CN103020308A - Method and device for recommending travel strategy project - Google Patents
Method and device for recommending travel strategy project Download PDFInfo
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- CN103020308A CN103020308A CN2013100048754A CN201310004875A CN103020308A CN 103020308 A CN103020308 A CN 103020308A CN 2013100048754 A CN2013100048754 A CN 2013100048754A CN 201310004875 A CN201310004875 A CN 201310004875A CN 103020308 A CN103020308 A CN 103020308A
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Abstract
The invention discloses a method and a device for recommending a travel strategy project. The method comprises the following steps: obtaining a destination of travel itinerary planning of a recommended user and the type of travel strategy project needing to be recommended to the recommended user; in combination with the matching degree between each travel strategy project and personal data of the recommended user, obtaining a recommendation grade of each travel strategy project according to user evaluation data of each travel strategy project of the type of a pre-stored destination, relevant event information of each travel strategy project, the travel itinerary planning of each travel strategy project as well as use information of the travel itinerary planning; and selecting the former n travel strategy projects with highest recommendation grades for each type of the travel strategy projects and recommending the former n travel strategy projects to the recommended user, wherein n is an integral number and not less than 1. Through the adoption of the method disclosed by the invention, the user experience can be improved.
Description
Technical field
The present invention relates to the computer internet technical field, in particular to a kind of recommend method and device of the attack strategy project of travelling.
Background technology
User's tour schedule planning is called the travelling attack strategy, comprises a series of projects that arrange according to time sequencing, and such as food and drink, lodging, sight spot, amusement and shopping etc., these projects can be referred to as POI(tourism attack strategy project).
In internet online tourism system, the high-quality project that needs to extract existing attack strategy represents to the user, makes things convenient for the user to understand the bright spot of attack strategy, and perhaps the user is in the process of making attack strategy, according to travelling address, travel time etc. for the user recommends suitable project, improve the quality that the user travels.
At present, POI recommends existing a lot of ready-made method, for example:
(1) according to the position at the current place of user, give him (she) and recommend nearest POI(such as restaurant), perhaps in conjunction with the condition of user's appointment (such as price etc.), filter out the interested POI of user;
(2) collaborative filtering recommending.Namely by the behavior of a large number of users, the user that interest is close gathers one group, and the interested POI of groups of people in same group is recommended other people in the group; The POI that is perhaps selected by a lot of people with a large amount of the time assembles in groups, when certain POI in the new user selection group, is other the POI in its recommendation group.
Above-mentioned POI recommend method is applied in the activity of short distance widely, such as choosing restaurant, hotel and public place of entertainment etc. the position is relied on stronger POI, can obtain preferably effect.
Yet, tour schedule planning for long-range destination (such as country, city), positional information is not the main factor of considering for the user, the user generally needs the other factors of balance when selecting POI, for example, whether other user likes this POI, and the preference of user individual (religion, faith etc.) etc.Therefore, adopt above-mentioned recommend method generally to be difficult to the user the suitable recommended project is provided.
Summary of the invention
For planning is difficult to the problem that the user provides the suitable recommended project to the tour schedule of long-range destination in the correlation technique, the invention provides a kind of recommend method and device of the attack strategy project of travelling, to address the above problem at least.
According to an aspect of the present invention, provide a kind of recommend method of the attack strategy project of travelling, having comprised: obtain the destination of recommended user's tour schedule planning, and the type of the tourism attack strategy project that need to recommend to recommended user; User's evaluating data, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project according to each tourism attack strategy project of the described type of the described destination of pre-save, and in conjunction with the matching degree of each described tourism attack strategy project and described recommended user's individuation data, obtain the recommendation score of each described tourism attack strategy project; For every type tourism attack strategy project, select the highest front n of described recommendation score described tourism attack strategy project recommendation to described recommended user, wherein, n is integer, and n 〉=1.
Preferably, user's evaluating data according to each tourism attack strategy project of the described type in described destination of pre-save, the dependent event information of each described tourism attack strategy project, and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project, and in conjunction with the matching degree of each described tourism attack strategy project and described recommended user's individuation data, obtain the recommendation score of each described tourism attack strategy project, comprise: according to described user's evaluating data, and comprise the tour schedule planning of each described tourism attack strategy project and the use information that this tour schedule is planned, obtain the basic score base_score (poi) of each described tourism attack strategy project; According to the dependent event information of each described tourism attack strategy project of preserving, obtain the event scoring event_score (poi) of each described tourism attack strategy project in described recommended user's travel time section; Calculate the recommendation score score (poi) of each described tourism attack strategy project: score (poi)={ base_score (poi) * weight1+event_score (poi) * weight2}*personal_weight according to following formula; Wherein, personal_weight is the personalized weight of described tourism attack strategy project, is used for estimating the matching degree of described tourism attack strategy project and recommended people's personality data; Weight1 and weight2 are respectively the weight weight1+weight2=1 of basic score and event scoring.
Preferably, according to described user's evaluating data, and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project, obtain the basic score base_score (poi) of each described tourism attack strategy project, comprise: from described user's evaluating data of each described tourism attack strategy project, obtain the user to the scoring user_eval (poi) of described tourism attack strategy project, and according to the use acquisition of information user of the tour schedule planning that comprises each described tourism attack strategy project and the planning of this tour schedule temperature hot_rate (poi) to described tourism attack strategy project; Calculate in the following manner the basic score base_score (poi) of each described tourism attack strategy project: base_score (poi)=user_eval (poi) * b_weight1+hot_rate (poi) * b_weight2; Wherein, b_weight1 and b_weight2 are respectively the weight of user_eval (poi) and hot_rate (poi), and b_weight1+b_weight2=1.
Preferably, from described user's evaluating data of each described tourism attack strategy project, obtain the user to the scoring user_eval (poi) of described tourism attack strategy project, comprise: from user's evaluating data of each described tourism attack strategy project, obtain each user to the initial score of described tourism attack strategy project: all users are carried out normalized to the initial score of described tourism attack strategy project, and calculate the mean value user_direct_eval after the normalized; Calculate the time weight time_weight of described tourism attack strategy project in described travel time section, wherein, the described time weight of same tourism attack strategy project in different time sections is not identical; Obtain the user to the scoring user_eval (poi) of described tourism attack strategy project according to following formula: user_eval (poi)=user_direct_eval*time_weight.
Preferably, the user comprises the temperature of described tourism attack strategy project: quote temperature and estimate temperature; According to the use acquisition of information user of the tour schedule planning that comprises each described tourism attack strategy project and the planning of this tour schedule temperature hot_rate (poi) to described tourism attack strategy project, comprise: step 1, for any one described tourism attack strategy project wherein, that obtains in the following manner described tourism attack strategy project quotes temperature ref_hot_rate: the number of times that the described tourism attack strategy that records in the use information according to the tour schedule planning that comprises described tourism attack strategy project of preserving is downloaded, and temperature sched_hote_rate is used in the download that obtains described tour schedule planning; The average poi_sched_avg_rate of temperature sched_hote_rate is used in the download that calculating has comprised all tour schedules planning of described tourism attack strategy project; The set of the tour schedule planning of relevant tourism attack strategy project and current described tourism attack strategy project has been quoted in calculating, temperature is used in download according to all tourism attack strategy projects in the described set, calculate the download of all tourism attack strategy projects in the described set and use temperature average all_sched_avg_rate, wherein, described relevant tourism attack strategy project refers to comprise other tourism attack strategy project that comprises in the tour schedule planning of current described tourism attack strategy project; That calculates current described tourism attack strategy project quotes temperature ref_hot_rate:ref_hot_rate=poi_sched_avg_rate/all_sched_a vg_rate; Step 2, for any one described tourism attack strategy project wherein, obtain in the following manner the evaluation temperature comment_hot_rate of described tourism attack strategy project: cmt_num[0 is counted in the evaluation of obtaining current described tourism attack strategy project from user's evaluating data of the tourism attack strategy project of pre-save], and cmt_num[1 is counted in the evaluation of described relevant tourism attack strategy project], cmt_num[k], wherein k represents the quantity of described relevant tourism attack strategy project; Calculate the general comment valence mumber of current described tourism attack strategy project and described relevant tourism attack strategy project:
Calculate the evaluation temperature comment_hot_rate=cmt_num[0 of current described tourism attack strategy project]/cmt_avg_num; Step 3, for any one described tourism attack strategy project wherein, calculate the user to the temperature of described tourism attack strategy project: hot_rate=(ref_hot_rate+comment_hot_rate)/N, wherein, N is preset value, and N 〉=1.
Preferably, obtain the event scoring event_score (poi) of each described tourism attack strategy project in described recommended user's travel time section, comprise: for any one the tourism attack strategy in each described tourism attack strategy project, according to configuration in advance, from the dependent event information of described tourism attack strategy project, obtain first score value corresponding to periodic event of the generation in the described travel time section; Relevant information according to the real-time event that records in the described dependent event information, judge whether to exist the influential accident of described tourism attack strategy project, if have, then according to the type of emergency event that sets in advance and the corresponding relation of score value, obtain second score value corresponding with the type of described accident; According to the first score value and described the second score value, obtain the event scoring of described tourism attack strategy project.
Preferably, in the following manner described tourism attack strategy project obtain personalized weight: obtain described recommended people's personality data, wherein, described individuation data comprises: the tourism attack strategy item types of described recommended people's preference and described recommended people's certain preference item; Judge whether current described tourism attack strategy project belongs to the tourism attack strategy item types of described recommended people's preference, obtain tourism attack strategy item types preference travel_poi_perf according to judged result; According to the corresponding relation of the certain preference item that sets in advance and certain preference item weight, obtain the certain preference item weight perf_weight[i corresponding with every certain preference item of described recommended people], wherein, i=1,2 ... n, n are the sum of described recommended people's certain preference item; Calculate the personalized weight personal_weight:personal_weight=travel_poi_perf*perf_wei ght[1 of obtaining of described tourism attack strategy project according to following formula] * perf_weght[2] * ... * perf_weight[n].
Preferably, described user's evaluating data comprises: the user is to the scoring of tourism attack strategy project, user textual description information and the evaluation time to tourism attack strategy project.
According to another aspect of the present invention, a kind of recommendation apparatus of the attack strategy project of travelling is provided, comprise: memory module is used for user's evaluating data of each tourism attack strategy project of storage system, dependent event information and the planning of existing tour schedule and the use information thereof of each described tourism attack strategy project; The first acquisition module is used for obtaining the destination of recommended user's tour schedule planning, and the type of the tourism attack strategy project that need to recommend to described recommended user; The second acquisition module, be used for obtaining from the data of memory module storage user's evaluating data, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project of each tourism attack strategy project of the described type of described destination, obtain the individuation data that from described recommended user's log-on message, obtains described recommended user; Computing module, user's evaluating data of each the tourism attack strategy project that is used for obtaining according to described the second acquisition module, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project, and in conjunction with the matching degree of each described tourism attack strategy project and described individuation data, calculate the recommendation score of each described tourism attack strategy project; Recommending module is used for the tourism attack strategy project for every type, selects recommendation score to arrive high front n described tourism attack strategy project recommendation most to described recommended user, and wherein, n is integer, and n 〉=1.
Preferably, described computing module comprises: the first acquiring unit, be used for obtaining the basic score base_score (poi) of each described tourism attack strategy project according to described user's evaluating data and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project; Second acquisition unit is used for the dependent event information according to each described tourism attack strategy project of preserving, and obtains the event scoring event_score (poi) of each described tourism attack strategy project in described recommended user's travel time section; Computing unit is used for calculating according to following formula the recommendation score score (poi) of each described tourism attack strategy project: score (poi)={ base_score (poi) * weight1+event_score (poi) * weight2}*personal_weight; Wherein, personal_weight is the personalized weight of described tourism attack strategy project, is used for estimating the matching degree of described tourism attack strategy project and recommended people's personality data; Weight1 and weight2 are respectively the weight of basic score and event scoring.
By the present invention, User evaluating data, existing tourism attack strategy and usage data, event information and user's preference, calculate the recommendation score of each tourism attack strategy project (POI) of attack strategy, the descending ordering of will marking, get one of the score value maximum or several project recommendations to the user, convenient extraction has the bright spot project of attack strategy or for the user who creates new attack strategy provides useful help, has improved user's experience.
Description of drawings
Accompanying drawing described herein is used to provide a further understanding of the present invention, consists of the application's a part, and illustrative examples of the present invention and explanation thereof are used for explaining the present invention, do not consist of improper restriction of the present invention.In the accompanying drawings:
Fig. 1 is the process flow diagram of recommend method of the tourism attack strategy project of the embodiment of the invention;
Fig. 2 is the structural representation of recommendation apparatus of the tourism attack strategy project of the embodiment of the invention;
Fig. 3 is the structural representation of computing module in the preferred embodiment of the present invention;
Fig. 4 is the structural representation of recommendation apparatus of the tourism attack strategy project of the preferred embodiment of the present invention.
Embodiment
Hereinafter also describe in conjunction with the embodiments the present invention in detail with reference to accompanying drawing.Need to prove that in the situation of not conflicting, embodiment and the feature among the embodiment among the application can make up mutually.
Before the technical scheme that the embodiment of the invention is provided is described, at first the technical term that relates in the embodiment of the invention is described.
1) tour schedule planning is also referred to as the travelling attack strategy: the flow layout of user's travelling is called the travelling attack strategy, stresses the tourism planning of long-range destination in the embodiment of the invention;
2) tourism attack strategy project (POI): a project of sign travelling attack strategy, it is dissimilar to be divided into food and drink, lodging, sight spot, amusement, shopping etc., and its general and concrete place is associated;
3) POI dependent event: event that special time period occurs, that POI is made a significant impact, such as the restaurant give a discount, oriental cherry in the sight spot is in full bloom, shopping place discounting etc.Temporal characteristics according to occuring is divided into recurrent event and accident, and recurrent event can predict that the flowers are in blossom such as certain park; Accident refers to the event that occurs once in a while, can not expect, pollutes such as POI etc.;
4) relevant POI: if the POI of appointment in already present travelling attack strategy P, other POI among the P becomes the relevant POI of this appointment POI so.
Embodiment one
According to the embodiment of the invention, provide a kind of recommend method of the attack strategy project of travelling.
Fig. 1 is that as shown in Figure 1, the method mainly comprises according to the process flow diagram of the recommend method of the tourism attack strategy project of the embodiment of the invention:
Step S102 obtains the destination of recommended user's tour schedule planning, and the type of the tourism attack strategy project that need to recommend to recommended user;
For example, the current tour schedule of formulating of user plans that its destination is Beijing, and a tourism attack strategy project of its structure is food and drink, then the destination of the recommended user's of system acquisition tour schedule planning is Beijing, and the type of the tourism attack strategy project that need to recommend to this user is food and drink.
Step S104, user's evaluating data, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project according to each tourism attack strategy project of the described type of the described destination of pre-save, and in conjunction with the matching degree of each described tourism attack strategy project and described recommended user's individuation data, obtain the recommendation score of each described tourism attack strategy project;
Take the destination as Beijing, the type of the tourism attack strategy project of recommending is that food and drink is example, in step S104, obtain user's evaluating data of each food and drink project of Pekinese of pre-save, dependent event information and the existing use information that includes tour schedule planning and the planning of this tour schedule of one of them food and drink project of each food and drink project.For example, Pekinese's food and drink project of preservation have Quanjude Roast Duck, Donglaishun, and the king remember the quick-boiled tripe king, obtain the user to the information such as scoring, textual description and evaluation time of each project.Wherein, the dependent event information of each food and drink project comprises the relevant information of recurrent event and accident, for example, Quanjude Roast Duck make a call to annual August 9 foldings or, on October 15th, 2012, accident occurs in the Donglaishun, for example, the information such as can't do business is being fitted up in the Donglaishun.According to the above-mentioned information of obtaining, can obtain the recommendation score of each tourism attack strategy project.
In actual applications, for each tourism attack strategy project, daily record that can be by analyzing existing system, user obtain user's evaluating data (comprising scoring, the text message of estimating, evaluation time etc.) of each tourism attack strategy project, the data such as travelling project that use is checked in download, the attack strategy of travelling comprises of existing tourism attack strategy to the evaluating data of attack strategy project, the relevant information of existing tourism attack strategy.
Step S106 for every type tourism attack strategy project, selects the highest front n the tourism attack strategy project recommendation of recommendation score to recommended user, and wherein, n is integer, and n 〉=1.
Said method by the embodiment of the invention provides if the set of the most original recommended project is each element of existing tourism attack strategy, namely can be the extraction bright spot project wherein of this tourism attack strategy; If the set of the most original recommended project is travelling attack strategy project all in the system, can provide for the user who creates the travelling attack strategy so the tabulation of the travelling project that can select, the establishment of convenient tourism attack strategy.
In an embodiment of the embodiment of the invention, can obtain by following steps the recommendation score score (poi) of each tourism attack strategy project:
Step 1 according to described user's evaluating data and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project, is obtained the basic score base_score (poi) of each described tourism attack strategy project; Can comprise that wherein the user is to the temperature of the evaluation of described tourism attack strategy project and this tourism attack strategy project;
Step 2 according to the dependent event information of each described tourism attack strategy project of preserving, is obtained the event scoring event_score (poi) of each described tourism attack strategy project in described recommended user's travel time section; This parameter is used for being characterized by in the hourage section event to the scoring of the impact of this tourism attack strategy project;
Step 3, calculate the recommendation score score (poi) of each tourism attack strategy project according to following formula:
score(poi)={base_score(poi)*weight1+event_score(poi)*weight2}*personal_weight；
Wherein,
Personal_weight is the personalized weight of tourism attack strategy project, is used for estimating the matching degree of described tourism attack strategy project and recommended people's personality information;
Weight1 and weight2 are respectively the weight of basic score and event scoring, be used for regulating the recommendation weight between basic score and the event scoring, in actual applications, if relatively more responsive to time factor, larger weight2 value then can be set, but must satisfy weight1+weight2=1.In specific implementation process, can for default fixedly value, for example, can be set to weight1=0.4, weight2=0.6.
In an optional embodiment of the embodiment of the invention, can obtain by following steps the basic score base_score (poi) of each tourism attack strategy project:
Step 1, from described user's evaluating data of each described tourism attack strategy project, obtain the user to the scoring user_eval (poi) of described tourism attack strategy project, and according to the use acquisition of information user of the tour schedule planning that comprises each described tourism attack strategy project and the planning of this tour schedule temperature hot_rate (poi) to described tourism attack strategy project;
Step 2, calculate in the following manner the basic score base_score (poi) of each described tourism attack strategy project:
base_score(poi)=user_eval(poi)*b_weight1+hot_rate(poi)*b_weight2；
Wherein, user_eval (poi) is that the user is to the scoring of described tourism attack strategy project, hot_rate (poi) is that the user is to the temperature of described tourism attack strategy project, b_weight1 and b_weight2 are respectively the weight of user_eval (poi) and hot_rate (poi), and b_weight1+b_weight2=1, occurrence can arrange according to the actual requirements, for example, if recommended user relatively values other users' scoring, value that then can b_weight1 is set to the value greater than b_weight2, otherwise, if recommended user relatively values the temperature of this tourism attack strategy project, namely to what of the interested user of this tourism attack strategy project, value that then can b_weight2 is set to the value greater than b_weight1.And do not have the user in the situation of clear and definite demand, b_weight1=0.5 and b_weight2=0.5 can be set.
In an optional embodiment of the embodiment of the invention, can obtain the user to the scoring of described tourism attack strategy project by following steps:
Step 1 is obtained the user to the initial score of described tourism attack strategy project, and this initial score refers to the user to the direct scoring of this POI, and this scoring derives from the user to the original evaluating data of this tourism attack strategy project;
Step 2 is carried out normalized with all users to the initial score of described tourism attack strategy project, and calculates the mean value user_direct_eval after the normalized;
Step 3 is calculated the time weight time_weight of described tourism attack strategy project in described travel time section, and wherein, the described time weight of same tourism attack strategy project in different time sections is not identical; Wherein, the travel time section can obtain according to the travel time section of formulation in recommended user's the tour schedule planning, for example, hourage, section can refer to front and back N days of travel dates in (such as front and back 20 days), also comprised the front and back 20 days on all corresponding dates in time in the past.This weight is used for distinguishing the Attraction Degree to visitor of POI in different time sections.In a preferred implementation, the average ratings number of the average ratings number of every day in Time_weight=section hourage/institute free interior every day.
Step 4 obtains the user to the scoring user_eval (poi) of described tourism attack strategy project according to following formula:
user_eval(poi)=user_direct_eval*time_weight。
In an optional embodiment of present embodiment, the user can comprise the temperature of described tourism attack strategy project: quote temperature and estimate temperature.Therefore, in an optional embodiment of present embodiment, can obtain the user to the temperature hot_rate of described tourism attack strategy project by following steps:
Step 1, for each tourism attack strategy project, obtain in the following manner it and quote temperature ref_hot_rate:
Step 1.1, the number of times that this tour schedule planning of recording in the use information according to the existing tour schedule planning that comprises described tourism attack strategy project is downloaded obtains downloading and uses temperature (sched_hote_rate);
Step 1.2, the average poi_sched_avg_rate of temperature (sched_hote_rate) is used in the download of calculating all tour schedule planning of having quoted current described tourism attack strategy project;
Step 1.3, the set of the attack strategy of relevant tourism attack strategy project and current tourism attack strategy project has been quoted in calculating, temperature is used in download according to all tourism attack strategy projects in the set, temperature average all_sched_avg_rate is used in the download of all tourism attack strategy projects in the set of computations, wherein, close tourism attack strategy project and refer to comprise other tourism attack strategy project that comprises in the tour schedule planning of current described tourism attack strategy project;
Step 1.4, calculate the temperature of quoting of current tourism attack strategy project:
ref_hot_rate=poi_sched_avg_rate/all_sched_avg_rate；
Step 2, for each tourism attack strategy project, obtain in the following manner it and estimate temperature comment_hot_rate:
Step 2.1, from user's evaluating data of the tourism attack strategy project of preserving, obtain the evaluation of current described tourism attack strategy project and count cmt_num[0], and cmt_num[1 is counted in the evaluation of relevant tourism attack strategy project] ... cmt_num[k], wherein k represents the quantity of relevant tourism attack strategy project;
Step 2.2, calculate the general comment valence mumber of current described tourism attack strategy project and described relevant tourism attack strategy project:
Step 2.3 is calculated the evaluation temperature comment_hot_rate=cmt_num[0 of current tourism attack strategy project]/cmt_avg_num;
Step 3, for each tourism attack strategy project, calculate the user to the temperature of described tourism attack strategy project: hot_rate=(ref_hot_rate+comment_hot_rate)/N, wherein, N is preset value, and N 〉=1.
In an optional embodiment of present embodiment, can calculate in the following manner the event scoring of described tourism attack strategy project:
Step 1, any one the tourism attack strategy in each described tourism attack strategy project according to configuration in advance, obtains the score value corresponding to periodic event of the generation in the described travel time section from the dependent event information of described tourism attack strategy project;
Step 2, relevant information according to the real-time event that records in the described dependent event information, judge whether to exist the influential accident of described tourism attack strategy project, if have, then according to the type of described accident, the type of emergency event that sets in advance and the corresponding relation of score value obtain the score value corresponding with described accident; The relevant information of the real-time event that wherein, records in the dependent event information can be provided in real time by external system;
Step 3, score value and score value corresponding to described accident corresponding according to described periodic event, obtain the event scoring of described tourism attack strategy project, for example, the event scoring can be periodic corresponding score value and score value sum corresponding to accident of event, perhaps, also can be respectively score value corresponding to score value corresponding to periodic event and accident a weight is set respectively, then calculate the event scoring of this tourism attack strategy project.
In embodiments of the present invention, event mainly refers to before and after hourage the event that POI is made a significant impact in a period of time.According to scoring impact is divided into two kinds on POI: useful event and diminish event, the former calculate one on the occasion of scoring, the latter calculates the scoring of a negative value, the scoring summation of all events obtains the event scoring of this POI.
All between-1 to 1, the sight spot scoring that any event does not occur is 0 in the scoring of all individual events.
For periodic event, can adopt and excavate or artificial mode, dispose corresponding score value.
For paroxysmal event, the relevant information (such as event type) of the real-time event that provides according to external system, manual configuration or calculate a marking system.
POI type for different has different events, is exemplified below:
Food and drink: group buying voucher, discounting season, food hygiene etc.;
The sight spot: the adolescence, day, concert, contamination accident etc. open for free;
Shopping: coupon, new product listing etc.
In an optional embodiment of the embodiment of the invention, can be by the personalized weight of obtaining of the described tourism attack strategy of following steps project:
Step 1 is obtained described recommended people's personality data, and wherein, described individuation data comprises: the tourism attack strategy item types of described recommended people's preference and described recommended people's certain preference item;
Step 2 judges whether current described tourism attack strategy project belongs to the tourism attack strategy item types of described recommended user preference, obtains tourism attack strategy item types preference travel_poi_perf according to judged result; Wherein, travel_poi_perf can be between 0 to 10 value, if the value of this parameter surpasses 1, represent that then recommended user has stronger preference to the attack strategy project of the type, such as, part population has stronger preference to shopping, can arrange to surpass 1 value.Perhaps, this value also can allow the user that some preference informations are provided by providing option to the user, such as for the shopping classification, provides the ground not liking, like, must go etc., is mapped on the fixing travel_poi_perf for these options.
Step 3 according to the corresponding relation of the certain preference item that sets in advance and certain preference item weight, is obtained the certain preference item weight perf_weight[i corresponding with every certain preference item of described recommended people], wherein, i=1,2,, n, n are the sum of described recommended people's certain preference item;
For example, can construct in advance the mapping table of a preference: map＜preference, tag, poi_type〉-〉 perf_weight, preference (perference) is described in the preference weight that has on the POI that particular community (tag) and type are poi_type;
Wherein, tag and poi_type can value be " * ", and expression is all used this weight for all tag or poi_type.
For example,＜the Huis, Islamic, restaurant〉-〉 1.5;＜drive parking lot, *〉-〉 1.1;
During enforcement, user's preference information, the tag of POI and POI type information query mappings table obtain perf_weight;
Step 4, calculate the personalized weight personal_weight that obtains of described tourism attack strategy project according to following formula:
personal_weight=travel_poi_perf*perf_weight[1]*perf_weght[2]*...*perf_weight[n].
In the present embodiment, for each POI, for the specific information of recommended people, calculate personalized weight in conjunction with the Some features of POI.Wherein, individuation data can consider that user's religion, schooling, consumption eating habit to the scoring of POI, can mark respectively for different POI types.If without any individuation data, personalized weight is made as 1.
For example, in an optional embodiment of the embodiment of the invention, can set in advance a corresponding relation, recommendation score value corresponding to record parameters, then the recommendation score that parameters is corresponding adds up, thereby obtains the recommendation score of corresponding tourism attack strategy project.For example, user in user's evaluating data can be set to the recommendation score value corresponding to different average score of tourism attack strategy project, recommendation score value corresponding to different access times that comprises the tour schedule planning of tourism attack strategy project, the recommendation score value that all kinds of recurrent events and all kinds of accident are corresponding different, and from the corresponding different recommendation score value of Different matching degree of user's individuation data, then according to the actual conditions of each tourism attack strategy project, obtain corresponding recommendation score value, and then obtain the recommendation score of each tourism attack strategy project.The method is a kind of acquisition methods of recommendation score, but is not limited to this, also can adopt other method in concrete the application.
Embodiment two
According to the embodiment of the invention, a kind of recommendation apparatus of the attack strategy project of travelling is provided, this device can be used for the method that realization embodiment one provides.
Fig. 2 is the structural representation according to the recommendation apparatus of the tourism attack strategy project of the embodiment of the invention, as shown in Figure 2, this device can comprise: memory module 10 is used for user's evaluating data of each tourism attack strategy project of storage system, dependent event information and the planning of existing tour schedule and the use information thereof of each tourism attack strategy project; The first acquisition module 20 is used for obtaining recommended user's the destination of tour schedule planning and the type of the tourism attack strategy project that need to recommend to recommended user; The second acquisition module 30, with memory module 10 be connected acquisition module 20 and be connected, be used for obtaining from the data of memory module storage user's evaluating data, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project of each tourism attack strategy project of the described type of described destination, obtain the individuation data that from described recommended user's log-on message, obtains described recommended user; Computing module 40, be connected with the second acquisition module 30, user's evaluating data of each the tourism attack strategy project that is used for obtaining according to described the second acquisition module, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project, and in conjunction with the matching degree of each described tourism attack strategy project and described individuation data, calculate the recommendation score of each described tourism attack strategy project; Recommending module 50 is connected with computing module 40, is used for the tourism attack strategy project for every type, selects recommendation score to arrive high front n described tourism attack strategy project recommendation most to described recommended user, and wherein, n is integer, and n 〉=1.
Fig. 3 is that an optional embodiment of the embodiment of the invention can, the structural representation of computing module 40, as shown in Figure 3, computing module 40 can comprise: the first acquiring unit 402, be used for obtaining the basic score base_score (poi) of each described tourism attack strategy project according to described user's evaluating data and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project; Second acquisition unit 404 is used for the dependent event information according to each described tourism attack strategy project of preserving, and obtains the event scoring event_score (poi) of each described tourism attack strategy project in described recommended user's travel time section; Computing unit 406 is connected with the first acquiring unit 402 and second acquisition unit 404, is used for calculating according to following formula the recommendation score score (poi) of each described tourism attack strategy project:
score(poi)={base_score(poi)*weight1+event_score(poi)*weight2}*personal_weight；
Wherein,
Personal_weight is the personalized weight of described tourism attack strategy project, is used for estimating the matching degree of described tourism attack strategy project and recommended people's personality data;
Weight1 and weight2 are respectively the weight of basic score and event scoring.
In specific implementation process, the first acquiring unit 402 can obtain according to the mode described in above-described embodiment the basic score base_score (poi) of each described tourism attack strategy project, and second acquisition unit 404 also can obtain according to the mode described in above-described embodiment the event scoring event_score (poi) of each described tourism attack strategy project, repeats no more in the concrete present embodiment.
Need to prove, the embodiment of above-mentioned computing module 40 is an optional embodiment of the embodiment of the invention, but be not limited to this, in actual applications, computing module 40 also can adopt other modes to calculate the recommendation score of each tourism attack strategy project, is not construed as limiting in the concrete embodiment of the invention.
Fig. 4 is the structural representation of recommendation apparatus of attack strategy project of travelling according to the preferred embodiment of the invention, as shown in Figure 3, this device comprises: user's rating database, attack strategy usage data storehouse, event database and preference descriptive data base (these databases are equivalent to above-mentioned memory module 10) and recommending module, recommending module comprises: the basic score computing module is used for calculating user's scoring and temperature and calculates; The event grading module is used for the scoring of calculating event; Personalized grading module is used for calculating personalized scoring according to recommended user's individuation data; Scoring merges module, is used for that basic score computing module, event grading module and personalized grading module are obtained scoring and merges, and obtains the recommendation score value of POI.
In embodiments of the present invention, the preparatory stage that it is basic data that the recommendation of POI mainly is divided into two parts and score calculation stage, the below is described respectively.
The preparatory stage of basic data
Basic data comprises user's evaluating data, attack strategy usage data, event data, preference data of description.
Wherein, user's evaluating data comprises the time to scoring and the scoring of POI of a large number of users; The attack strategy usage data is the description of all attack strategys and the information that is downloaded use; Event database comprise POI and with description and weight data of its dependent event; The preference data of description comprises the mapping table of preference and weight.
In addition, also have recommended user's individuation data and need to calculate the POI data of scoring, this part is the input for specific recommendations.
The score calculation stage
Comprise that the user marks, temperature is marked, event is marked, personalized mark four individual event score calculation and scoring merging.
The calculating that user's scoring, temperature are marked, the event scoring can be regular to all POI when having the new POI demand of finding the solution to arrive, can directly be inquired about, and avoids a large amount of enforcement to process.
Calculating in real time of personalized scoring dependence preference database and recommended user's customized information.
At last each item rating is merged into one according to weight and recommend score value.
The weight of using in the commending system adopts manual the setting, and the methods such as machine learning can be used for optimizing and revising the setting of weight.
Embodiment three
Present embodiment describes the technical scheme that the embodiment of the invention provides with a concrete example.In the present embodiment, the recommendation of tourism attack strategy project is divided into following several stages:
(1) data are prepared
Suppose, existing item1, item2, four travellings of item3, item4 attack strategy project (restaurant type) in the system, the existing subscriber has used these four attack strategy project build three tourism attack strategys, the project that each attack strategy comprises is as follows.By adding up these three tourism attack strategy download log, obtain each tourism attack strategy and divide other download time.
TR_BOOK1={item1,item2,item3},download_num=100
TR_BOOK2={item2,item3,item4}download_num=130
TR_BOOK3={item1,item3}download_num=80
At the user evaluation of attack strategy project, stored the time of all users to evaluation and the evaluation of attack strategy project.In the present embodiment, everyone is to { item3 obtains user_direct_eval (item1, item2, item3, item4)=(0.9,0.6,0.8,0.7) after mean value is done in item4} scoring (value is between 0 to 1) for item1, item2.
By adding up all users' comment data, can obtain:
Evaluation quantity in the front and back of current time 20 days: curr_comment_count (item1, item2, item3, item4)=(10,23,34,9);
The overall merit quantity of (getting nearest 1 year, i.e. 365 days data) in all fates: total_comment_count (item1, item2, item3, item4)=(100,80,300,100)
Wherein, Item1 is a Huis dining room of registering, and other three do not have special attribute.
(2) basic score is calculated
1.POI user scoring
In the present embodiment, user_eval (item1, item2, item3, item4)=user_direct_eval*time_weight
=(365*10/(100*20),365*23/(80*20),365*34/(300*20),365*9/(100*20))
=(1.825,5.247,2.068,1.643)
2.POI temperature
The temperature of each tourism attack strategy obtains according to the download time of each tourism attack strategy, and in the present embodiment, temperature is used in the download of each tourism attack strategy:
sched_hot_rate(TR_BOOK1,TR_BOOK2,TR_BOOK3)=(100,130,80)。
The average of temperature is used in the download of quoting the tourism attack strategy of each POI:
poi_sched_avg_rate(item1,item2,item3,item4)={(80+100)/2,(100+130)/2,(100+130+80)/3,130}={90,115,103,130}。
The relevant POI set of POI is respectively: relate_poi (item1, item2, item3, item4)={ { item2, item3}, { item1, item3, item4}, { item1, item2, item4}, { item2, item3}}.
The complete or collected works of the relevant attack strategy of Item1, item2, item3, item4 are exactly TR_BOOK1, TR_BOOK2, and TR_BOOK3, then, relevant attack strategy complete or collected works' temperature average all_sched_avg_rate (item1, item2, item3, item4)={ 103,103,103,103}.
Therefore, the temperature of quoting of each attack strategy project of travelling:
ref_hot_rate(item1,item2,item3,item4)=(90/103,115/103,103/103,130/103)=(0.873,1.117,1,1.262)
In the present embodiment, the evaluation temperature of each POI is:
cmt_hot_rate(item1,item2,item3,item4)={(100*3/(100+80+300)),(80*4/(100+80+300+100)),(300*4/(100+80+300+100)),(100*4/(80+300+100))}={0.832,0.552,2.068,0.832}
N in the hot_rate computing method is used for regulating the parameter that temperature is calculated, and generalized case is got N=2, namely gets the temperature that the average of quoting temperature and estimating temperature is calculated POI, and then in the present embodiment, the temperature of each POI is:
hot_rate=((0.873+0.832)/2,(1.117+0.552)/2,(1+2.068)/2,(1.262+0.832)/2)
=(0.8525,0.8345,1.534,1.047)
3. Calculating Foundation scoring
In the present embodiment, in Calculating Foundation when scoring,, user's scoring of POI and the weight between user's temperature can be by arranging b_weight1 and the b_weight2 weight is regulated, and the value of present embodiment setting is respectively 0.6 and 0.4.
Then in the present embodiment, the basic score of each POI is respectively: base_score (poi)=(1.825*0.6+0.8525*0.4,5.247*0.6+1.534*0.4,2.068*0.6+1.534*0.4,1.643*0.6+1.047*0.4)=(1.436,3.7618,1.8544,1.4046)
(3) event scoring
Suppose among the current item1 contamination accident to have occured, movable unfavorable to going sight-seeing, and item3 has a nationwide activity, and tourism is had facilitation, then can distinguish each item and compose an event scoring (these information can be put in order by artificial mode), be in the present embodiment:
evet_score(item1,item2,item3,item4)={-0.5,0,1,0}
(4) personalized weight
Systemic presupposition has Extraordinary data＜Huis, Islamic, restaurant〉-〉 1.5, system is to the type indistinction of attack strategy project, travel_poi_perf=1.
If that use current commending system is a user of the Hui ethnic group, the selection in restaurant there is requirement.According to the explanation of data preparatory stage, there is Huis' attribute in the item1 restaurant, and then the personalized weight of each POI is:
personal_weight(item1,item2,item3,item4)=(1.5,1,1,1)。
(5) recommendation score is calculated
At present embodiment, basic score weight and event scoring weight are respectively weight1=0.6, weight2=0.4.
The recommendation score of each POI that then calculates is as follows:
score(item1)=(1.436*0.6-0.5*0.4)*1.5=0.9924
score(item2)=(3.7618*0.6+0*0.4)*1=2.25708
score(item3)=(1.8544*0.6+1*0.4)*1=1.51264
score(item4)=(1.4046*0.6+0*0.4)*1=0.84276
The ordering of then recommending is item2, item3, item1, item4, if value is recommended two elements for the user, can recommend item2 and item3 so.
From above description, can find out, by the technical scheme that one of above-described embodiment provides, considered the factor of the many aspects such as focus, event, individual preference of data, the POI of user's style of writing data, existing attack strategy, for providing, the user more reasonably recommends; With the focus of POI, movablely recommend factor the inside, and use the method for machine to extract automatically the hot spot data of POI, adjust the recommendation score of this project according to the time of travelling; Consider different crowds, the preference demands such as own culture, religion, faith are arranged, arrangement is in the middle of the scoring of recommending.
Obviously, those skilled in the art should be understood that, above-mentioned each module of the present invention or each step can realize with general calculation element, they can concentrate on the single calculation element, perhaps be distributed on the network that a plurality of calculation elements form, alternatively, they can be realized with the executable program code of calculation element, thereby, they can be stored in the memory storage and be carried out by calculation element, and in some cases, can carry out step shown or that describe with the order that is different from herein, perhaps they are made into respectively each integrated circuit modules, perhaps a plurality of modules in them or step are made into the single integrated circuit module and realize.Like this, the present invention is not restricted to any specific hardware and software combination.
The above is the preferred embodiments of the present invention only, is not limited to the present invention, and for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any modification of doing, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. the recommend method of attack strategy project of travelling is characterized in that, comprising:
Obtain the destination of recommended user's tour schedule planning, and the type of the tourism attack strategy project that need to recommend to recommended user;
User's evaluating data, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project according to each tourism attack strategy project of the described type of the described destination of pre-save, and in conjunction with the matching degree of each described tourism attack strategy project and described recommended user's individuation data, obtain the recommendation score of each described tourism attack strategy project;
For every type tourism attack strategy project, select the highest front n of described recommendation score described tourism attack strategy project recommendation to described recommended user, wherein, n is integer, and n 〉=1.
2. method according to claim 1, it is characterized in that, user's evaluating data, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project according to each tourism attack strategy project of the described type in described destination of pre-save, and in conjunction with the matching degree of each described tourism attack strategy project and described recommended user's individuation data, obtain the recommendation score of each described tourism attack strategy project, comprising:
According to described user's evaluating data and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project, obtain the basic score base_score (poi) of each described tourism attack strategy project;
According to the dependent event information of each described tourism attack strategy project of preserving, obtain the event scoring event_score (poi) of each described tourism attack strategy project in described recommended user's travel time section;
Calculate the recommendation score score (poi) of each described tourism attack strategy project according to following formula:
score(poi)={base_score(poi)*weight1+event_score(poi)*weight2}*personal_weight；
Wherein,
Personal_weight is the personalized weight of described tourism attack strategy project, is used for estimating the matching degree of described tourism attack strategy project and recommended people's personality data;
Weight1 and weight2 are respectively the weight weight1+weight2=1 of basic score and event scoring.
3. method according to claim 2, it is characterized in that, according to described user's evaluating data and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project, obtain the basic score base_score (poi) of each described tourism attack strategy project, comprising:
From described user's evaluating data of each described tourism attack strategy project, obtain the user to the scoring user_eval (poi) of described tourism attack strategy project, and according to the use acquisition of information user of the tour schedule planning that comprises each described tourism attack strategy project and the planning of this tour schedule temperature hot_rate (poi) to described tourism attack strategy project;
Calculate in the following manner the basic score base_score (poi) of each described tourism attack strategy project:
base_score(poi)=user_eval(poi)*b_weight1+hot_rate(poi)*b_weight2；
Wherein, b_weight1 and b_weight2 are respectively the weight of user_eval (poi) and hot_rate (poi), and b_weight1+b_weight2=1.
4. method according to claim 3 is characterized in that, obtains the user to the scoring user_eval (poi) of described tourism attack strategy project from described user's evaluating data of each described tourism attack strategy project, comprising:
From user's evaluating data of each described tourism attack strategy project, obtain each user to the initial score of described tourism attack strategy project:
All users are carried out normalized to the initial score of described tourism attack strategy project, and calculate the mean value user_direct_eval after the normalized;
Calculate the time weight time_weight of described tourism attack strategy project in described travel time section, wherein, the described time weight of same tourism attack strategy project in different time sections is not identical;
Obtain the user to the scoring user_eval (poi) of described tourism attack strategy project according to following formula:
user_eval(poi)=user_direct_eval*time_weight。
5. method according to claim 3 is characterized in that, the user comprises the temperature of described tourism attack strategy project: quote temperature and estimate temperature; According to the use acquisition of information user of the tour schedule planning that comprises each described tourism attack strategy project and the planning of this tour schedule temperature hot_rate (poi) to described tourism attack strategy project, comprising:
Step 1, for any one described tourism attack strategy project wherein, that obtains in the following manner described tourism attack strategy project quotes temperature ref_hot_rate:
The number of times that the described tourism attack strategy that records in the use information according to the tour schedule planning that comprises described tourism attack strategy project of preserving is downloaded, temperature sched_hote_rate is used in the download that obtains described tour schedule planning;
The average poi_sched_avg_rate of temperature sched_hote_rate is used in the download that calculating has comprised all tour schedules planning of described tourism attack strategy project;
The set of the tour schedule planning of relevant tourism attack strategy project and current described tourism attack strategy project has been quoted in calculating, temperature is used in download according to all tourism attack strategy projects in the described set, calculate the download of all tourism attack strategy projects in the described set and use temperature average all_sched_avg_rate, wherein, described relevant tourism attack strategy project refers to comprise other tourism attack strategy project that comprises in the tour schedule planning of current described tourism attack strategy project;
That calculates current described tourism attack strategy project quotes temperature ref_hot_rate:
ref_hot_rate=poi_sched_avg_rate/all_sched_avg_rate；
Step 2, for any one described tourism attack strategy project wherein, obtain in the following manner the evaluation temperature comment_hot_rate of described tourism attack strategy project:
From user's evaluating data of the tourism attack strategy project of pre-save, obtain the evaluation of current described tourism attack strategy project and count cmt_num[0], and cmt_num[1 is counted in the evaluation of described relevant tourism attack strategy project],, cmt_num[k], wherein k represents the quantity of described relevant tourism attack strategy project;
Calculate the general comment valence mumber of current described tourism attack strategy project and described relevant tourism attack strategy project:
Calculate the evaluation temperature comment_hot_rate=cmt_num[0 of current described tourism attack strategy project]/cmt_avg_num;
Step 3 for any one described tourism attack strategy project wherein, is calculated the user to described tourism attack strategy project
Temperature: hot_rate=(ref_hot_rate+comment_hot_rate)/N, wherein, N is preset value, and N 〉=1.
6. method according to claim 2 is characterized in that, obtains the event scoring event_score (poi) of each described tourism attack strategy project in described recommended user's travel time section, comprising:
Any one tourism attack strategy in each described tourism attack strategy project according to configuration in advance, obtains first score value corresponding to periodic event of the generation in the described travel time section from the dependent event information of described tourism attack strategy project;
Relevant information according to the real-time event that records in the described dependent event information, judge whether to exist the influential accident of described tourism attack strategy project, if have, then according to the type of emergency event that sets in advance and the corresponding relation of score value, obtain second score value corresponding with the type of described accident;
According to the first score value and described the second score value, obtain the event scoring of described tourism attack strategy project.
7. method according to claim 2 is characterized in that, in the following manner described tourism attack strategy project obtain personalized weight:
Obtain described recommended people's personality data, wherein, described individuation data comprises: the tourism attack strategy item types of described recommended people's preference and described recommended people's certain preference item;
Judge whether current described tourism attack strategy project belongs to the tourism attack strategy item types of described recommended people's preference, obtain tourism attack strategy item types preference travel_poi_perf according to judged result;
According to the corresponding relation of the certain preference item that sets in advance and certain preference item weight, obtain the certain preference item weight perf_weight[i corresponding with every certain preference item of described recommended people], wherein, i=1,2 ... n, n are the sum of described recommended people's certain preference item;
Calculate the personalized weight personal_weight that obtains of described tourism attack strategy project according to following formula:
personal_weight=travel_poi_perf*perf_weight[1]*perf_weght[2]*…*perf_weight[n]。
8. each described method in 7 according to claim 1 is characterized in that described user's evaluating data comprises: the user is to the scoring of tourism attack strategy project, user textual description information and the evaluation time to tourism attack strategy project.
9. the recommendation apparatus of attack strategy project of travelling is characterized in that, comprising:
Memory module is used for user's evaluating data of each tourism attack strategy project of storage system, dependent event information and the planning of existing tour schedule and the use information thereof of each described tourism attack strategy project;
The first acquisition module is used for obtaining the destination of recommended user's tour schedule planning, and the type of the tourism attack strategy project that need to recommend to described recommended user;
The second acquisition module, be used for obtaining from the data of memory module storage user's evaluating data, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project of each tourism attack strategy project of the described type of described destination, obtain the individuation data that from described recommended user's log-on message, obtains described recommended user;
Computing module, user's evaluating data of each the tourism attack strategy project that is used for obtaining according to described the second acquisition module, the dependent event information of each described tourism attack strategy project and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project, and in conjunction with the matching degree of each described tourism attack strategy project and described individuation data, calculate the recommendation score of each described tourism attack strategy project;
Recommending module is used for the tourism attack strategy project for every type, selects recommendation score to arrive high front n described tourism attack strategy project recommendation most to described recommended user, and wherein, n is integer, and n 〉=1.
10. device according to claim 9 is characterized in that, described computing module comprises:
The first acquiring unit, be used for obtaining the basic score base_score (poi) of each described tourism attack strategy project according to described user's evaluating data and the use information that comprises tour schedule planning and the planning of this tour schedule of each described tourism attack strategy project;
Second acquisition unit is used for the dependent event information according to each described tourism attack strategy project of preserving, and obtains the event scoring event_score (poi) of each described tourism attack strategy project in described recommended user's travel time section;
Computing unit is used for calculating according to following formula the recommendation score score (poi) of each described tourism attack strategy project:
score(poi)={base_score(poi)*weight1+event_score(poi)*weight2}*personal_weight；
Wherein,
Personal_weight is the personalized weight of described tourism attack strategy project, is used for estimating the matching degree of described tourism attack strategy project and recommended people's personality data;
Weight1 and weight2 are respectively the weight of basic score and event scoring.
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