CN106372970A - Private tour guide automatic recommendation method and system - Google Patents
Private tour guide automatic recommendation method and system Download PDFInfo
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- CN106372970A CN106372970A CN201610807434.1A CN201610807434A CN106372970A CN 106372970 A CN106372970 A CN 106372970A CN 201610807434 A CN201610807434 A CN 201610807434A CN 106372970 A CN106372970 A CN 106372970A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0282—Rating or review of business operators or products
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2457—Query processing with adaptation to user needs
- G06F16/24578—Query processing with adaptation to user needs using ranking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0255—Targeted advertisements based on user history
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
- G06Q30/0271—Personalized advertisement
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/14—Travel agencies
Abstract
The invention discloses a private tour guide automatic recommendation method and system. The method comprises the following steps: S1, obtaining tour guide information of private tour guides; S2, obtaining travel information of travelers; S3, analyzing travel information of all historical travelers to obtain weights of various data in the travel information in tour guide selection; and S4, according to the travel information of current travelers, matching proper tour guides according to weight relations. According to the invention, by use of a big data technology, the tour guide information of the private tour guides and the travel information of the travelers are obtained through an information obtaining module, then according to the travel information of the travelers, various influential factors influencing selection of the tour guides by the travelers are analyzed, different weight models are established, and finally, according to the travel information of the current travelers, in accordance with the weight relations, proper tour guides are matched, such that the proper private tour guides can be automatically and quite accurately recommended to the travelers.
Description
Technical field
The present invention relates to tourism intelligent recommendation technical field, the method that more particularly, to a kind of private guide recommends automatically and be
System.
Background technology
With growth in the living standard, tourist industry increasing prevalence at home.A lot of economic conditions preferably, are pursued certainly simultaneously again
By the visitor travelling, select free walker, private tourism guiding service arises at the historic moment in this context.But how to select one suitably
Private guide, becomes the problem of most people headache.
Content of the invention
It is an object of the invention to provide the method and system that a kind of private guide recommends automatically, can accurately push away to visitor
Recommend suitably private guide.
To achieve these goals, the present invention provides a kind of method that private guide recommends automatically, and it comprises the following steps:
S1, the tour guide information of the private guide of acquisition；
S2, the travel information of acquisition visitor；
S3, the travel information to all history visitors are analyzed, and each item data obtaining in travel information selects in guide
Shared weight in selecting；
S4, the suitable guide of travel information foundation weight relationship coupling according to current visitor.
According to a preferred embodiment of the invention: every data of the travel information of described visitor includes: visitor's age, property
Not, tourist famous-city, language requirement and income.
According to a preferred embodiment of the invention: every data of described tour guide information includes: guide's sex, Dao Younian
Age, coverage, language, guide's grade, history connect an amount and guide's evaluation.
According to a preferred embodiment of the invention: in described step s3, each item data obtaining in historical tourism information exists
During guide selects, shared weight includes:
S31, using each item data in the travel information of history visitor as influence factor, with each item number of each tour guide information
According to as evaluation points；Set up multiple different weight model；
S32, calculate the weights corresponding to each item data of the travel information of history visitor in each weight model.
According to a preferred embodiment of the invention: described step s4 also includes,
S41, judge each item data proportion in the travel information of current visitor,
Current weights synthesis average corresponding to visitor in s42, the different weight model of calculating；
S43, comprehensive average is ranked up toward low from high；
S44, each comprehensive average is corresponded to corresponding weight model, coupling is corresponding to conduct a sightseeing tour.
According to a preferred embodiment of the invention: further comprise the steps of:
S5, the personal consumption historical record of the current visitor of acquisition；
S6, the selection preference guide of the current visitor of analysis；
S7, by described select preference guide screened with the guide mated by weight model, if repeated, then general
The guide repeating pushes at current visitor, if not repeating, pushing simultaneously and selecting the guide of preference and by weight model
The guide of coupling.
Present invention also offers the system that a kind of private guide recommends automatically, comprising:
Data obtaining module, goes through for obtaining the private tour guide information conducted a sightseeing tour and the travel information of visitor and personal consumption
The Records of the Historian is recorded；
Weight model sets up module, selects in guide for obtaining each item data in the travel information of all history visitors
In shared weight；
Computing module, for calculating the weights synthesis average corresponding to current visitor in different weight model；
Order module, for being ranked up the weights synthesis average corresponding to current visitor；
Information display module, for being pushed to the guide after final screening at visitor.
According to a preferred embodiment of the invention: also include:
Preference screening module, for the case history consumer record according to current visitor, is carried out to the guide selecting preference
Screening.
According to a preferred embodiment of the invention: described information acquisition module includes intelligent terminal app or website.
The beneficial effects of the present invention is: the present invention utilizes big data technology, obtains individual by data obtaining module and leads
The tour guide information of trip and the travel information of visitor, then select each impact of guide according to the travel information analysis visitor of visitor
Factor, thus setting up different weight model, the travel information finally according to current visitor is suitable according to weight relationship coupling
Guide, so as to accomplishing automatic and more accurately recommending suitably private guide to visitor.
Brief description
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
Have technology description in required use accompanying drawing be briefly described it should be apparent that, drawings in the following description be only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, acceptable
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is the automatic method flow diagram recommended of private guide of the embodiment of the present invention；
Fig. 2 is the frame diagram of the automatic system recommended of private guide of the embodiment of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawings the preferred embodiments of the present invention are described in detail, so that advantages and features of the invention energy
It is easier to be readily appreciated by one skilled in the art, thus protection scope of the present invention is made apparent clearly defining.
Central scope of the present invention is: by setting up the large database concept of a guide and visitor, this large database concept includes leading
The relevant information of trip and visitor's personal information.Confirm the consuming capacity and the consumption habit of this user according to visitor's personal information, so
It is based on large database concept afterwards automatically to recommend to conduct a sightseeing tour to visitor.
Embodiment one:
Fig. 1 is the method flow diagram of the automatic method recommended of private guide of the embodiment of the present invention；This individual guide is automatically
The method recommended, it comprises the following steps:
S1, the tour guide information of the private guide of acquisition；
S2, the travel information of acquisition visitor；
S3, the travel information to all history visitors are analyzed, and each item data obtaining in travel information selects in guide
Shared weight in selecting；
S4, the suitable guide of travel information foundation weight relationship coupling according to current visitor.
In step s1 and s2 of the present invention, obtain the tour guide information of private guide and the approach of the travel information of visitor includes
The related webpage of setting or the app of intelligent terminal, fill in tour guide information after guide and visitor's registration and tourist information are carried out
Obtain.
Wherein, the travel information of visitor includes: visitor's age, sex, tourist famous-city, language requirement and income.Guide
Information includes: guide's sex, guide's age, coverage, language, guide's grade, history meet an amount and guide's evaluation, Dao Youping
Assume that in valency and be divided into 1 star, 2 stars, 3 stars, 4 stars, 5 stars totally 5 ranks, 5 stars are highest.Visitor can be right after tourism terminates
Guide is scored).
In step s3 of the embodiment of the present invention, each item data obtaining in historical tourism information is shared in guide's selection
Weight includes:
S31, using each item data in the travel information of history visitor as influence factor, with each item number of each tour guide information
According to as evaluation points；Set up multiple different weight model；So weight model just can be corresponded with guide, root
Just can corresponding guide at recommendation according to calculating after the compound average of weight of weight model.
S32, calculate the weights corresponding to each item data of the travel information of history visitor in each weight model.According to power
Value may determine that every data influence degree to visitor for the tour guide information.
For example, may determine that tour guide information includes to every data influence degree of visitor according to weights: priority is successively
The coverage that reduces, language, guide's grade, guide are evaluated, guide's age, guide sex, history connect an amount.This priority is arranged
Sequence is that the history according to visitor selects guide's record analyses to draw, with the change of history selection guide's record of visitor, should
Prioritization also can change.
Step s4 of the present invention also includes,
S41, judge each item data proportion in the travel information of current visitor, judgment mode can pass through current visitor's
Directly fill in related proportion in the app of webpage or intelligent terminal；
Current weights synthesis average corresponding to visitor in s42, the different weight model of calculating；
S43, comprehensive average is ranked up toward low from high；
S44, each comprehensive average is corresponded to corresponding weight model, coupling is corresponding to conduct a sightseeing tour.
In the present invention, it is ranked up it is possible to weight model according to the comprehensive average of weights in different weight model
Corresponding different guide, that is, be equivalent to and carry out prioritization to guide, thus matching the guide being best suitable for current visitor successively.
Specifically, present invention additionally comprises step:
S5, the personal consumption historical record of the current visitor of acquisition；This personal consumption historical record can be by related net
The app historical record of page or intelligent terminal is obtained；
S6, the selection preference guide of the current visitor of analysis；Screened in the history guide of current visitor, judged
The guide mated most with this travel information；
S7, by described select preference guide screened with the guide mated by weight model, if repeated, then general
The guide repeating pushes at current visitor, if not repeating, pushing simultaneously and selecting the guide of preference and by weight model
The guide of coupling.
Below the recommendation method of the present invention is illustrated:
The first step, the coverage of guide are screened according to the tourist famous-city of visitor, obtain result a；For example: visitor
Tourist famous-city be: " Shanghai ", then coverage be " Shanghai " guide screened out, obtain result a；
Second step, on the basis of result a, according to guide language screened according to the language that visitor requires, obtain
Result b；For example: the language that visitor requires is " Chinese ", then only language is screened out for the guide of " Chinese ", obtains result
b；This result b is located in the range of the guide that coverage is " Shanghai " simultaneously.
3rd step, on the basis of result b, according to guide grade screened according to the income of visitor, obtain result
c；For example: guide's registration is divided into senior tour guide, middle rank guide and primary guide, when the income of visitor takes in ＞ 20000, then right
Answer senior tour guide；Income, in 10000-20000 corresponding middle rank guide, corresponds to primary guide less than 10000) screened, obtain
Result c, certainly, the correspondence of this income and guide's rank, Reasonable adjustment can be carried out according to the tourist famous-city of visitor.
4th step, on the basis of result c, age and sex according to guide carry out Integrated Selection, and the age is close and property
Not different carrying out mates, and obtains result d；
5th step, on the basis of result d, according to guide evaluation height, filter out front n name and obtain result e；For example,
Filter out top ten list e as a result.
6th step, on the basis of result e, the history according to guide connects an amount size, filters out the many front m bars of the group's of connecing amount
Data, obtains result f；For example, filter out front 20 data f as a result.
7th step, result f is pushed to visitor.
8th step, the history consumer record according to visitor, select the condition preference of guide to carry out screening and obtain result g；Example
As: visitor is screened to the place of guide it is necessary to be the guide of tourism purpose, is result g after being screened,
9th step, result f and result g are compared, the guide filtering out repetition promotes to this client, that is, this guide with
When possess preference and the consumption habit of visitor, such as no repetition, show result f and result g, and, before result g is shown in simultaneously
Face.Visitor is facilitated to carry out oneself judging to select.
Refering to shown in Fig. 2, the system that a kind of private guide of the present invention recommends automatically, comprising:
Data obtaining module 1, for obtaining the private tour guide information of guide and the travel information of visitor and personal consumption
Historical record；Acquiring way includes arranging the app of related webpage or intelligent terminal, is filled in and lead after guide and visitor's registration
Trip information and tourist information are obtained.
Weight model sets up module 2, selects in guide for obtaining each item data in the travel information of all history visitors
Shared weight in selecting；
Computing module 3, for calculating the weights synthesis average corresponding to current visitor in different weight model；
Order module 4, for being ranked up the weights synthesis average corresponding to current visitor；
Information display module 5, for being pushed to the guide after final screening at visitor.
Specifically, the system of the present invention also includes:
Preference screening module 6, for the case history consumer record according to current visitor, is carried out to the guide selecting preference
Screening.Wherein, data obtaining module 1 includes intelligent terminal app or website.
The present invention utilizes big data technology, obtains the tour guide information of private guide and the trip of visitor by data obtaining module
Trip information, then selects each influence factor of guide according to the travel information analysis visitor of visitor, thus setting up different power
Molality type, the travel information finally according to current visitor is conducted a sightseeing tour according to weight relationship coupling is suitable, so as to accomplish automatically and
More accurately recommend suitably private guide to visitor.
More than, the specific embodiment of the only present invention, but protection scope of the present invention is not limited thereto, any without
Cross the change or replacement that creative work is expected, all should be included within the scope of the present invention.Therefore, the protection of the present invention
Scope should be defined by the protection domain that claims are limited.
Claims (9)
1. a kind of method that private guide recommends automatically is it is characterised in that comprise the following steps:
S1, the tour guide information of the private guide of acquisition；
S2, the travel information of acquisition visitor；
S3, the travel information to all history visitors are analyzed, and each item data in acquisition travel information is in guide's selection
Shared weight；
S4, the suitable guide of travel information foundation weight relationship coupling according to current visitor.
2. private guide as claimed in claim 1 recommends automatically method is it is characterised in that the travel information of described visitor
Every data includes: visitor's age, sex, tourist famous-city, language requirement and income.
3. private guide as claimed in claim 2 recommends automatically method is it is characterised in that each item number of described tour guide information
According to inclusion: guide's sex, guide's age, coverage, language, guide's grade, history connect an amount and guide's evaluation.
4. the method that private guide as claimed in claim 3 recommends automatically is it is characterised in that in described step s3, acquisition is gone through
Each item data in history travel information shared weight in guide's selection includes:
S31, using each item data in the travel information of history visitor as influence factor, made with each item data of each tour guide information
For evaluation points；Set up multiple different weight model；
S32, calculate the weights corresponding to each item data of the travel information of history visitor in each weight model.
5. individual as claimed in claim 4 conducts a sightseeing tour the method automatically recommended it is characterised in that described step s4 also includes,
S41, judge each item data proportion in the travel information of current visitor；
Current weights synthesis average corresponding to visitor in s42, the different weight model of calculating；
S43, comprehensive average is ranked up toward low from high；
S44, each comprehensive average is corresponded to corresponding weight model, coupling is corresponding to conduct a sightseeing tour.
6. the method that private guide as claimed in claim 5 recommends automatically is it is characterised in that further comprise the steps of:
S5, the personal consumption historical record of the current visitor of acquisition；
S6, the selection preference guide of the current visitor of analysis；
S7, by described select preference guide screened with the guide mated by weight model, if repeated, then will repeat
Guide push at current visitor, if not repeating, simultaneously push select preference guide mate with by weight model
Guide.
7. the system that a kind of private guide recommends automatically is it is characterised in that include:
Data obtaining module, for obtaining the private tour guide information of guide and the travel information of visitor and personal consumption history note
Record；
Weight model sets up module, for obtaining the institute in guide's selection of each item data in the travel information of all history visitors
The weight accounting for；
Computing module, for calculating the weights synthesis average corresponding to current visitor in different weight model；
Order module, for being ranked up the weights synthesis average corresponding to current visitor；
Information display module, for being pushed to the guide after final screening at visitor.
8. the system that private guide as claimed in claim 7 recommends automatically is it is characterised in that also include:
Preference screening module, for the case history consumer record according to current visitor, screens to the guide selecting preference.
9. private guide as claimed in claim 7 or 8 recommends automatically system is it is characterised in that described information acquisition module
Including intelligent terminal app or website.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610807434.1A CN106372970A (en) | 2016-09-07 | 2016-09-07 | Private tour guide automatic recommendation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610807434.1A CN106372970A (en) | 2016-09-07 | 2016-09-07 | Private tour guide automatic recommendation method and system |
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| CN106372970A true CN106372970A (en) | 2017-02-01 |
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ID=57900251
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| CN201610807434.1A Pending CN106372970A (en) | 2016-09-07 | 2016-09-07 | Private tour guide automatic recommendation method and system |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107016076A (en) * | 2017-03-27 | 2017-08-04 | 北京游享伟业科技有限公司 | The method for recommend the method for guide to visitor, recommending the method for visitor to guide and recommend group friend to visitor |
| CN107222562A (en) * | 2017-07-03 | 2017-09-29 | 深圳市乐唯科技开发有限公司 | A kind of user's intelligent recommendation system based on Internet user's feature |
| CN109064357A (en) * | 2018-08-22 | 2018-12-21 | 潘皓波 | A kind of tour guide's recommender system and method in real time |
| CN109409916A (en) * | 2017-08-18 | 2019-03-01 | 徐子明 | A kind of Tourism Marketing system based on big data platform |
| WO2023179314A1 (en) * | 2022-03-22 | 2023-09-28 | 云游天下(北京)科技有限公司 | Smart tourism service method and apparatus, and storage medium and server |
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| CN1358019A (en) * | 2001-12-31 | 2002-07-10 | 阮闯 | Global electronic tourist guide system and method |
| CN201607767U (en) * | 2010-03-19 | 2010-10-13 | 冯祥 | Personalized 3G tour-guide interpretive service system |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107016076A (en) * | 2017-03-27 | 2017-08-04 | 北京游享伟业科技有限公司 | The method for recommend the method for guide to visitor, recommending the method for visitor to guide and recommend group friend to visitor |
| CN107222562A (en) * | 2017-07-03 | 2017-09-29 | 深圳市乐唯科技开发有限公司 | A kind of user's intelligent recommendation system based on Internet user's feature |
| CN109409916A (en) * | 2017-08-18 | 2019-03-01 | 徐子明 | A kind of Tourism Marketing system based on big data platform |
| CN109409916B (en) * | 2017-08-18 | 2021-10-22 | 重庆赫皇科技咨询有限公司 | Tourism marketing system based on big data platform |
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