CN107944735A - A kind of tourist attraction brand value analysis method based on classic poetry - Google Patents
A kind of tourist attraction brand value analysis method based on classic poetry Download PDFInfo
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- CN107944735A CN107944735A CN201711280130.5A CN201711280130A CN107944735A CN 107944735 A CN107944735 A CN 107944735A CN 201711280130 A CN201711280130 A CN 201711280130A CN 107944735 A CN107944735 A CN 107944735A
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Abstract
The present invention relates to data analysis application field, especially a kind of tourist attraction brand value analysis method based on classic poetry.The classic poetry that the method for the present invention passes through already present big data quantity, content therein is analyzed, and famous each tourist attraction is associated analysis with existing country, therefrom draw brand value of the famous tourist attraction in classic poetry, so as to assess the overall value of these scenic spots, Humanistic Value, reference analysis is provided for the visit of people, in turn or the publicity of each tourist attraction provides corresponding propaganda materials and direction, so as to improve the popularity of tourist attraction.This method can realize value dimension of the classic poetry in economic publicity, can promote the utilization of classic poetry data, lift the utility value benefit of data.
Description
Technical field
The present invention relates to data analysis application field, especially a kind of tourist attraction brand value analysis based on classic poetry
Method.
Background technology
With the popularization of big data analysis, big data can make people in common information in the labor of all trades and professions
The middle more values of acquisition, such as famous tourist attraction.With the raising of people's economic level, more and more people can like
OK.In terms of tourist attraction, how propaganda strength is improved, the brand value for excavating scenic spot is an important job；It is right at the same time
For the people to go on a tour, the tourist attractions of a high value, and a critically important selection how are found.
How to excavate the brand value of tourist attraction, this be not by relevant scenic spot publicity can, or by correlation
Advertisement promotion with regard to feasible；It needs to be publicized by indirectly, in the related important evidence of history obtaining information, such as has
The association of some great names in history, or the angle from history, more permanent historical information etc., have so as to be promoted in publicity
More watching focus introductions；And with regard to relevant history introduction and the history deal of the people of introduction, in corresponding brand promotion,
It is to have different effects, so being excavated in the brand value of tourist attraction, need to finds that heavy weight, information are more, foundation is reliable
Information excavated；With reference to historical analyzable document and famous person's information, analyzed from the angle of classic poetry, be one
The method of a very effective fruit.
The content of the invention
Present invention solves the technical problem that it is to provide a kind of tourist attraction brand value analysis method based on classic poetry；
By the classic poetry of already present big data quantity, content therein is analyzed, and each tourism scape famous with existing country
Area is associated analysis, therefrom draws brand value of the famous tourist attraction in classic poetry, so as to assess these scenic spots
Overall value, Humanistic Value, reference analysis is provided for the visit of people, in turn or each tourist attraction publicity provide
Corresponding propaganda materials and direction, so as to improve the popularity of tourist attraction.
The present invention solve above-mentioned technical problem technical solution be：
The method comprises the following steps：
Step 1：The information such as the title of each famous tourist attraction, introduction, former name, abbreviation are collected, for identifying scenic spot
Feature；
Step 2：Collection classic poetry data as complete as possible from network, including the information such as its content, author, while as far as possible
Make it associated with author, realize the recognizable of age information；
Step 3：TrieTree tree algorithms are built, algorithm is calculated using HDFS as storage, using the memory of Spark, calculates knot
It is stored in after structure processing on relevant database；
Step 4：Using the relevant information of tourist attraction as input, the TrieTree tree constructions with all scenic spots are built, are used
Matched in the input of all classic poetries；
Step 5：All classic poetries are read, inputs one by one and analyzes its matching degree to related tourist attraction, count one by one
Calculate the classic poetry that each scenic spot is related to；
Step 6：After the completion of all classic poetry input matchings, by the matching degree at each scenic spot, after simplifying processing, each scape
The relevant informations such as area's title, number of matches, the specific corresponding classic poetry of matching, export to relevant database；
Step 7, by reading maximum classic poetry match scenic spot, analyzes its associating with famous verse, sets relevant
Weight fraction, calculates corresponding brand value, for reference；
Step 8, set corresponding query interface, by inputting corresponding scenic spot, can view scenic spot and each classic poetry
Incidence relation.
The method is by Famous sceneries collection module, classic poetry data collection module, TrieTree Algorithm Analysis modules
Realized with data analysis and processing module；
The Famous sceneries collection module collects the title to form each Famous sceneries, geographical location, abbreviation, former name
Collect, for the matching to related classic poetry；
The classic poetry data collection module obtains poem content by modes such as data grabbers, includes the detailed feelings of author
Condition, age etc. of author, for detailed data foundation can be provided during follow-up data analysis；
The TrieTree Algorithm Analysis module is to the related contents of the Famous sceneries of collection, using TrieTree algorithms
Creation analysis tree is carried out, forms the analysis initial tree with Famous sceneries, then the classic poetry being collected into is subjected to word-breaking input, analysis
Go out the higher classic poetry of matching degree, for subsequent data analysis processing；
The Data Analysis Services module analysis draws the Famous sceneries for being related to that classic poetry is most, description is most, is used for
Select tourist attraction reference；The name at scenic spot can also be inputted, so that it is relevant to show which scenic spot is begun with age from which
The description of classic poetry.
The beneficial effects of the invention are as follows：
This method is by collecting each famous tourist attraction and all classic poetries, based on TrieTree tree algorithms, big number
According to analyzing the matching degree of each tourist attraction and each classic poetry, at the same associate out in history each famous poet to each tourist attraction
Evaluation, so as to fulfill from the angle of classic poetry, excavates the brand value of tourist attraction, is realizing the value of big data analysis application
While, realize the maximization of the brand value of classic poetry combination tourist attraction, there is provided the promotion method of a big data analysis.
This method is by based on large-scale classic poetry, by all kinds of big data analysis methods, to all classic poetries into
Row word-breaking is analyzed, and carries out with the place name of each tourist attraction associated, is the tourism of people so as to draw intrinsic value therein
Selection provides reference, and the publicity for each title scenic spot provides corresponding Humanistic Value, realizes valency of the classic poetry in economic publicity
Value embodies, the utilization to promoting species classic poetry data, lifts the utility value benefit of data.
Brief description of the drawings
The present invention is further described below in conjunction with the accompanying drawings：
Fig. 1 is the method frame figure of the tourist attraction brand value big data analysis of the invention based on classic poetry；
Fig. 2 is the flow chart of the tourist attraction brand value big data analysis of the invention based on classic poetry.
Embodiment
As shown in Figure 1, 2, the flow of the method for the tourist attraction brand value big data analysis of the invention based on classic poetry
Step is：
Step 1：The information such as the title of each famous tourist attraction, introduction, former name, abbreviation are collected, for identifying scenic spot
Feature；
Step 2：Collection classic poetry data as complete as possible from network, including the information such as its content, author, while as far as possible
Make it associated with author, realize the recognizable of age information；
Step 3：TrieTree tree algorithms are built, algorithm is calculated using HDFS as storage, using the memory of Spark, calculates knot
It is stored in after structure processing on relevant database；
Step 4：Using the relevant information of tourist attraction as input, the TrieTree tree constructions with all scenic spots are built, it is accurate
It is ready for use on the input matching of all classic poetries；
Step 5：All classic poetries are read, and inputs one by one and analyzes its matching degree to related tourist attraction, one by one
Calculate the classic poetry that each scenic spot is related to；
Step 6：After the completion of all classic poetry input matchings, by the matching degree at each scenic spot, after simplifying processing, each scape
The relevant informations such as area's title, number of matches, the specific corresponding classic poetry of matching, export to relevant database；
Step 7, by reading maximum classic poetry match scenic spot, analyzes its associating with famous verse, sets relevant
Weight fraction, calculates corresponding brand value, for reference；
Step 8, set corresponding query interface, by inputting corresponding scenic spot, can view scenic spot and each classic poetry
Incidence relation.
A large amount of classic poetries based on collection of the invention, by the method for word-breaking, and with existing each famous tourist attraction into
Row association analysis, draws the description of specific classic poetry, analyzes the visit of which famous poet, how many poem is retouched
State, the primary attraction of description, term of description etc., algorithm is based primarily upon TrieTree algorithms, main including as follows with lower module：
Famous sceneries collection module：By the collection of the method, formed the titles of each Famous sceneries, geographical location, abbreviation,
The collection of former name, collect as far as possible it is complete, for the matching to related classic poetry；
Classic poetry data collection module：Classic poetry Data Collection is mainly carried out by modes such as data grabbers, crawl it is interior
Hold except poem content, also need to include the details of author, age etc. of author, detailed information is divided for follow-up data
Detailed data foundation can be provided during analysis；
TrieTree Algorithm Analysis modules：This module is used by the related content of the Famous sceneries to collection
TrieTree algorithms carry out creation analysis tree, so that the analysis initial tree with Famous sceneries is formed, then the classic poetry being collected into
Word-breaking input is carried out, analyzes the higher classic poetry of matching degree, for subsequent data analysis processing；
Data Analysis Services module：The process of analyzing and processing can draw the famous scape for being related to that classic poetry is most, description is most
Area, the method are used for the reference that people select tourist attraction；The name at scenic spot can also be inputted in turn, so that it is ancient which draws
Poem analyzed the scenic spot of input, which age to begin with the description of relevant classic poetry from, and the method is used for related scenic spot
Publicity.
The method of the present invention, it is therefore an objective to the analysis of big data is carried out by the description to all Famous sceneries and classic poetry,
The new Humanistic Value of each tourist attraction is obtained from the historical value of classic poetry, historical value, tourism mesh is being selected for people
Ground while do a reference, be also the publicity at scenic spot, realize that economic value provides a kind of feasible method.
The present invention need to collect famous tourist attractions, particularly there is the sight spot of certain history, and the information of collection includes tourism
The relevant information at sight spot, former name, abbreviation etc., need to carry out these information the correspondence of unique tourist attractions.
The tourist attractions information of collection need to be as far as possible complete, first, ensureing that the data of the process of analysis are complete, another is
More full data display can be obtained at the related tourist attractions of inquiry；The title of tourist attractions, former name, abbreviation etc. need at the same time
Relevant sight spot recommended information can be uniquely corresponded to, avoids causing the situation of multiple sight spot conflicts during subsequent query.
The acquisition of classic poetry：The acquisition scope of classic poetry is wider, and the information of acquisition not only includes the content of poem, also wraps
Include author, age etc., the method for acquisition mainly by way of network crawl, can capture as far as possible classic poetry author information,
Matched again by its corresponding information of author, it is possible to determine the corresponding age, the refinement for subsequent analysis；
Collect the information of complete famous tourist attractions, ancient poetry word information be the method premise, famous tourist attractions are
The target analyzed, and classic poetry is the foundation for the assessment that tourist attractions are carried out with brand value, whether both information
Complete is whether correlation analysis is correctly basic, so before being analyzed, need to take much time and first be carried out in these two aspects
The collection of related data, to ensure the complete of data.
With the title of the famous sites of collection, former name, abbreviation etc., by TrieTree tree algorithms, dividing by means of characters input is carried out,
The matched TrieTree trees of related names may be carried out by building one；The TrieTree trees of structure, by inputting all Gus
Poem, exports corresponding statistical information of each famous sites with classic poetry, each corresponding tourist attractions statistics is preserved, after being used for
It is continuous to analyze again.
The ancient poetry word association statistical information of each tourist attractions obtained by TrieTree tree algorithms, its input data amount with
Output data quantity is huge, while mass data calculating storage is preserved, and need to can make input by corresponding design Storage
Tourist attractions are matched with the statistics of substantial amounts of classic poetry, the process of design by the distributed storage architecture based on HDFS,
And the advantages of being calculated using the memory of Spark, then it is finally analyzed as a result, association pass with multiple keyword statistics numbers
System, stores to relevant database, so that it is to support Distributed Calculation support is a large amount of to calculate to be formed in calculating, and result of calculation
Analysis displaying can be carried out by the result of relationship type.
The brand value big data analysis of tourist attractions and classic poetry based on TrieTree tree algorithms, it is therefore an objective to from ancient poetry
The history-related that each sight spot is obtained in word is worth, in the data analysis process more than, so that it may show that each tourist attractions are related to Gu
Which the most sight spots of poem quantity, the main description term at the sight spot for the classic poetry being related to, the main history name poet being related to have,
The longest history being related to have how long, the analysis that relevant analysis report can be in this way draws final analysis result.
The brand value big data analysis of tourist attractions and classic poetry based on TrieTree tree algorithms, analysis as a result,
After each tourist attractions are associated with, it can realize that user carries out the inquiry of tourist famous-city, such as user by being provided out interface
Want to understand Yellow Crane Tower people's details, after inputting keyword Yellow Crane Tower, can show the information for the related classic poetry for being related to Yellow Crane Tower,
Here user can view earliest Yellow Crane Tower classic poetry description, which famous poet went sight-seeing, and have the scape what is special
See etc..
Analyzed based on the tourist attractions of classic poetry and great names in history, if having obtained describing, largely for substantial amounts of classic poetry
Famous in ancient poet visit, then illustrate that sight spot possesses fabulous Humanistic Value, in the publicity of tourist attractions or its warp
Help in valuation, possess great valuation, more preferable economic value can be produced for sight spot by the excavation of these information；Analyze at the same time
As a result, or user carry out the selection on tourism target ground and one reference be provided, it also has high warp to a certain extent
Ji value.By the method for big data analysis, the big data analysis of each tourist attractions and classic poetry is gathered, has been each tourist attractions
Excavate brand value and a feasible method is provided, so as to fulfill data of the big data on classic poetry and tourist attractions analysis
The integration of resource, realizes the value of the data analysis of classic poetry.
Claims (2)
- A kind of 1. tourist attraction brand value analysis method based on classic poetry, it is characterised in that：The method includes following Step：Step 1：The information such as the title of each famous tourist attraction, introduction, former name, abbreviation are collected, for identifying the feature at scenic spot；Step 2：Collection classic poetry data as complete as possible from network, including the information such as its content, author, while make it as far as possible It is associated with author, realize the recognizable of age information；Step 3：TrieTree tree algorithms are built, algorithm is calculated using HDFS as storage, using the memory of Spark, calculated at structure It is stored in after reason on relevant database；Step 4：Using the relevant information of tourist attraction as input, the TrieTree tree constructions with all scenic spots are built, for institute The input for having classic poetry matches；Step 5：All classic poetries are read, inputs one by one and analyzes its matching degree to related tourist attraction, are calculated one by one each The classic poetry that scenic spot is related to；Step 6：After the completion of all classic poetry input matchings, by the matching degree at each scenic spot, after simplifying processing, each scenic spot name The relevant informations such as title, number of matches, the specific corresponding classic poetry of matching, export to relevant database；Step 7, by reading maximum classic poetry match scenic spot, analyzes its associating with famous verse, sets relevant weight Fraction, calculates corresponding brand value, for reference；Step 8, set corresponding query interface, by inputting corresponding scenic spot, can view the pass at scenic spot and each classic poetry Connection relation.
- 2. according to the method described in claim 1, it is characterized in that：The method is by Famous sceneries collection module, classic poetry Data collection module, TrieTree Algorithm Analysis module and data analysis and processing module are realized；The Famous sceneries collection module collects the title to form each Famous sceneries, geographical location, abbreviation, the receipts of former name Collection, for the matching to related classic poetry；The classic poetry data collection module obtains poem content by modes such as data grabbers, including the details of author, Age of author etc., for detailed data foundation can be provided during follow-up data analysis；The TrieTree Algorithm Analysis module carries out the related content of the Famous sceneries of collection using TrieTree algorithms Creation analysis tree, forms the analysis initial tree with Famous sceneries, then the classic poetry being collected into is carried out word-breaking input, analyzes With higher classic poetry is spent, for subsequent data analysis processing；The Data Analysis Services module analysis draws the Famous sceneries for being related to that classic poetry is most, description is most, for selecting Tourist attraction refers to；The name at scenic spot can also be inputted, so as to show which scenic spot begins with relevant ancient poetry in age from which The description of word.
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| CN109948157A (en) * | 2019-03-13 | 2019-06-28 | 日照职业技术学院 | A kind of poem is collected and data analysing method |
| CN114819469A (en) * | 2022-02-24 | 2022-07-29 | 北京清华同衡规划设计研究院有限公司 | Intelligent tourism planning and designing method and system based on big data |
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Application publication date: 20180420 |