characteristics to construct an evaluation model;
analyzing the evaluation result through an evaluation model;
and (4) recommending and optimizing the user, the merchant and the travel mode by combining the evaluation model results of all indexes.
According to the technical scheme, the step of acquiring the evaluation information under the tourism system by the big data and carrying out primary selection processing comprises the following steps:
obtaining evaluation information under each tourism system through big data, and storing the evaluation information in a database after primary processing;
and selecting out evaluation index words related to the intelligent travel service.
According to the technical scheme, the step of performing weight analysis on the selected index features to construct the evaluation model comprises the following steps:
carrying out normalization processing on the data, and further determining the weight of each evaluation index by an analytic hierarchy process;
and carrying out weighted summation on the obtained index weight and the normalized data to obtain a neural network target value, and constructing an evaluation model through neural network training.
According to the above technical solution, the step of analyzing the evaluation result by the evaluation model includes:
and inputting the acquired data into the evaluation model to obtain each index evaluation result of the area corresponding to the data.
According to the technical scheme, the step of recommending and optimizing the user, the merchant and the tourism mode by combining the evaluation model result of each index comprises the following steps:
and intelligently recommending the user by analyzing the finally output evaluation result of each index, and feeding back information to the merchant.
According to the above technical solution, the system comprises:
the tourism evaluation information acquisition module is used for acquiring tourism evaluation information;
the tourism evaluation information analysis module is used for analyzing the tourism evaluation information;
and the travel evaluation information utilization module is used for carrying out effective utilization according to the analysis of the evaluation result.
According to the technical scheme, the tourism evaluation information acquisition module comprises:
the database storage module is used for storing the acquired evaluation information;
the evaluation information acquisition module is used for acquiring evaluation information;
the data processing module is used for carrying out primary processing on the obtained evaluation information;
and the service index selection module is used for selecting the service index words from the evaluation information text.
According to the technical scheme, the tourism evaluation information analysis module comprises:
the index weight analysis module is used for analyzing the service index weight;
the evaluation model building module is used for building an evaluation model;
and the evaluation result analysis module is used for analyzing the final result of the evaluation information through the evaluation model.
According to the technical scheme, the travel evaluation information utilization module comprises:
the user intelligent recommendation module is used for intelligently recommending the user according to the evaluation result;
the tourism merchant feedback module is used for feeding back information to merchants according to the evaluation result;
and the intelligent tourism mode optimization module is used for optimizing and improving the intelligent tourism mode according to the evaluation result.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, through the arrangement of a tourism evaluation information acquisition module, a tourism evaluation information analysis module and a tourism evaluation information utilization module, evaluation information under each tourism system is acquired through big data, the text data of evaluation contents is preprocessed, then descriptive statistical analysis is carried out, a word cloud picture is generated, part of speech analysis and emotion tendency analysis are carried out, and evaluation index words related to intelligent tourism service are selected; after the weight of each evaluation index is determined through an analytic hierarchy process, weighting summation is carried out on the obtained index weight and normalized data to obtain a neural network target value, an evaluation model is built through neural network training, the obtained data are input into the evaluation model to obtain each index evaluation result of a region corresponding to the data, intelligent recommendation is carried out on a user, information feedback is carried out on a merchant, the intelligent tourism mode can be optimized and improved according to the information, and the intelligent tourism evaluation content is maximized.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flowchart illustrating a method for operating a big data based intelligent travel evaluation system according to an embodiment of the present invention;
FIG. 2 is a block diagram of a big data based intelligent tour evaluation system according to a second embodiment of the present invention.
Detailed Description
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, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
fig. 1 is a flowchart of a method of a big data-based smart travel evaluation system according to an embodiment of the present invention, where the method can be executed by the big data-based smart travel evaluation system according to the embodiment of the present invention, and the system is composed of a plurality of software and hardware modules, and the method specifically includes the following steps:
s101, acquiring evaluation information under a tourism system by big data and carrying out primary selection processing;
in some embodiments of the present invention, the evaluation information under each travel system is obtained through big data and stored in the database after being subjected to preliminary processing.
Illustratively, in the embodiment of the invention, the evaluation information under each tourism system comprises satisfaction evaluation of tourists on tourist sights, traffic, accommodation and the like of a tourist city, and feedback evaluation on reservation and purchase of tourism products.
In some embodiments of the invention, the evaluation content text data is preprocessed, including removal of emoticons, word segmentation, and removal of stop words, followed by descriptive statistical analysis, word cloud generation, and part-of-speech analysis and emotional orientation analysis.
Specifically, in the embodiment of the invention, word frequency statistics is completed through TF-IDF, and high-frequency words with actual meanings in comments are screened out; analyzing according to the part of speech, and screening out key words which have important influence on the tourism process; analyzing the keywords with practical significance, and performing frequency statistics grouped according to the emotion tendency labels to finish qualitative analysis; and drawing a word cloud picture which consists of word labels and word sizes, and visualizing the analysis result and visually displaying the word frequency.
In some embodiments of the present invention, evaluation index words associated with the intelligent travel service are selected for subsequent analysis of index weights and model construction.
For example, in the embodiment of the present invention, the evaluation index word related to the smart travel service may be an evaluation word related to a smart dining accommodation service, a smart transportation service, a city tour service, an entertainment shopping service, a city information service, and a city security service.
S102, performing weight analysis on the selected index features to construct an evaluation model;
in some embodiments of the invention, the data is normalized to between [0,1] by using a maximum and minimum data normalization method before constructing the evaluation model, so that the original meaning of the data is well preserved without information loss.
In some embodiments of the invention, the weight of each evaluation index is further determined by an analytic hierarchy process.
Specifically, in the embodiment of the invention, a decision target, a considered factor and a decision object are divided into a highest layer, a middle layer and a lowest layer according to the mutual relation among the decision target, the considered factor and the decision object, and a hierarchical structure diagram is drawn; when determining the weight among the factors of each layer, the consistent matrix method is adopted, namely all the factors are not put together for comparison, but two factors are compared with each other, and the relative scale is adopted during comparison, so that the difficulty of comparing different factors with each other is reduced as much as possible, and the accuracy is improved; and (4) carrying out consistency check on each index, then carrying out consistency check on the judgment matrix, further carrying out total hierarchical ordering, and finally solving the index weight of each layer by combining the relative importance scores of each evaluation index given by system management personnel.
Illustratively, in the embodiment of the present invention, consistency in the consistency check of the matrix refers to judging logical consistency of thinking, for example, when a is strongly important than c, and b is slightly important, it is obvious that a is definitely more important than b, otherwise, the judgment will be contradictory.
Specifically, the hierarchical total ranking is a ranking weight process for determining the relative importance of all factors of a certain layer to the total target.
In the embodiment of the invention, the obtained index weight and the normalized data are subjected to weighted summation to obtain a neural network target value, and an evaluation model is constructed through neural network training.
S103, analyzing an evaluation result through an evaluation model;
in some embodiments of the present invention, the obtained data is input into the evaluation model to obtain evaluation results of each index of the area corresponding to the data.
For example, in the embodiment of the present invention, the model may be applied to various types of tourist areas such as viewing scenic spots, amusement parks, service scenic spots, and the like, and may also perform overall tourist evaluation analysis according to a city, which may reflect the overall service condition of a certain tourist area in a micro-scale manner according to the evaluation result of the tourist or reflect the overall service condition of a certain city in a macro-scale manner, thereby providing an optimization suggestion or an effective recommendation feedback for the user, the business and the intelligent tourist mode operated in each region.
S104, recommending and optimizing the user, the merchant and the travel mode by combining the evaluation model results of all indexes;
in some embodiments of the invention, the user is intelligently recommended by analyzing the finally output evaluation results of each index, information feedback is performed on the merchant, and the intelligent tourism mode can be optimized and improved according to the information feedback, so that the intelligent tourism evaluation content is maximally utilized.
Illustratively, in the embodiment of the invention, when a user considers a tourist location or wants to further know about an intention tourist area, related information can be input in the system according to the strength of an intention index according to own requirements, the system can finally output the related matching between the area and the user according to historical evaluation information through an evaluation model for the user to refer to, and the user can decide by himself by visually displaying the related evaluation information content with strong intention index; the business in the tourism area can further improve the directions of the business service system, price formulation, commodity category and the like of the business by checking the evaluation indexes related to business service and by feeding back the overall result and the displayed content information by the system; the intelligent tourism department can judge whether the intelligent tourism mode has corresponding problems or not through overall evaluation of the whole city tourism service, and optimize and improve the mode according to specific contents of tourist evaluation so as to improve the satisfaction degree of tourists and further improve the service level and the favorable comment degree of the city.
Example two:
an embodiment of the present invention provides a big data-based intelligent tourism evaluation system, and fig. 2 is a schematic diagram of a module configuration of the big data-based intelligent tourism evaluation system provided in the embodiment two, as shown in fig. 2, the system includes:
the tourism evaluation information acquisition module is used for acquiring tourism evaluation information;
the tourism evaluation information analysis module is used for analyzing the tourism evaluation information;
and the travel evaluation information utilization module is used for carrying out effective utilization according to the analysis of the evaluation result.
In some embodiments of the present invention, the travel evaluation information acquisition module includes:
the database storage module is used for storing the acquired evaluation information;
the evaluation information acquisition module is used for acquiring evaluation information;
the data processing module is used for carrying out primary processing on the obtained evaluation information;
and the service index selection module is used for selecting the service index words from the evaluation information text.
In some embodiments of the present invention, the travel evaluation information analysis module comprises:
the index weight analysis module is used for analyzing the service index weight;
the evaluation model building module is used for building an evaluation model;
and the evaluation result analysis module is used for analyzing the final result of the evaluation information through the evaluation model.
In some embodiments of the present invention, the travel assessment information utilization module comprises:
the user intelligent recommendation module is used for intelligently recommending the user according to the evaluation result;
the tourism merchant feedback module is used for feeding back information to merchants according to the evaluation result;
and the intelligent tourism mode optimization module is used for optimizing and improving the intelligent tourism mode according to the evaluation result.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described above, or equivalents may be substituted for elements thereof. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. Wisdom tourism evaluation system based on big data, its characterized in that: the method run by the system comprises the following steps:
big data is used for obtaining evaluation information under a tourism system and carrying out primary selection processing;
performing weight analysis on the selected index characteristics to construct an evaluation model;
analyzing an evaluation result through an evaluation model;
and (4) recommending and optimizing the user, the merchant and the travel mode by combining the evaluation model results of all indexes.
2. The big data-based intelligent travel assessment system according to claim 1, wherein: the step of acquiring the evaluation information under the tourism system by the big data and carrying out the primary selection processing comprises the following steps:
obtaining evaluation information under each tourism system through big data, and storing the evaluation information in a database after primary processing;
and selecting out evaluation index words related to the intelligent travel service.
3. The big data-based intelligent travel assessment system according to claim 1, wherein: the step of performing weight analysis on the selected index features to construct an evaluation model comprises the following steps:
carrying out normalization processing on the data, and further determining the weight of each evaluation index by an analytic hierarchy process;
and carrying out weighted summation on the obtained index weight and the normalized data to obtain a neural network target value, and constructing an evaluation model through neural network training.
4. The big data-based intelligent travel assessment system according to claim 1, wherein: the step of analyzing the evaluation result by the evaluation model includes:
and inputting the acquired data into the evaluation model to obtain each index evaluation result of the area corresponding to the data.
5. The big data-based intelligent travel assessment system according to claim 1, wherein: the step of recommending and optimizing the user, the merchant and the travel mode by combining the evaluation model results of all indexes comprises the following steps:
and intelligently recommending the user by analyzing the finally output evaluation result of each index, and feeding back information to the merchant.
6. The big data-based intelligent travel assessment system according to claim 1, wherein: the system comprises:
the tourism evaluation information acquisition module is used for acquiring tourism evaluation information;
the tourism evaluation information analysis module is used for analyzing the tourism evaluation information;
and the travel evaluation information utilization module is used for carrying out effective utilization according to the analysis of the evaluation result.
7. The big data-based intelligent travel assessment system according to claim 6, wherein: the tourism evaluation information acquisition module comprises:
the database storage module is used for storing the acquired evaluation information;
the evaluation information acquisition module is used for acquiring evaluation information;
the data processing module is used for carrying out primary processing on the obtained evaluation information;
and the service index selection module is used for selecting the service index words from the evaluation information text.
8. The big data-based intelligent travel assessment system according to claim 6, wherein: the tourism evaluation information analysis module comprises:
the index weight analysis module is used for analyzing the service index weight;
the evaluation model building module is used for building an evaluation model;
and the evaluation result analysis module is used for analyzing the final result of the evaluation information through the evaluation model.
9. The big data-based intelligent travel assessment system according to claim 6, wherein: the travel evaluation information utilization module comprises:
the user intelligent recommendation module is used for intelligently recommending the user according to the evaluation result;
the tourism merchant feedback module is used for feeding back information to merchants according to the evaluation result;
and the intelligent tourism mode optimization module is used for optimizing and improving the intelligent tourism mode according to the evaluation result.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116151933A (en) * | 2023-04-18 | 2023-05-23 | 深圳市感恩网络科技有限公司 | International trade information data digital supervision system and method based on big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116151933A (en) * | 2023-04-18 | 2023-05-23 | 深圳市感恩网络科技有限公司 | International trade information data digital supervision system and method based on big data |
| CN116151933B (en) * | 2023-04-18 | 2023-10-24 | 深圳市感恩网络科技有限公司 | International trade information data digital supervision system and method based on big data |
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