CN113570293A - Offline activity information intelligent management system based on online social information analysis - Google Patents
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Abstract
The invention belongs to the technical field of offline social activity management, and particularly discloses an offline activity information intelligent management system based on online social information analysis, which comprises an online tourism social record extraction module, an offline collective tourism target parameter analysis module, an offline collective tourism social subject determination module, a social subject tourism social record classification module and a social subject offline collective tourism preparation activity management module, wherein the offline collective tourism preparation activity management is realized by extracting tourism social records from an online tourism social group and classifying the social record sets corresponding to the social subjects so as to perform offline collective tourism preparation activity management on the social subjects according to the social record sets corresponding to the social subjects, and the online tourism preparation activity management mainly takes the online tourism social records as management basis in the process of the online tourism preparation activity management, the management fitting degree of the offline integrated tourism preparation activities is greatly improved, and the probability of improper management is reduced to a certain extent.
Description
Technical Field
The invention belongs to the technical field of offline social activity management, and particularly relates to an offline activity information intelligent management system based on online social information analysis.
Background
With the continuous development of computer technology, social networks are gradually merged into the daily life of people, more and more users of online social network sites are available, and people can establish social groups for communication by the online social network sites according to common interests; however, for some social groups, the simple online social contact cannot meet the requirements of social agents in the groups, such as a travel social group, as is well known, travel is an item needing to be experienced on the spot, and the social contact experience is reduced only by online social contact of information in the aspect of travel, so that many travel social groups organize collective travel activities on the spot to realize offline travel social contact, and the feelings of members in the groups are enhanced; in such a case, the management of the organization's offline collective travel activities by the activity organizer is required.
However, most of the current management on the offline integrated tourism activities are only in the aspect of tourism process, such as the planning of important scenic area tourism sequence and route in tourist attractions, and the management on the aspect of tourism preparation activities, such as the management of tourism travel traffic and tourism accommodation and hotels, is neglected. If the travel preparation activities are not managed properly, some travel members can not arrive at the tourist attractions in time or can not smoothly live in a residence, and under the condition, the management on the travel process cannot be correspondingly performed, so that the experience of collective travel is reduced. Therefore, the management of the travel preparation activities is the premise of the whole collective travel activity, and the smooth travel process can be ensured only if the travel preparation activities are properly managed, so that the management of the travel preparation activities of the lower collective travel activity is very necessary.
Disclosure of Invention
In order to achieve the above object, the present invention provides an offline activity information intelligent management system based on online social information analysis, which takes an online tourism social group as a management starting point, and performs targeted management of offline collective tourism preparation activities by collecting and analyzing the tourism social record information in the online tourism social group.
The invention provides the following technical scheme: an offline activity information intelligent management system based on online social information analysis comprises an online tourism social record extraction module, an offline collective tourism target parameter analysis module, an offline collective tourism social subject determination module, a social subject tourism social record classification module and a social subject offline collective tourism preparation activity management module.
The online travel social record extraction module is used for extracting travel social records from an online travel social group.
And the offline collective tourism target parameter analysis module is used for performing semantic analysis on the extracted tourism social records to obtain target parameters corresponding to the offline collective tourism.
The offline collective travel social body determining module is used for intercepting the social body head portrait corresponding to each travel social record from the extracted travel social records, further performing duplicate removal and identification on all the social body head portraits corresponding to the travel social records, and determining each social body corresponding to the offline collective travel.
And the social contact subject tourism social contact record classification module collects and classifies the social contact records corresponding to the same social contact subject in the tourism social contact record content according to the social contact subjects corresponding to the offline collective tourism to obtain a social contact record collection corresponding to each social contact subject.
And the social agent offline collective tourism preparation activity management module is used for performing offline collective tourism preparation activity management on each social agent according to the social record set corresponding to each social agent.
The social agent offline collective tourism preparation activity management module comprises an offline collective tourism travel traffic management terminal and an offline collective tourism accommodation management terminal.
The offline integrated tourism travel traffic management terminal comprises a social main body habit tourism travel characteristic acquisition module, a social main body local location identification module and an optimal travel train number screening module.
The offline integrated travel accommodation management terminal comprises a social agent habit travel accommodation feature acquisition module and a preferred accommodation hotel screening module.
The invention has the following beneficial effects: 1. the invention extracts the travel social records from the online travel social group, and performs target parameter analysis and social body determination of the offline collective travel on the extracted travel social records, meanwhile, according to the social contact subjects corresponding to the offline collective tourism, the social contact records corresponding to the same social contact subject in the tourism social contact record content are collected and classified to obtain a social contact record collection corresponding to each social contact subject, further, the preparation activity management of the offline collective tourism is carried out on each social agent according to the social record set corresponding to each social agent, and the preparation activity management mainly takes online travel social records as the management basis in the process of proceeding, thereby greatly improving the management fitness of the offline integrated travel preparation activity, therefore, the probability of improper management is reduced to a certain extent, and the preparation activity experience feeling of the offline collective tourism corresponding to each social main body is enhanced.
2. According to the invention, the preferred lodging hotels corresponding to the offline collective tourism and the preferred travel vehicle times of each social body are screened by collecting the habitual travel characteristic and the habitual travel lodging characteristic corresponding to each social body according to the social record set corresponding to each social body in the offline collective tourism preparation activity management process, wherein the screening indexes of the preferred lodging hotels and the preferred travel vehicle times both cover the multi-dimensional characteristic, so that the screening process is more comprehensive, the sidedness of the screening result caused by the too single screening index is avoided, and the accuracy of the screening result is improved.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a schematic diagram of a system module structure according to the present invention.
FIG. 2 is a block diagram of the social agent offline corporate travel preparation activity management module according to the present invention.
Fig. 3 is a schematic structural view of the offline collective travel traffic management terminal of the present invention.
Fig. 4 is a schematic structural view of the offline integrated travel accommodation management terminal of the present invention.
In the figure: 1. an online travel social record extraction module; 2. an offline collective tourism target parameter analysis module; 3. an offline collective tourism social contact subject determination module; 4. a social agent tourism social record classification module; 5. a social agent offline collective travel preparation activity management module; 51. an offline integrated travel traffic management terminal; 52. an offline integrated tourism accommodation management terminal; 53. the offline collective tourism preparation activity management result feedback terminal; 511. a social agent habit travel characteristic acquisition module; 512. a social agent local location identification module; 513. preferably selecting a trip train number screening module; 521. a social agent habit tourism accommodation characteristic acquisition module; 522. and preferably selecting the lodging and hotel screening module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments; all other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an offline activity information intelligent management system based on online social information analysis includes an online tourism social record extraction module 1, an offline collective tourism target parameter analysis module 2, an offline collective tourism social subject determination module 3, a social subject tourism social record classification module 4, and a social subject offline collective tourism preparation activity management module 5.
The online tourism social record extraction module 1 is connected with the offline collective tourism target parameter analysis module 2 and the offline collective tourism social body determination module 3 respectively, the offline collective tourism social body determination module 3 is connected with the social body tourism social record classification module 4, and the social body tourism social record classification module 4 and the offline collective tourism target parameter analysis module 2 are connected with the social body offline collective tourism preparation activity management module 5.
The online travel social record extracting module 1 is used for extracting travel social records from an online travel social group.
The offline collective tourism target parameter analysis module 2 is used for performing semantic analysis on the extracted tourism social records to obtain target parameters corresponding to the offline collective tourism, wherein the target parameters comprise tourist attraction names and departure dates, and the specific analysis method of the semantic analysis is as follows: the method comprises the following steps: and acquiring the retrieval associated words corresponding to the target parameters, wherein the retrieval associated words corresponding to the names of the scenic spots comprise scenic spots, scenic spots and the like, and the retrieval associated words corresponding to the departure dates comprise the moving time, the departure dates and the like.
Step two: and performing semantic retrieval by inputting retrieval associated words corresponding to all target parameters in the travel social records to obtain target parameters corresponding to the offline collective travel.
The offline collective travel social body determining module 3 is configured to intercept, from the extracted travel social records, social body icons corresponding to each travel social record, perform deduplication identification on all social body icons corresponding to the travel social records, and determine each social body corresponding to the offline collective travel.
The purpose of determining that the offline collective tourism corresponds to each social subject in the embodiment of the invention is to provide convenience for classifying the tourism social records.
And the social contact subject travel social contact record classifying module 4 summarizes and classifies the social contact records corresponding to the same social contact subject in the travel social contact record content according to the social contact subjects corresponding to the offline collective travel to obtain the social contact record sets corresponding to the social contact subjects.
Referring to fig. 2, the social agent offline collective travel preparation activity management module 5 is configured to perform offline collective travel preparation activity management on each social agent according to the social record set corresponding to each social agent, where the social agent offline collective travel preparation activity management module 5 includes an offline collective travel transportation management terminal 51, an offline collective travel accommodation management terminal 52, and an offline collective travel preparation activity management result feedback terminal 53.
Referring to fig. 3, the offline integrated travel traffic management terminal 51 includes a social agent habit travel characteristic collection module 511, a social agent local location identification module 512, and a preferred travel train number screening module 513.
The social agent habit travel characteristic collecting module 511 is configured to collect habit travel characteristics from a social record set corresponding to each social agent, and the specific collecting method is to extract habit travel vehicles, habit travel time points, permitted travel upper limit duration and permitted travel upper limit fare keywords from all social records in the social record set corresponding to each social agent, so as to obtain the habit travel characteristics corresponding to each social agent, where the habit travel characteristics include the habit travel vehicles, the habit travel time points, the permitted travel upper limit duration and the permitted travel upper limit fare.
The customary travel vehicles mentioned in the present embodiment include trains, cars, planes, and the like.
The social agent local location identification module 512 is configured to identify a local location corresponding to each social agent, and the specific identification method includes: and obtaining IP addresses displayed by the publishing terminal when the social contact subjects publish the social records in the online tourism social group.
And identifying the local place corresponding to each social contact agent according to the IP address displayed by the corresponding publishing terminal of each social contact agent.
The preferred travel train number screening module 513 is configured to perform screening of the preferred travel train number of the offline collective tour on each social subject by combining the habitual tour travel characteristics corresponding to each social subject, the local location and the target parameters corresponding to the offline collective tour, and the specific screening process executes the following steps: the first step is to number the social agents, labeled 1,2, a.
And secondly, extracting the habit travel vehicles from the habit travel characteristics corresponding to each social agent, and further linking the habit travel vehicles to an online ticket buying platform of the corresponding habit travel vehicles.
And thirdly, taking the local place corresponding to each social agent as a travel starting point.
And fourthly, extracting the names and the departure dates of the tourist attractions from the target parameters corresponding to the off-line collective tourism, taking the locations of the names of the tourist attractions as travel end points, and taking the departure dates as travel dates.
And fifthly, inputting a travel date, a travel starting point and a travel ending point in an online ticket buying platform which is linked to the corresponding habit travel vehicle to inquire the train number, and obtaining all travel train number inquiry results of the collective travel corresponding to each social contact subject under the train number.
And sixthly, primarily screening all the travel vehicle numbers corresponding to the social main bodies of the offline collective tourism to obtain alternative travel vehicle numbers corresponding to the screened social main bodies, wherein the primary screening method comprises the steps of obtaining the current remaining ticket number corresponding to each travel vehicle number, and then rejecting the travel vehicle number with the current remaining ticket number being zero, so that the travel vehicle number reserved by each social main body is marked as the alternative travel vehicle number, and the alternative travel vehicle numbers corresponding to each social main body are numbered according to the sequence of departure time points, and are sequentially marked as 1,2,.
Seventhly, respectively acquiring departure time points, distance durations and the highest fare of vacant seats of the alternative trip vehicle numbers corresponding to the social main bodies from the trip vehicle number query results, and forming a social main body alternative trip vehicle number departure parameter set
，
The departure parameters of the ith social subject corresponding to the jth alternative trip train number are represented, w is represented as the departure parameters, and w = r1, r2 and r3 are respectively represented as the departure time point, the journey duration and the highest fare of the vacant seat.
And eighth step, extracting an habit travel time point, an allowable travel upper limit duration and an allowable travel upper limit fare from habit travel characteristics corresponding to each social subject of the collective travel under the time line, and dispatching the habit travel time point, the allowable travel upper limit duration and the allowable travel upper limit fare with alternative travel train numbers of the social subjectsParameter set
Comparing, and calculating the matching value coefficient of each alternative travel train number corresponding to each social subject by using a preset travel train number matching value calculation formula
，
The matching value coefficient of the ith social subject corresponding to the jth alternative trip train number is expressed,
、
、
the train departure time point of a certain alternative trip train number is closer to the habitual trip time point of the social main body, the journey duration is shorter, the highest fare of the vacant seat is lower, the matching value coefficient is larger, and the matching value is higher.
And ninthly, screening the alternative travel train number with the maximum matching value coefficient from the matching value coefficients of the alternative travel train numbers corresponding to the social subjects to serve as the preferred travel train number of each social subject.
Referring to fig. 4, the offline collective travel accommodation management terminal 52 includes a social subject habit travel accommodation feature acquisition module 521 and a preferred accommodation hotel screening module 522.
The social agent habit travel accommodation feature acquisition module 521 is configured to acquire habit travel accommodation features from the social record set corresponding to each social agent, and the specific acquisition method is to extract the habit accommodation room bed size and the allowable accommodation room upper unit price keyword from all social records in the social record set corresponding to each social agent, so as to obtain the habit travel accommodation features corresponding to each social agent, where the habit travel accommodation features include the habit accommodation room bed size and the allowable accommodation room upper unit price.
The preferred lodging hotel screening module 522 is used for screening preferred lodging hotels traveling at tourist attractions locations in the offline integrated manner, and the specific screening process is as follows: step 1: and according to the names of the tourist attractions of the offline collective tourism, linking to the online hotel reservation platform, and further inputting the names of the tourist attractions on the online hotel reservation platform to obtain all adjacent hotels corresponding to the tourist attractions.
Step 2: and respectively acquiring accommodation matching indexes corresponding to adjacent hotels from an online hotel reservation platform, wherein the accommodation matching indexes comprise route distances from locations of tourist attractions, the number of vacant accommodation rooms on the day of departure date, and the bed size and the room unit price corresponding to each vacant accommodation room.
And step 3: the method comprises the steps of conducting preliminary analysis on accommodation matching indexes corresponding to adjacent hotels to reserve a plurality of candidate adjacent hotels, wherein the specific analysis process comprises the steps of extracting the number of vacant accommodation rooms on the day of departure date from the accommodation matching indexes corresponding to the adjacent hotels, comparing the number of vacant accommodation rooms with the number of social entities corresponding to travel of the offline collective body, if the number of vacant accommodation rooms on the day of departure date corresponding to a certain adjacent hotel is larger than or equal to the number of social entities corresponding to travel of the offline collective body, reserving the adjacent hotel, and recording the reserved adjacent hotel as the candidate adjacent hotel.
And 4, step 4: and numbering the candidate adjacent hotels according to the sequence of the route distances from the tourist attractions to the positions of the candidate adjacent hotels from near to far, wherein the candidate adjacent hotels are marked as 1, 2.
Step 5, extracting the bed size of the habitual lodging room and the upper unit price of the room allowed to lodge from the habitual travel lodging characteristics corresponding to each social subject, comparing the bed sizes of the habitual lodging rooms corresponding to each social subject, classifying the social subjects corresponding to the bed sizes of the habitual lodging rooms, and countingThe number of the bed sizes of the lodging rooms with the same habits and the number of the social bodies corresponding to the bed sizes of the lodging rooms with the same habits are taken as the number of the required bed size categories, the number of the social bodies corresponding to the bed sizes of the lodging rooms with the same habits is taken as the number of the required rooms corresponding to the bed sizes, the number of the required bed size categories is taken as X, the number of the required bed size categories and the number of the required rooms corresponding to the required bed sizes are taken as the required bed matching parameters of the lodging hotels corresponding to the offline collective tourism, the upper limit unit prices of the lodging rooms corresponding to the social bodies are compared with each other, the upper limit unit price of the lodging room with the highest upper limit unit price is selected as the unit price of the lodging rooms corresponding to the offline collective tourism, is marked as
。
Step 6, comparing the bed sizes of the vacant rooms corresponding to the candidate adjacent hotels, classifying the space rooms corresponding to the same bed size to obtain the bed size types and the number of the vacant rooms corresponding to the bed sizes of the candidate adjacent hotels, comparing the lodging unit prices of the vacant rooms corresponding to the candidate adjacent hotels, selecting the highest lodging unit price as the highest lodging unit price of the candidate adjacent hotels, and recording the highest lodging unit price as the highest lodging unit price of the candidate adjacent hotels
。
Step 7, matching the bed size types corresponding to the candidate adjacent hotels and the number of vacant rooms corresponding to various bed sizes with the required bed matching parameters of the accommodation hotels corresponding to the offline collective tourism, counting the number of the bed size types corresponding to the candidate adjacent hotels and recording the number as the successfully matched bed size types
Simultaneously counting the successfully matched beds in the candidate adjacent hotelsThe number of the vacant rooms successfully matched in the position size type is recorded as the number of the vacant rooms successfully matched in the position size type, the sizes of the various beds successfully matched in the candidate adjacent hotels are numbered as 1,2, the
And calculating the bed matching degree of the accommodation room corresponding to each candidate adjacent hotel
，
Expressed as the degree of matching of the accommodation room beds corresponding to the kth candidate neighboring hotel,
the number of bed size categories corresponding to the matching success of the kth candidate neighboring hotel is expressed,
expressed as the required bed size, variety and quantity of the accommodation hotel corresponding to the offline collective travel,
the d-th bed size indicated as the k-th candidate neighboring hotel corresponding to the successful matching corresponds to the number of vacant rooms successfully matched,
the number of required rooms corresponding to the d-th bed size of the accommodation hotel corresponding to the offline collective tourism is represented, wherein the number of the successfully matched bed sizes and the number of the successfully matched vacant rooms corresponding to the successfully matched bed sizes are increased, and the bed matching degree of the accommodation rooms is increased.
Step 8, the highest accommodation unit price of each candidate adjacent hotel and the demand of the accommodation hotel corresponding to the offline collective travelMatching the unit prices of the accommodation rooms, calculating the unit price matching degree of the accommodation rooms corresponding to the candidate adjacent hotels, and recording as
，
Expressed as the unit price matching degree of the accommodation room corresponding to the kth candidate adjacent hotel,
expressed as the highest accommodation unit price corresponding to the kth candidate neighboring hotel,
and the required accommodation room unit price of the accommodation hotel corresponding to the offline collective travel is expressed, wherein the smaller the highest accommodation unit price of a candidate adjacent hotel is, the larger the accommodation room unit price matching degree of the candidate adjacent hotel is.
Step 9, recording the route distance of each candidate adjacent hotel from the tourist attraction location
Thereby will be
、
And
the comprehensive accommodation matching degree corresponding to each candidate adjacent hotel is obtained by substituting the set accommodation hotel comprehensive matching degree calculation formula for statistics
，
Expressed as the kth candidateThe comprehensive accommodation matching degree corresponding to the adjacent hotel,
、
、
respectively expressed as matching weight values corresponding to the bed position, unit price and route distance of the accommodation room, and
、
、
the value of the method can be 0.4, 0.4 or 0.2, and the candidate adjacent hotel corresponding to the maximum comprehensive accommodation matching degree is screened out from the candidate adjacent hotel as the preferred accommodation hotel for the offline collective tourism in the tourist attraction.
According to the embodiment of the invention, the preferred lodging hotels corresponding to the offline collective tourism and the preferred travel vehicle times of each social body are screened by collecting the habitual travel characteristic and the habitual travel lodging characteristic corresponding to each social body in the offline collective tourism preparation activity management process of each social body according to the social record set corresponding to each social body, wherein the screening indexes of the preferred lodging hotels and the preferred travel vehicle times both include the multi-dimensional characteristic, so that the screening process is more comprehensive, the one-sidedness of the screening result caused by the fact that the screening index is too single is avoided, and the accuracy of the screening result is improved.
The offline collective travel preparation activity management result feedback terminal 53 is used for feeding back preferred lodging hotels corresponding to the offline collective travel and preferred travel car numbers of the social subjects to the online travel social group, so that the social subjects in the group can be intuitively and timely known.
The embodiment of the invention extracts the travel social records from the online travel social group, and performs target parameter analysis and social body determination of offline collective travel on the extracted travel social records, meanwhile, according to the social contact subjects corresponding to the offline collective tourism, the social contact records corresponding to the same social contact subject in the tourism social contact record content are collected and classified to obtain a social contact record collection corresponding to each social contact subject, further, the preparation activity management of the offline collective tourism is carried out on each social agent according to the social record set corresponding to each social agent, and the preparation activity management mainly takes online travel social records as the management basis in the process of proceeding, thereby greatly improving the management fitness of the offline integrated travel preparation activity, therefore, the probability of improper management is reduced to a certain extent, and the preparation activity experience feeling of the offline collective tourism corresponding to each social main body is enhanced.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (10)
1. The utility model provides an offline activity information intelligent management system based on online social information analysis which characterized in that: the online tourism social record management system comprises an online tourism social record extraction module, an offline collective tourism target parameter analysis module, an offline collective tourism social body determination module, a social body tourism social record classification module and a social body offline collective tourism preparation activity management module;
the online travel social record extraction module is used for extracting travel social records from an online travel social group;
the online collection tourism target parameter analysis module is used for performing semantic analysis on the extracted tourism social records to obtain target parameters corresponding to the online collection tourism;
the offline collective travel social body determining module is used for intercepting the social body head portrait corresponding to each travel social record from the extracted travel social records, further performing duplicate removal and identification on all the social body head portraits corresponding to the travel social records, and determining each social body corresponding to the offline collective travel;
the social contact subject tourism social contact record classification module collects and classifies social contact records corresponding to the same social contact subject in the tourism social contact record content according to the social contact subjects corresponding to the offline collection tourism to obtain a social contact record collection corresponding to each social contact subject;
the social agent offline collective tourism preparation activity management module is used for performing offline collective tourism preparation activity management on each social agent according to the social record set corresponding to each social agent;
the social agent offline collective tourism preparation activity management module comprises an offline collective tourism travel traffic management terminal and an offline collective tourism accommodation management terminal;
the offline integrated tourism travel traffic management terminal comprises a social main body habit tourism travel characteristic acquisition module, a social main body local location identification module and an optimal travel train number screening module;
the offline integrated travel accommodation management terminal comprises a social agent habit travel accommodation feature acquisition module and a preferred accommodation hotel screening module.
2. The system of claim 1 for intelligent management of offline activity information based on online social information analysis, wherein: the specific analysis method of the semantic analysis is as follows:
the method comprises the following steps: acquiring a retrieval associated word corresponding to each target parameter;
step two: and performing semantic retrieval by inputting retrieval associated words corresponding to all target parameters in the travel social records to obtain target parameters corresponding to the offline collective travel.
3. The system of claim 1 for intelligent management of offline activity information based on online social information analysis, wherein: the target parameters include tourist attraction names and departure dates.
4. The system of claim 1 for intelligent management of offline activity information based on online social information analysis, wherein: the social main body habit travel characteristic acquisition module is used for acquiring habit travel characteristics from a social record set corresponding to each social main body, wherein the habit travel characteristics comprise habit travel vehicles, habit travel time points, allowable travel upper limit duration and allowable travel upper limit fare.
5. The system of claim 1 for intelligent management of offline activity information based on online social information analysis, wherein: the social agent local location identification module is used for identifying local locations corresponding to the social agents, and the specific identification method comprises the following steps:
the method comprises the steps that IP addresses displayed by a publishing terminal when each social contact main body publishes social records in an online tourism social group are obtained;
and identifying the local place corresponding to each social contact agent according to the IP address displayed by the corresponding publishing terminal of each social contact agent.
6. The system of claim 1 for intelligent management of offline activity information based on online social information analysis, wherein: the preferred travel train number screening module is used for screening preferred travel train numbers of offline collective travel for the social main bodies by combining the habitual travel characteristics corresponding to the social main bodies, the local places and the target parameters corresponding to the offline collective travel, and the specific screening process executes the following steps:
the method comprises the steps of firstly, numbering social agents, wherein the social agents are marked as 1,2, a.
Secondly, extracting the habit travel vehicles from the habit travel characteristics corresponding to each social agent, and further linking the habit travel vehicles to an online ticket buying platform of the corresponding habit travel vehicles;
taking the local place corresponding to each social agent as a trip starting point;
fourthly, extracting the names and the departure dates of the tourist attractions from the target parameters corresponding to the off-line collective tourism, taking the locations of the names of the tourist attractions as travel end points and the departure dates as travel dates;
fifthly, inputting travel date, a travel starting point and a travel ending point in an online ticket buying platform which is linked to a corresponding habit travel vehicle to inquire the number of vehicles, and obtaining all travel number inquiry results of the collective travel corresponding to each social contact subject under the travel of the corresponding time;
sixthly, preliminarily screening all the travel vehicle numbers corresponding to the social main bodies of the offline collective tourism to obtain alternative travel vehicle numbers corresponding to the screened social main bodies, numbering the alternative travel vehicle numbers corresponding to the social main bodies according to the sequence of departure time points, and sequentially marking the alternative travel vehicle numbers as 1,2,. once.j,. once.m;
seventhly, respectively obtaining departure time points, distance duration and the maximum fare of the vacant seats of the alternative trip vehicle numbers corresponding to the social subjects, and forming a candidate trip vehicle number departure parameter set of the social subjects
，
The departure parameter is expressed as the departure parameter of the ith social principal corresponding to the jth alternative trip train number, w is expressed as the departure parameter, and w = r1, r2 and r3 are respectively expressed as the departure time point, the distance duration and the highest fare of the vacant seats;
the eighth step of extracting the habit travel time point, the allowable travel upper limit duration and the allowable travel upper limit fare from the habit travel characteristics corresponding to each social main body of the collective travel under the time line, and comparing the habit travel time point, the allowable travel upper limit duration and the allowable travel upper limit fare with the habit travel characteristics
Comparing, and calculating the matching value coefficient of each alternative travel train number corresponding to each social subject by using a preset travel train number matching value calculation formula
，
The matching value coefficient of the ith social subject corresponding to the jth alternative trip train number is expressed,
、
、
respectively representing a habitual travel time point, an upper limit duration of a permitted travel distance and an upper limit fare of the permitted travel distance corresponding to the ith social contact subject;
and ninthly, screening the alternative travel train number with the maximum matching value coefficient from the matching value coefficients of the alternative travel train numbers corresponding to the social subjects to serve as the preferred travel train number of each social subject.
7. The system of claim 1 for intelligent management of offline activity information based on online social information analysis, wherein: the social agent habit travel and accommodation feature acquisition module is used for acquiring habit travel and accommodation features from a social record set corresponding to each social agent, wherein the habit travel and accommodation features comprise habit room bed size and allowable accommodation room upper limit unit price.
8. The system of claim 1 for intelligent management of offline activity information based on online social information analysis, wherein: the preferred lodging hotel screening module is used for screening preferred lodging hotels traveling at tourist attractions of the offline integrated tourism site, and the specific screening process is as follows:
step 1: according to the names of tourist attractions of the off-line collective tourism, the on-line hotel reservation platform is linked, and then the names of the tourist attractions are input on the on-line hotel reservation platform to obtain all adjacent hotels corresponding to the tourist attractions;
step 2: respectively collecting accommodation matching indexes corresponding to adjacent hotels from an online hotel reservation platform, and carrying out preliminary analysis on the accommodation matching indexes corresponding to the adjacent hotels so as to reserve a plurality of candidate adjacent hotels;
and step 3: numbering each candidate adjacent hotel according to the sequence of the route distance from the tourist attraction location from near to far, and respectively marking the candidate adjacent hotels as 1,2,. once, k,. once, z;
step 4, comprehensively analyzing the habit travel accommodation characteristics corresponding to each social subject to obtain the required bed position matching parameters and the required accommodation room unit price of the accommodation hotel corresponding to the offline collective travel;
step 5, matching the accommodation matching indexes corresponding to the candidate adjacent hotels with the required bed matching parameters and the required accommodation room unit prices of accommodation hotels corresponding to the offline collective tourism respectively, calculating the accommodation room bed matching degrees and the accommodation room unit price matching degrees corresponding to the candidate adjacent hotels, and recording the accommodation room bed matching degrees as accommodation room bed matching degrees
The unit price matching degree of the accommodation room is recorded as
；
Step 6, recording the distance of the route of each candidate adjacent hotel from the tourist attraction location
Thereby will be
、
And
the comprehensive accommodation matching degree corresponding to each candidate adjacent hotel is obtained by substituting the set accommodation hotel comprehensive matching degree calculation formula for statistics
，
Expressed as the comprehensive accommodation matching degree corresponding to the kth candidate neighboring hotel,
、
、
and the matching weight values are respectively expressed as the matching weight values corresponding to the bed position of the accommodation room, the unit price of the accommodation room and the route distance, and the candidate adjacent hotel corresponding to the maximum comprehensive accommodation matching degree is screened out from the matching weight values and serves as the preferred accommodation hotel for the lower-line collective tourism at the tourist attraction.
9. The system of claim 8, wherein the offline activity information intelligent management system based on online social information analysis is characterized in that: the required bed matching parameters comprise the types and the number of the bed sizes and the number of rooms corresponding to various bed sizes.
10. The system of claim 1 for intelligent management of offline activity information based on online social information analysis, wherein: the social agent offline collective travel preparation activity management module further comprises an offline collective travel preparation activity management result feedback terminal, and the offline collective travel preparation activity management result feedback terminal is used for feeding back preferred accommodation hotels corresponding to the offline collective travel and preferred travel car numbers of the social agents to the online travel social group.
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