CN115935076A - Travel service information pushing method and system based on artificial intelligence - Google Patents

Travel service information pushing method and system based on artificial intelligence Download PDF

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Publication number
CN115935076A
CN115935076A CN202310134950.2A CN202310134950A CN115935076A CN 115935076 A CN115935076 A CN 115935076A CN 202310134950 A CN202310134950 A CN 202310134950A CN 115935076 A CN115935076 A CN 115935076A
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service
travel service
order
target
travel
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陈文波
李妙瑜
刘旭
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Zhuhai Dahengqin Pan Tourism Development Co ltd
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Zhuhai Dahengqin Pan Tourism Development Co ltd
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract

The invention relates to the field of artificial intelligence, and discloses a travel service information pushing method and system based on artificial intelligence, which are used for the accuracy of travel service information pushing. The method comprises the following steps: performing accent feature recognition and voice text conversion on the online voice data to obtain a target voice text, and performing user demand detection on the target voice text to obtain a travel service demand; generating order information of target old tourists according to the tourism service demands, dividing the order information into order types to obtain a target order type, and matching the pictures of the tourism service personnel according to the tourism service demands to obtain a plurality of candidate tourism service personnel; obtaining the current order receiving quantity, and calculating the order dispatching crowdedness degree of a plurality of candidate travel service personnel according to the current order receiving quantity to obtain the order dispatching crowdedness degree; and selecting target travel service personnel according to the dispatch crowdedness degree and the target dispatch type.

Description

Artificial intelligence-based travel service information pushing method and system
Technical Field
The invention relates to the field of artificial intelligence, in particular to a tourism service information pushing method and system based on artificial intelligence.
Background
With the continuous development of the internet, the tourism industry is developing towards informatization, networking and automation. The artificial intelligence technology is introduced into the tourism service, so that the effective management of the tourism resources and the intelligent and efficient analysis of the tourism information are realized, the integration of the existing tourism resources is facilitated, and unprecedented convenience and brand-new service are brought to tourists. The old people are the people with the largest demand in the travel service industry, some old people only capable of saying dialects exist in the old people, and the travel service scheme aiming at the old people is lacked at present.
According to the existing scheme, the related information of tourists is provided for the tourists to the tourism service management platform, or a recommendation channel is published to the social platform of the tourists, so that the tourists at the sides can submit the related information to the tourism service management platform through the recommendation channel, but the recommendation accuracy rate of the existing scheme for old tourist groups is low.
Disclosure of Invention
The invention provides a travel service information pushing method and system based on artificial intelligence, which are used for the accuracy of travel service information pushing.
The invention provides a travel service information pushing method based on artificial intelligence, which comprises the following steps: acquiring order data of a plurality of travel service personnel from a preset travel service order database, and carrying out order classification and personnel configuration on the order data to obtain a historical service order of each travel service personnel; performing order feature extraction on a historical service order of each travel service person to obtain historical order features of each travel service person, performing cluster analysis on the historical order features of each travel service person to generate a travel service person representation of each travel service person, wherein the travel service person representation is used for indicating the type of travel service which the travel service person is good at; the method comprises the steps of obtaining online voice data of a target old visitor, carrying out accent feature recognition and voice text conversion on the online voice data to obtain a target voice text, carrying out user demand detection on the target voice text to obtain a travel service demand of the target old visitor, wherein the travel service demand comprises: medical service requirements, catering service requirements and tour guide service requirements; generating order information of the target old visitor according to the travel service demand, dividing the order information into order types to obtain a target order type corresponding to the order information, and matching the tourist service personnel portrait according to the travel service demand to obtain a plurality of candidate tourist service personnel related to the target old visitor; obtaining the current order receiving quantity of each candidate travel service staff, and calculating the order dispatching crowdedness degree of the candidate travel service staff according to the current order receiving quantity of each candidate travel service staff to obtain the order dispatching crowdedness degree; and selecting target travel service personnel from the candidate travel service personnel according to the dispatch crowdedness and the target dispatch type, and dispatching the order information of the target old tourist to the target travel service personnel.
Optionally, in a first implementation manner of the first aspect of the present invention, the performing order feature extraction on the historical service order of each travel service person to obtain the historical order feature of each travel service person, and performing cluster analysis on the historical order feature of each travel service person to generate the travel service person representation of each travel service person, where the travel service person representation is used to indicate a type of travel service that the travel service person is good at, includes: extracting a plurality of service types of the historical service orders of each travel service personnel and the service frequency corresponding to each service type; generating historical order characteristics of each travel service personnel according to the plurality of service types and the service frequency corresponding to each service type; the historical order characteristics for each travel service representative are clustered to generate a travel service representative profile for each travel service representative, wherein the travel service representative profiles are indicative of the types of travel services that the travel service representative is good at.
Optionally, in a second implementation manner of the first aspect of the present invention, the obtaining online voice data of the target elderly visitor, performing accent feature recognition and voice text conversion on the online voice data to obtain a target voice text, and performing user requirement detection on the target voice text to obtain a travel service requirement of the target elderly visitor, where the travel service requirement includes: medical service needs, food and beverage service needs and tour guide service needs include: receiving a travel service request sent by a target old visitor, and acquiring online voice data of the target old visitor according to the travel service request; carrying out accent feature recognition on the online voice data to obtain accent categories and acoustic features corresponding to the online voice data; performing voice text conversion on the online voice data according to the accent type and the acoustic characteristics to obtain a target voice text; and detecting user requirements of the target voice text to obtain the tourism service requirements of the target old visitor, wherein the tourism service requirements comprise: medical service needs, catering service needs and tour guide service needs.
Optionally, in a third implementation manner of the first aspect of the present invention, the generating order information of the target elderly visitor according to the travel service requirement, performing dispatch type division on the order information to obtain a target dispatch type corresponding to the order information, and matching the images of the travel service staff according to the travel service requirement to obtain a plurality of candidate travel service staff related to the target elderly visitor includes: generating an ordering interface according to the travel service requirement, and generating order information of the target old tourist according to the ordering interface; performing order dispatching type division on the order information according to a preset order dispatching index to obtain a target order dispatching type corresponding to the order information, wherein the target order dispatching type comprises: urgent, urgent and normal; and calculating a correlation coefficient between the travel service demand and the travel service person representation, and taking the travel service person representation with the correlation coefficient larger than a preset target value as a plurality of candidate travel service persons related to the target old tourist.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the obtaining the current order taking amount of each candidate travel service person, and performing order dispatching congestion degree calculation on the plurality of candidate travel service persons according to the current order taking amount of each candidate travel service person to obtain the order dispatching congestion degree includes: acquiring the current bill receiving quantity of each candidate tourist service staff; calculating the congestion degree of the current service node of each candidate travel service staff according to the current order receiving quantity of each candidate travel service staff; and generating the dispatch congestion degree according to the congestion degree of the current service node of each candidate travel service staff.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the selecting a target travel service staff from the multiple candidate travel service staff according to the dispatch congestion degree and the target dispatch type, and dispatching order information of the target elderly visitor to the target travel service staff includes: sequencing the plurality of candidate travel service personnel according to the dispatch crowdedness degree to obtain a candidate travel service personnel sequence; matching target travel service personnel from the sequence of candidate travel service personnel according to the type of the target order; and generating a visual form according to the order information of the target old visitor, and dispatching the order information of the target old visitor to the target travel service staff according to the visual form.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the artificial intelligence based travel service information pushing method further includes: acquiring image data uploaded by the target travel service personnel; performing service evaluation on the target travel service personnel according to the image data to obtain a first service evaluation index; obtaining phone call return visit data of the target old visitor, and performing service evaluation analysis on the phone call return visit data to obtain a second service evaluation index; judging whether the first service evaluation index and the second service evaluation index are consistent or not to obtain a judgment result; and generating comprehensive service evaluation corresponding to the target travel service personnel according to the judgment result.
The second aspect of the present invention provides a travel service information pushing system based on artificial intelligence, wherein the travel service information pushing system based on artificial intelligence comprises: the acquisition module is used for acquiring order data of a plurality of travel service personnel from a preset travel service order database, and carrying out order classification and personnel configuration on the order data to obtain a historical service order of each travel service personnel; the extraction module is used for carrying out order feature extraction on the historical service order of each travel service person to obtain the historical order feature of each travel service person, carrying out cluster analysis on the historical order feature of each travel service person to generate a travel service person representation of each travel service person, wherein the travel service person representation is used for indicating the type of travel service which the travel service person is good at; the detection module is used for acquiring online voice data of the target old tourist, performing accent feature recognition and voice text conversion on the online voice data to obtain a target voice text, performing user demand detection on the target voice text to obtain the travel service demand of the target old tourist, wherein the travel service demand comprises: medical service requirements, catering service requirements and tour guide service requirements; the matching module is used for generating order information of the target old visitor according to the travel service demand, dividing the order information into order types to obtain a target order type corresponding to the order information, and matching the tourist service personnel figures according to the travel service demand to obtain a plurality of candidate tourist service personnel related to the target old visitor; the calculation module is used for acquiring the current order receiving quantity of each candidate travel service personnel and calculating the order dispatching crowdedness degree of the candidate travel service personnel according to the current order receiving quantity of each candidate travel service personnel to obtain the order dispatching crowdedness degree; and the order dispatching module is used for selecting target travel service personnel from the candidate travel service personnel according to the order dispatching crowdedness and the target order dispatching type and dispatching the order information of the target old tourist to the target travel service personnel.
Optionally, in a first implementation manner of the second aspect of the present invention, the extracting module is specifically configured to: extracting a plurality of service types of the historical service orders of each travel service personnel and the service frequency corresponding to each service type; generating historical order characteristics of each travel service personnel according to the plurality of service types and the service frequency corresponding to each service type; the historical order characteristics for each travel service representative are clustered to generate a travel service representative representation for each travel service representative, wherein the travel service representative representation indicates the type of travel service that the travel service representative is good at.
Optionally, in a second implementation manner of the second aspect of the present invention, the detection module is specifically configured to: receiving a travel service request sent by a target old visitor, and acquiring online voice data of the target old visitor according to the travel service request; carrying out accent feature recognition on the online voice data to obtain accent categories and acoustic features corresponding to the online voice data; performing voice text conversion on the online voice data according to the accent type and the acoustic characteristics to obtain a target voice text; and detecting user requirements of the target voice text to obtain the tourism service requirements of the target old visitor, wherein the tourism service requirements comprise: medical service needs, catering service needs and tour guide service needs.
Optionally, in a third implementation manner of the second aspect of the present invention, the matching module is specifically configured to: generating an ordering interface according to the travel service requirement, and generating order information of the target old tourist according to the ordering interface; performing order dispatching type division on the order information according to a preset order dispatching index to obtain a target order dispatching type corresponding to the order information, wherein the target order dispatching type comprises: urgent, urgent and normal; and calculating a correlation coefficient between the travel service demand and the travel service personnel portrait, and taking the travel service personnel portrait of which the correlation coefficient is greater than a preset target value as a plurality of candidate travel service personnel related to the target old visitor.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the calculation module is specifically configured to: acquiring the current bill receiving quantity of each candidate tourist service staff; calculating the crowdedness of the current service node of each candidate travel service staff according to the current bill receiving amount of each candidate travel service staff; and generating the dispatch congestion degree according to the congestion degree of the current service node of each candidate travel service staff.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the dispatch module is specifically configured to: sequencing the candidate travel service personnel according to the dispatch list crowdedness degree to obtain a candidate travel service personnel sequence; matching target travel service personnel from the sequence of candidate travel service personnel according to the type of the target order; and generating a visual form according to the order information of the target old visitor, and dispatching the order information of the target old visitor to the target travel service staff according to the visual form.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the artificial intelligence-based travel service information pushing apparatus further includes: the evaluation module is used for acquiring the image data uploaded by the target travel service personnel; performing service evaluation on the target travel service personnel according to the image data to obtain a first service evaluation index; obtaining phone call return visit data of the target old visitor, and performing service evaluation analysis on the phone call return visit data to obtain a second service evaluation index; judging whether the first service evaluation index and the second service evaluation index are consistent or not to obtain a judgment result; and generating comprehensive service evaluation corresponding to the target travel service personnel according to the judgment result.
The third aspect of the invention provides a tour service information pushing device based on artificial intelligence, comprising: a memory and at least one processor, the memory having instructions stored therein; the at least one processor invokes the instructions in the memory to cause the artificial intelligence based travel service information push device to perform the artificial intelligence based travel service information push method described above.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which, when run on a computer, cause the computer to execute the above-mentioned artificial intelligence based travel service information push method.
According to the technical scheme, the order data of a plurality of tourism service personnel are analyzed to obtain the tourism service type which is good for each tourism service personnel, the matching degree of the tourism service personnel and the target old visitor is improved, the online voice data of the target old visitor is subjected to accent analysis and text conversion, the tourism service requirement of the target old visitor is generated, the identification accuracy of the online voice data is improved by the accent analysis of the online voice data, the accuracy of the tourism service requirement analysis of the target old visitor is improved, the dispatch type is analyzed, the matching degree of the tourist service personnel image and the target old visitor is higher, the dispatch crowdedness degree is calculated, the dispatch is carried out according to the calculation result, and the accuracy of the tourism service information pushing and the dispatch is improved.
Drawings
FIG. 1 is a schematic diagram of an embodiment of an artificial intelligence based travel service information pushing method according to the invention;
FIG. 2 is a schematic view of another embodiment of an artificial intelligence based travel service information push method according to the present invention;
FIG. 3 is a schematic view of an embodiment of an artificial intelligence based travel service information push system in accordance with the present invention;
FIG. 4 is a schematic view of another embodiment of an artificial intelligence based travel service information push system in accordance with one embodiment of the present invention;
FIG. 5 is a schematic diagram of an embodiment of an artificial intelligence based travel service information push device in accordance with the present invention.
Detailed Description
The embodiment of the invention provides a travel service information pushing method and system based on artificial intelligence, which are used for the accuracy of travel service information pushing. The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For convenience of understanding, a specific flow of the embodiment of the present invention is described below, and referring to fig. 1, an embodiment of the artificial intelligence based travel service information pushing method in the embodiment of the present invention includes:
101. acquiring order data of a plurality of travel service personnel from a preset travel service order database, and carrying out order classification and personnel configuration on the order data to obtain a historical service order of each travel service personnel;
it is understood that the execution subject of the present invention may be the travel service information pushing system based on artificial intelligence, and may also be a terminal or a server, which is not limited herein. The embodiment of the present invention is described by taking a server as an execution subject.
Specifically, the server acquires order data of a plurality of travel service personnel from a preset travel service order database, generates historical order data according to service start time and service end time in historical order information, and optionally generates order start time according to the service start time in the order information; and generating order ending time according to the service ending time in the order information. The server calculates order time according to service start time and first preset buffer time in the order information, or calculates order end time according to service end time and second preset buffer time in the order information, wherein the order end time is later than the service end time, for example, the first preset buffer time is one day after the service end time, the tour guide end time is 5 months and 15 days, and 16 days are used as the order end time to perform order classification and personnel configuration on order data, so as to obtain a historical service order of each tour service personnel.
102. Performing order feature extraction on the historical service order of each travel service person to obtain the historical order feature of each travel service person, performing cluster analysis on the historical order feature of each travel service person to generate a travel service person representation of each travel service person, wherein the travel service person representation is used for indicating the types of travel services which the travel service person is good at;
specifically, the order characteristics are selected, the order characteristic information gain value is calculated to generate a preselected characteristic subset, the optimal candidate characteristic subset is selected by utilizing a decision tree C4.5 algorithm, the subset is generated by utilizing a sequence forward floating search algorithm, the subset is evaluated by utilizing the decision tree C4.5 algorithm to obtain the finally selected characteristic subset, the historical order characteristics of each travel service worker are subjected to cluster analysis, the travel service worker figure of each travel service worker is generated, different evaluation standards can be adopted at different search stages, the rapid calculation characteristic of a Filter algorithm and the high classification precision advantage of a Wrapper algorithm are combined through the information gain and sequence forward floating search mixed characteristic selection algorithm, the performance of the algorithm is guaranteed, the time complexity of the algorithm is reduced, the dynamic search characteristic of the characteristic subset is provided, the possibility of characteristic nesting is avoided, and the high suspicious order identification rate can be obtained.
103. Obtain old visitor's of target online speech data to carry out accent feature recognition and speech text conversion to online speech data, obtain the target speech text, and carry out user's demand to the target speech text and detect, obtain old visitor's of target tourism service demand, the tourism service demand includes: medical service requirements, catering service requirements and tour guide service requirements;
specifically, the server obtains current character information, current word information, current part of speech information and current manual extraction characteristics output by voice recognition, the characteristics are input into the multitask neural network model, and the multitask neural network model outputs an inverse text conversion mark of each current character. The method comprises the steps of obtaining an inverse text conversion result of a current character according to an inverse text conversion mark of the current character and a set inverse text conversion specification, adjusting the inverse text conversion result of the current character according to the smoothness probability of the current character and the probability of a set punctuation mark to be marked behind the current character, obtaining a processing result after voice recognition, performing accent feature recognition and voice text conversion on online voice data to obtain a target voice text, detecting user requirements on the target voice text to obtain the tourism service requirements of a target old visitor, and performing multi-task modeling through a network to enable the operation speed and processing to be faster. The text recognition is more humanized. The man-machine interaction is more natural, a mask authentication network with stronger learning capability is applied, and a network output strategy is added.
104. Generating order information of target old tourists according to the tourism service demands, carrying out dispatch type division on the order information to obtain a target dispatch type corresponding to the order information, and matching the pictures of the tourism service staff according to the tourism service demands to obtain a plurality of candidate tourism service staff related to the target old tourists;
specifically, order information is obtained, wherein the order information is used for representing an order state and/or an order use condition, and a work order to be operated is generated according to the order information and a preset work order generation rule, wherein the work order generation rule comprises a corresponding relation between the order information and a work order type; according to a preset work order distribution rule, the work orders to be operated are sent to corresponding target personnel, the order information is divided into order types, the target order types corresponding to the order information are obtained, images of the travel service personnel are matched according to travel service requirements, and a plurality of candidate travel service personnel related to the target old tourists are obtained, so that the target service personnel can operate according to the work orders to be operated.
105. Obtaining the current order receiving quantity of each candidate travel service staff, and calculating the order dispatching crowdedness degree of a plurality of candidate travel service staff according to the current order receiving quantity of each candidate travel service staff to obtain the order dispatching crowdedness degree;
the method comprises the steps of obtaining the current order receiving quantity of service personnel, determining the crowding degree of the service personnel according to the current order receiving quantity of the service personnel and a current order receiving quantity threshold value, and determining the weight of the crowding degree according to the crowding degree of the service personnel so as to determine the current order dispatching weight of the service personnel according to the weight of the crowding degree and dispatch the service personnel. The system can improve a device for calculating the dispatch congestion degree of service personnel such as a dispatch mechanism and the like, reduce the condition of order taking and two-pole differentiation of service personnel such as tourists and the like, initialize the current order taking amount of the service personnel to be 0 under the condition that the service personnel such as tourists and the like go on line to open an order taking switch, set the threshold value threshold of the congestion degree to be 10, and reduce the calculation result of the congestion degree to be about 0, add 1 to the current order taking amount of the service personnel under the condition that the service personnel receives the dispatch order, update the congestion degree of the service personnel through a service personnel congestion degree calculation model, and finally calculate the dispatch congestion degree of a plurality of candidate tourism service personnel according to the current order taking amount of each candidate tourism service personnel to obtain the dispatch congestion degree.
106. And selecting target travel service personnel from the plurality of candidate travel service personnel according to the dispatch list crowdedness degree and the target dispatch list type, and dispatching the order information of the target old tourists to the target travel service personnel.
Specifically, a plurality of pieces of user business order data are screened to obtain at least one piece of corresponding target user business order data, wherein each user terminal device generates corresponding user business order data based on business order selection operation performed by a corresponding order user, a business processing user corresponding to the target user business order data is determined for each piece of target user business order data, whether the business processing user can perform business processing operation or not is determined, and for each piece of target user business order data, if the corresponding business processing user cannot perform business processing operation, a final server selects a target tourist service person from a plurality of candidate tourist service persons according to the dispatch crowding degree and the target dispatch type and dispatches the order information of the target old tourist to the target tourist service person.
In the embodiment of the invention, the order data of a plurality of tourism service personnel are analyzed to obtain the adequacy tourism service type of each tourism service personnel, which is beneficial to improving the matching degree of the tourism service personnel and the target old visitor, the online voice data of the target old visitor is subjected to accent analysis and text conversion to generate the tourism service requirement of the target old visitor, the online voice data is subjected to accent analysis to improve the recognition accuracy of the online voice data, the tourism service requirement analysis accuracy of the target old visitor is improved, the dispatch type is analyzed to ensure that the matching degree of the tourist service personnel portrait and the target old visitor is higher, and finally the dispatch crowdedness degree is calculated, and the dispatch is carried out according to the calculation result to improve the accuracy of the tourism service information pushing and the dispatch.
Referring to FIG. 2, another embodiment of the artificial intelligence based travel service information pushing method according to the present invention comprises:
201. obtaining order data of a plurality of tourism service personnel from a preset tourism service order database, and carrying out order classification and personnel configuration on the order data to obtain a historical service order of each tourism service personnel;
specifically, in this embodiment, the specific implementation of step 201 is similar to that of step 101, and is not described herein again.
202. Performing order feature extraction on the historical service order of each travel service person to obtain the historical order feature of each travel service person, performing cluster analysis on the historical order feature of each travel service person to generate a travel service person representation of each travel service person, wherein the travel service person representation is used for indicating the types of travel services which the travel service person is good at;
specifically, a plurality of service types of historical service orders of each travel service personnel and service frequency corresponding to each service type are extracted; generating historical order characteristics of each travel service personnel according to the plurality of service types and the service frequency corresponding to each service type; the historical order characteristics for each travel service representative are clustered to generate a travel service representative representation for each travel service representative, wherein the travel service representative representation is used to indicate the type of travel service that the travel service representative is good at.
The server extracts a plurality of service types of historical service orders of each travel service worker and service frequency corresponding to each service type; generating historical order features of each travel service staff according to a plurality of service types and service frequencies corresponding to each service type, carrying out cluster analysis on the historical order features by using a clustering algorithm embedded by a genetic algorithm and a K-modes model, counting the number of samples in each group by researching the distribution rule of the groups and the distance between clustering centers, calculating the distribution density in each group, analyzing the historical order features of a selected area, and providing a historical order feature dividing method by using regional historical order feature data in a database and adopting an analysis method embedded by the genetic algorithm and a K-modes so as to analyze and research the historical order features and have better clustering effect and stability.
203. Obtain old visitor's of target online speech data to carry out accent feature recognition and speech text conversion to online speech data, obtain the target speech text, and carry out user's demand to the target speech text and detect, obtain old visitor's of target tourism service demand, the tourism service demand includes: medical service requirements, catering service requirements and tour guide service requirements;
specifically, a travel service request sent by a target old visitor is received, and online voice data of the target old visitor are obtained according to the travel service request; carrying out accent feature recognition on the online voice data to obtain accent categories and acoustic features corresponding to the online voice data; performing voice text conversion on the online voice data according to the accent category and the acoustic characteristics to obtain a target voice text; user demand detection is carried out on the target voice text, and tourism service demands of the target old tourists are obtained, wherein the tourism service demands comprise: medical service needs, catering service needs and tour guide service needs.
The method comprises the steps that a server receives a travel service request sent by a target old visitor and obtains online voice data of the target old visitor according to the travel service request, wherein the server obtains a first voice recognition text which is obtained based on voice recognition, corrects partial words in the first voice recognition text to obtain a second voice recognition text, and deletes redundant information in the second voice recognition text to obtain a third voice recognition text; and based on the grammar semantic correction and the language style correction, converting the third voice recognition text into a target voice recognition text, and detecting the user demand of the target voice text to obtain the tourism service demand of the target old tourist, wherein the tourism service demand comprises: medical service needs, catering service needs and tour guide service needs. Through error correction, redundancy removal, semantic correction and written conversion, the accuracy of voice recognition is efficiently improved greatly, the voice is converted into an accurate and smooth written text, and the user experience of voice recognition is improved.
204. Generating order information of target old tourists according to the tourism service demands, carrying out order type division on the order information to obtain a target order type corresponding to the order information, and matching the pictures of the tourism service staff according to the tourism service demands to obtain a plurality of candidate tourism service staff related to the target old tourists;
specifically, an ordering interface is generated according to the travel service requirement, and order information of the target old tourists is generated according to the ordering interface; performing order dispatching type division on the order information according to a preset order dispatching index to obtain a target order dispatching type corresponding to the order information, wherein the target order dispatching type comprises the following steps: urgent, urgent and normal; and calculating a correlation coefficient between the travel service demand and the travel service person portrait, and taking the travel service person portrait with the number of the correlations larger than a preset target value as a plurality of candidate travel service persons related to the target old visitor.
How to realize point-to-point quick matching of a task list and support personnel, constructing a classification rule of a travel service demand based on the characteristics of the travel service demand, determining an event type, a task type, an event grade, a retrieval professional type and a retrieval event grade corresponding to the travel service demand by the classification rule, generating target list sending time based on the classification rule for a reported target list sending type, generating a corresponding task list by combining a target area corresponding to the target list sending type, retrieving candidate travel service personnel on duty currently based on a configured retrieval rule set based on a pre-defined area, selecting the candidate travel service personnel meeting the matching degree as a list sending person based on the configured matching rule set, and sending the task list to the travel service personnel.
205. Obtaining the current order receiving quantity of each candidate travel service staff, and calculating the order dispatching crowdedness degree of a plurality of candidate travel service staff according to the current order receiving quantity of each candidate travel service staff to obtain the order dispatching crowdedness degree;
specifically, the current admission amount of each candidate travel service personnel is obtained; calculating the crowdedness of the current service node of each candidate travel service staff according to the current bill receiving amount of each candidate travel service staff; and generating the dispatch list congestion degree according to the congestion degree of the current service node of each candidate travel service staff.
The method comprises the steps of obtaining the current order receiving quantity of service personnel, determining the crowding degree of the service personnel according to the current order receiving quantity of the service personnel and a current order receiving quantity threshold value, and determining the weight of the crowding degree according to the crowding degree of the service personnel so as to determine the current order dispatching weight of the service personnel according to the weight of the crowding degree and dispatch the service personnel. The system can improve a device for calculating the dispatch congestion degree of service personnel such as a dispatch mechanism and the like, reduce the condition of order taking and two-pole differentiation of service personnel such as tourists and the like, initialize the current order taking amount of the service personnel to be 0 under the condition that the service personnel such as tourists and the like go on line to open an order taking switch, set the threshold value threshold of the congestion degree to be 10, and reduce the calculation result of the congestion degree to be about 0, add 1 to the current order taking amount of the service personnel under the condition that the service personnel receives the dispatch order, update the congestion degree of the service personnel through a service personnel congestion degree calculation model, and finally calculate the dispatch congestion degree of a plurality of candidate tourism service personnel according to the current order taking amount of each candidate tourism service personnel to obtain the dispatch congestion degree.
206. Sequencing a plurality of candidate travel service personnel according to the dispatch crowdedness degree to obtain a candidate travel service personnel sequence;
207. matching the target travel service personnel from the candidate travel service personnel sequence according to the target order type;
specifically, the plurality of candidate travel service personnel are sequenced according to the dispatch crowdedness degree to obtain a candidate travel service personnel sequence, then a travel service personnel visual table is generated according to the service personnel sequence, and finally the server matches the target travel service personnel from the candidate travel service personnel sequence according to the visual table and based on the target dispatch type.
208. And generating a visual form according to the order information of the target old visitor, and dispatching the order information of the target old visitor to the target tourism service personnel according to the visual form.
Optionally, acquiring image data uploaded by the target travel service personnel; performing service evaluation on the target travel service personnel according to the image data to obtain a first service evaluation index; obtaining phone return visit data of the target old visitor, and performing service evaluation analysis on the phone return visit data to obtain a second service evaluation index; judging whether the first service evaluation index and the second service evaluation index are consistent or not to obtain a judgment result; and generating comprehensive service evaluation corresponding to the target travel service personnel according to the judgment result.
The method comprises the steps that a server acquires image data uploaded by target tourism service personnel, tourism service evaluation is usually carried out by adopting a single evaluation index, influence of various factors on the tourism service level cannot be considered comprehensively, and a complete evaluation index system is established by adopting a bottom-layer evaluation index based on four aspects of client appeal, responsibility attribution, transaction level and service processing. Obtaining a score distribution type through a double-layer clustering model, determining central scores of evaluation grades under different types of distributions, converting the scores of the evaluation indexes into easily understood evaluation grades through a fuzzy evaluation method, performing visual evaluation on the quality of the tourism service, acquiring call return data of the target old tourists, and performing service evaluation analysis on the call return data to obtain a second service evaluation index; judging whether the first service evaluation index and the second service evaluation index are consistent or not to obtain a judgment result; and generating comprehensive service evaluation corresponding to the target travel service personnel according to the judgment result. The client-side travel service analysis method based on the structured chemical order data can quickly and effectively evaluate the travel service level according to the structured work order data, and is beneficial to improving the client-side travel service level and accurately positioning the service weak point.
In the embodiment of the invention, the order data of a plurality of tourism service personnel are analyzed to obtain the adequacy tourism service type of each tourism service personnel, which is beneficial to improving the matching degree of the tourism service personnel and the target old visitor, the online voice data of the target old visitor is subjected to accent analysis and text conversion to generate the tourism service requirement of the target old visitor, the online voice data is subjected to accent analysis to improve the recognition accuracy of the online voice data, the tourism service requirement analysis accuracy of the target old visitor is improved, the dispatch type is analyzed to ensure that the matching degree of the tourist service personnel portrait and the target old visitor is higher, and finally the dispatch crowdedness degree is calculated, and the dispatch is carried out according to the calculation result to improve the accuracy of the tourism service information pushing and the dispatch.
Referring to fig. 3, the artificial intelligence based travel service information push system in the embodiment of the present invention includes:
the acquisition module 301 is configured to acquire order data of a plurality of travel service personnel from a preset travel service order database, and perform order classification and personnel configuration on the order data to obtain a historical service order of each travel service personnel;
an extracting module 302, configured to perform order feature extraction on the historical service order of each travel service person to obtain the historical order feature of each travel service person, perform cluster analysis on the historical order feature of each travel service person, and generate a travel service person representation of each travel service person, where the travel service person representation is used to indicate a type of travel service that the travel service person is good at;
the detection module 303 is configured to acquire online voice data of a target elderly visitor, perform accent feature recognition and voice text conversion on the online voice data to obtain a target voice text, and perform user demand detection on the target voice text to obtain a travel service demand of the target elderly visitor, where the travel service demand includes: medical service requirements, catering service requirements and tour guide service requirements;
the matching module 304 is used for generating order information of the target old visitor according to the travel service demand, dividing the order information into order types to obtain a target order type corresponding to the order information, and matching the tourist service personnel figures according to the travel service demand to obtain a plurality of candidate tourist service personnel related to the target old visitor;
the calculating module 305 is configured to obtain the current order taking amount of each candidate travel service person, and calculate the order sending congestion degree of the candidate travel service persons according to the current order taking amount of each candidate travel service person to obtain the order sending congestion degree;
and the dispatching module 306 is used for selecting target travel service personnel from the candidate travel service personnel according to the dispatching crowdedness and the target dispatching type and dispatching the order information of the target old tourist to the target travel service personnel.
In the embodiment of the invention, the order data of a plurality of tourism service personnel are analyzed to obtain the adequacy tourism service type of each tourism service personnel, which is beneficial to improving the matching degree of the tourism service personnel and the target old visitor, the online voice data of the target old visitor is subjected to accent analysis and text conversion to generate the tourism service requirement of the target old visitor, the online voice data is subjected to accent analysis to improve the recognition accuracy of the online voice data, the tourism service requirement analysis accuracy of the target old visitor is improved, the dispatch type is analyzed to ensure that the matching degree of the tourist service personnel portrait and the target old visitor is higher, and finally the dispatch crowdedness degree is calculated, and the dispatch is carried out according to the calculation result to improve the accuracy of the tourism service information pushing and the dispatch.
Referring to FIG. 4, another embodiment of the artificial intelligence based travel service information push system according to the present invention comprises:
the acquisition module 301 is configured to acquire order data of a plurality of travel service staff from a preset travel service order database, and perform order classification and staff configuration on the order data to obtain a historical service order of each travel service staff;
an extracting module 302, configured to perform order feature extraction on the historical service order of each travel service person to obtain the historical order feature of each travel service person, perform cluster analysis on the historical order feature of each travel service person, and generate a travel service person representation of each travel service person, where the travel service person representation is used to indicate a type of travel service that the travel service person is good at;
the detection module 303 is configured to acquire online voice data of a target elderly visitor, perform accent feature recognition and voice text conversion on the online voice data to obtain a target voice text, and perform user demand detection on the target voice text to obtain a travel service demand of the target elderly visitor, where the travel service demand includes: medical service requirements, catering service requirements and tour guide service requirements;
the matching module 304 is used for generating order information of the target old visitor according to the travel service demand, dividing the order information into order types to obtain a target order type corresponding to the order information, and matching the tourist service personnel figures according to the travel service demand to obtain a plurality of candidate tourist service personnel related to the target old visitor;
the calculation module 305 is configured to obtain a current order receiving amount of each candidate travel service person, and calculate the order dispatching congestion degree of the candidate travel service persons according to the current order receiving amount of each candidate travel service person to obtain the order dispatching congestion degree;
and the dispatching module 306 is used for selecting target travel service personnel from the candidate travel service personnel according to the dispatching crowdedness and the target dispatching type and dispatching the order information of the target old tourist to the target travel service personnel.
Optionally, the extracting module 302 is specifically configured to: extracting a plurality of service types of the historical service orders of each travel service personnel and the service frequency corresponding to each service type; generating historical order characteristics of each travel service personnel according to the plurality of service types and the service frequency corresponding to each service type; the historical order characteristics for each travel service representative are clustered to generate a travel service representative profile for each travel service representative, wherein the travel service representative profiles are indicative of the types of travel services that the travel service representative is good at.
Optionally, the detecting module 303 is specifically configured to: receiving a travel service request sent by a target old visitor, and acquiring online voice data of the target old visitor according to the travel service request; carrying out accent feature recognition on the online voice data to obtain accent categories and acoustic features corresponding to the online voice data; performing voice text conversion on the online voice data according to the accent type and the acoustic characteristics to obtain a target voice text; and detecting user requirements of the target voice text to obtain the tourism service requirements of the target old visitor, wherein the tourism service requirements comprise: medical service needs, catering service needs and tour guide service needs.
Optionally, the matching module 304 is specifically configured to: generating an order interface according to the tourism service requirement, and generating order information of the target old visitor according to the order interface; performing order dispatching type division on the order information according to a preset order dispatching index to obtain a target order dispatching type corresponding to the order information, wherein the target order dispatching type comprises: urgent, urgent and normal; and calculating a correlation coefficient between the travel service demand and the travel service person representation, and taking the travel service person representation with the correlation coefficient larger than a preset target value as a plurality of candidate travel service persons related to the target old tourist.
Optionally, the calculating module 305 is specifically configured to: acquiring the current bill receiving quantity of each candidate tourism service worker; calculating the congestion degree of the current service node of each candidate travel service staff according to the current order receiving quantity of each candidate travel service staff; and generating the dispatch congestion degree according to the congestion degree of the current service node of each candidate travel service staff.
Optionally, the dispatch module 306 is specifically configured to: sequencing the plurality of candidate travel service personnel according to the dispatch crowdedness degree to obtain a candidate travel service personnel sequence; matching target travel service personnel from the candidate travel service personnel sequence according to the target order type; and generating a visual form according to the order information of the target old visitor, and dispatching the order information of the target old visitor to the target travel service staff according to the visual form.
Optionally, the travel service information pushing device based on artificial intelligence further includes:
the evaluation module 307 is used for acquiring the image data uploaded by the target travel service personnel; performing service evaluation on the target travel service personnel according to the image data to obtain a first service evaluation index; obtaining phone call return visit data of the target old visitor, and performing service evaluation analysis on the phone call return visit data to obtain a second service evaluation index; judging whether the first service evaluation index and the second service evaluation index are consistent or not to obtain a judgment result; and generating comprehensive service evaluation corresponding to the target travel service personnel according to the judgment result.
According to the embodiment of the invention, the order data of a plurality of tourism service personnel are analyzed to obtain the tourism service type which is good for each tourism service personnel, so that the matching degree of the tourism service personnel and the target old visitor is improved, the online voice data of the target old visitor is subjected to accent analysis and text conversion, the tourism service requirement of the target old visitor is generated, the online voice data is subjected to accent analysis, the recognition accuracy of the online voice data is improved, the tourism service requirement analysis accuracy of the target old visitor is improved, the dispatch list type is analyzed, the matching degree of the picture of the tourism service personnel and the target old visitor is higher, the dispatch list congestion degree is calculated, the dispatch list is sent according to the calculation result, and the tourism service information pushing and dispatch accuracy are improved.
FIGS. 3 and 4 above describe the artificial intelligence based travel service information push system in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the artificial intelligence based travel service information push device in the embodiment of the present invention is described in detail from the perspective of the hardware processing.
FIG. 5 is a block diagram of an embodiment of an artificial intelligence based travel service information push device 500 that may vary significantly depending on configuration or performance, and that may include one or more processors (CPUs) 510 (e.g., one or more processors) and memory 520, one or more storage media 530 (e.g., one or more mass storage devices) storing applications 533 or data 532. Memory 520 and storage media 530 may be, among other things, transient or persistent storage. The program stored on the storage medium 530 may include one or more modules (not shown), each of which may include a sequence of instructions for operating the artificial intelligence based travel service information push device 500. Still further, the processor 510 may be configured to communicate with the storage medium 530 to execute a series of instructional operations on the storage medium 530 on the artificial intelligence based travel service information push device 500.
The artificial intelligence based travel service information push device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input-output interfaces 560, and/or one or more operating systems 531, such as Windows Server, mac OS X, unix, linux, freeBSD, and the like. Those skilled in the art will appreciate that the configuration of the artificial intelligence based travel service information push device illustrated in FIG. 5 does not constitute a limitation on the artificial intelligence based travel service information push device and may include more or less components than those illustrated, or some components may be combined, or a different arrangement of components.
The invention also provides artificial intelligence based travel service information pushing equipment which comprises a memory and a processor, wherein computer readable instructions are stored in the memory, and when the computer readable instructions are executed by the processor, the processor executes the steps of the artificial intelligence based travel service information pushing method in each embodiment.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium or a volatile computer readable storage medium, having stored therein instructions, which, when executed on a computer, cause the computer to perform the steps of the artificial intelligence based travel service information push method.
Further, the computer-readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is substantially or partly contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A travel service information pushing method based on artificial intelligence is characterized by comprising the following steps:
acquiring order data of a plurality of travel service personnel from a preset travel service order database, and carrying out order classification and personnel configuration on the order data to obtain a historical service order of each travel service personnel;
performing order feature extraction on the historical service order of each travel service person to obtain the historical order feature of each travel service person, performing cluster analysis on the historical order feature of each travel service person to generate a representation of the travel service person of each travel service person, wherein the representation of the travel service person is used for indicating the type of travel service which the travel service person excels in;
the method comprises the steps of obtaining online voice data of a target old visitor, carrying out accent feature recognition and voice text conversion on the online voice data to obtain a target voice text, carrying out user demand detection on the target voice text to obtain a tourism service demand of the target old visitor, wherein the tourism service demand comprises the following steps: medical service requirements, catering service requirements and tour guide service requirements;
generating order information of the target old visitor according to the travel service demand, dividing the order information into order types to obtain a target order type corresponding to the order information, and matching the pictures of the travel service staff according to the travel service demand to obtain a plurality of candidate travel service staff related to the target old visitor;
obtaining the current order receiving quantity of each candidate tourism service personnel, and calculating the order sending crowdedness degree of the candidate tourism service personnel according to the current order receiving quantity of each candidate tourism service personnel to obtain the order sending crowdedness degree;
and selecting target travel service personnel from the candidate travel service personnel according to the dispatch crowdedness and the target dispatch type, and dispatching the order information of the target old tourist to the target travel service personnel.
2. The artificial intelligence based travel service information push method as recited in claim 1, wherein the step of performing order feature extraction on the historical service orders of each travel service person to obtain the historical order features of each travel service person, and performing cluster analysis on the historical order features of each travel service person to generate the travel service person representation of each travel service person, wherein the travel service person representation is used for indicating the types of travel services that the travel service person excels at, comprises the steps of:
extracting a plurality of service types of historical service orders of each travel service worker and service frequency corresponding to each service type;
generating historical order characteristics of each travel service personnel according to the plurality of service types and the service frequency corresponding to each service type;
the historical order characteristics for each travel service representative are clustered to generate a travel service representative profile for each travel service representative, wherein the travel service representative profiles are indicative of the types of travel services that the travel service representative is good at.
3. The artificial intelligence based travel service information pushing method according to claim 1, wherein the obtaining of the online voice data of the target elderly visitor, the performing of accent feature recognition and voice text conversion on the online voice data to obtain a target voice text, and the performing of user demand detection on the target voice text to obtain a travel service demand of the target elderly visitor are performed, and the travel service demand includes: medical service needs, food and beverage service needs and tour guide service needs, include:
receiving a travel service request sent by a target old visitor, and acquiring online voice data of the target old visitor according to the travel service request;
carrying out accent feature recognition on the online voice data to obtain accent categories and acoustic features corresponding to the online voice data;
performing voice text conversion on the online voice data according to the accent type and the acoustic characteristics to obtain a target voice text;
and detecting user requirements of the target voice text to obtain the tourism service requirements of the target old visitor, wherein the tourism service requirements comprise: medical service needs, catering service needs and tour guide service needs.
4. The artificial intelligence based travel service information pushing method according to claim 1, wherein the generating of order information of the target elderly visitor according to the travel service requirement, the dividing of the order type of the order information, the obtaining of the target order type corresponding to the order information, and the matching of the travel service person figures according to the travel service requirement, the obtaining of a plurality of candidate travel service persons related to the target elderly visitor comprise:
generating an order interface according to the tourism service requirement, and generating order information of the target old visitor according to the order interface;
performing dispatch type division on the order information according to a preset dispatch index to obtain a target dispatch type corresponding to the order information, wherein the target dispatch type comprises: urgent, urgent and normal;
and calculating a correlation coefficient between the travel service demand and the travel service person representation, and taking the travel service person representation with the correlation coefficient larger than a preset target value as a plurality of candidate travel service persons related to the target old tourist.
5. The artificial intelligence based travel service information pushing method as claimed in claim 1, wherein the obtaining of the current pick-up volume of each candidate travel service person and the calculation of the dispatch congestion degree of the candidate travel service persons according to the current pick-up volume of each candidate travel service person to obtain the dispatch congestion degree comprises:
acquiring the current bill receiving quantity of each candidate tourist service staff;
calculating the congestion degree of the current service node of each candidate travel service staff according to the current order receiving quantity of each candidate travel service staff;
and generating the dispatch congestion degree according to the congestion degree of the current service node of each candidate travel service staff.
6. The artificial intelligence based travel service information pushing method as claimed in claim 1, wherein the step of selecting a target travel service person from the plurality of candidate travel service persons according to the dispatch crowdedness and the target dispatch type and dispatching the order information of the target elderly tourist to the target travel service person comprises the steps of:
sequencing the plurality of candidate travel service personnel according to the dispatch crowdedness degree to obtain a candidate travel service personnel sequence;
matching target travel service personnel from the sequence of candidate travel service personnel according to the type of the target order;
and generating a visual form according to the order information of the target old visitor, and dispatching the order information of the target old visitor to the target travel service staff according to the visual form.
7. The artificial intelligence based travel service information push method according to any one of claims 1-6, wherein the artificial intelligence based travel service information push method further comprises:
acquiring image data uploaded by the target travel service personnel;
performing service evaluation on the target travel service personnel according to the image data to obtain a first service evaluation index;
obtaining phone call return visit data of the target old visitor, and performing service evaluation analysis on the phone call return visit data to obtain a second service evaluation index;
judging whether the first service evaluation index and the second service evaluation index are consistent or not to obtain a judgment result;
and generating comprehensive service evaluation corresponding to the target travel service personnel according to the judgment result.
8. The utility model provides a tourism service information push system based on artificial intelligence which characterized in that, said tourism service information push system based on artificial intelligence includes:
the acquisition module is used for acquiring order data of a plurality of travel service personnel from a preset travel service order database, and carrying out order classification and personnel configuration on the order data to obtain a historical service order of each travel service personnel;
the extraction module is used for carrying out order feature extraction on the historical service order of each travel service person to obtain the historical order feature of each travel service person, carrying out cluster analysis on the historical order feature of each travel service person to generate a travel service person representation of each travel service person, wherein the travel service person representation is used for indicating the type of travel service which the travel service person is good at;
the detection module is used for acquiring online voice data of the target old tourist, performing accent feature recognition and voice text conversion on the online voice data to obtain a target voice text, performing user demand detection on the target voice text to obtain the travel service demand of the target old tourist, wherein the travel service demand comprises: medical service requirements, catering service requirements and tour guide service requirements;
the matching module is used for generating order information of the target old visitor according to the travel service demand, dividing the order information into order types to obtain a target order type corresponding to the order information, and matching the tourist service personnel figures according to the travel service demand to obtain a plurality of candidate tourist service personnel related to the target old visitor;
the calculating module is used for acquiring the current order receiving quantity of each candidate travel service worker and calculating the order sending crowdedness degree of the candidate travel service workers according to the current order receiving quantity of each candidate travel service worker to obtain the order sending crowdedness degree;
and the order dispatching module is used for selecting target travel service personnel from the candidate travel service personnel according to the order dispatching crowdedness and the target order dispatching type and dispatching the order information of the target old tourist to the target travel service personnel.
9. The utility model provides a tourism service information push equipment based on artificial intelligence which characterized in that, said tourism service information push equipment based on artificial intelligence includes: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invokes the instructions in the memory to cause the artificial intelligence based travel service information push device to perform the artificial intelligence based travel service information push method of any one of claims 1-7.
10. A computer-readable storage medium having instructions stored thereon, wherein the instructions, when executed by a processor, implement the artificial intelligence based travel service information push method according to any one of claims 1-7.
CN202310134950.2A 2023-02-20 2023-02-20 Travel service information pushing method and system based on artificial intelligence Pending CN115935076A (en)

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Application publication date: 20230407