CN112380414A - User portrait acquisition method and acquisition device - Google Patents
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Abstract
The invention discloses a user portrait acquisition method, which comprises the steps of acquiring attribute factors of a traveler, determining travel activity types of the traveler, determining influence factors obviously influencing each travel activity type based on the attribute factors, determining key factors influencing travel activities of the traveler by utilizing an inter-class inspection mode, generating a user portrait based on the key factors and the like, and can provide personalized information service for a client according to the attribute factors of the user such as gender, occupation, age, education degree, income, private car and common traffic modes and comprehensively considering the actual requirements of the user on different travel activities, thereby being beneficial to improving the service experience of the traveler.
Description
Technical Field
The invention relates to the technical field of intelligent traffic, in particular to a user portrait acquisition method and device.
Background
Maas (mobility as a service) has become a hotspot of traffic research and social attention in recent years. Reliability of travel information service is one of the main factors affecting service experience of travelers, and unreliable travel information can cause failure or inefficiency of trip plans of travelers.
Currently, a public-oriented travel information service (public-based service mode) provided by travel software represented by a Baidu and Gaodde map stays at a travel decision basis level, provided information contents comprise a travel mode, a travel path and travel time, an expected arrival time factor of a traveler is not considered, a departure time directly required by the traveler is not provided, the traveler still needs to make a self-decision on the departure time according to the expected arrival time, and when a decision of the departure time of the traveler has a large error, the travel reliability and the travel efficiency of the traveler are difficult to guarantee; in addition, the difference demand analysis of traffic trip information service using objects is lacked in the current trip information service system, and the difference of reserved time length demands of different travelers under different trip activity demands is not considered, so that the service experience of the travelers is influenced.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a user portrait acquisition method and device for intelligent transportation, which not only consider the expected arrival time factor of travelers, but also consider the difference of the reserved time requirements of different travelers under different travel activity requirements, and obviously improve the service experience of the travelers.
The technical scheme adopted by the invention specifically comprises the following contents:
a user image acquisition method for intelligent transportation comprises the following steps:
acquiring attribute factors of a traveler;
determining the type of the travel activity of the traveler;
determining influence factors which obviously influence each type of travel activities based on the attribute factors;
determining key factors influencing the trip activities of travelers by utilizing an inter-class inspection mode;
a user representation is generated based on the key factors.
Preferably, the type of the travel activity of the traveler is determined according to the expected reserved time length of the traveler for the travel activity.
Preferably, the attribute factors include sex, occupation, age, education level, income, presence or absence of private cars and general transportation of the traveler.
Preferably, the travel activity types include a high-arrival-ahead-of-time demand travel activity, a low-arrival-ahead-of-time demand travel activity and a no-arrival-ahead-of-time demand travel activity.
Preferably, the high-early-arrival-demand travel activities include train taking activities and airplane taking activities; the low-early-arrival-demand travel activities include daily commuting activities and movie watching activities; the no-advance-arrival-demand travel activities include general leisure activities.
Preferably, based on the attribute factors, the determining of the influence factors which significantly influence each type of the travel activities is the determining of the significant influence factors of each type of the travel activities by means of chi-square test.
The invention also provides a device for acquiring the user portrait, which comprises an acquiring unit, a first determining unit, a second determining unit, a verifying unit and a generating unit, wherein the acquiring unit is used for acquiring attribute factors of a traveler; the first determining unit is used for determining the type of the travel activity of the traveler; the second determining unit determines influence factors which significantly influence each type of travel activity based on the attribute factors, the verifying unit is used for determining key factors which influence travel activities of travelers by means of inter-class inspection, and the generating unit generates the user portrait based on the key factors.
Compared with the prior art, the invention has the beneficial effects that:
a method for obtaining a user portrait comprises the steps of obtaining attribute factors of a traveler, determining travel activity types of the traveler, determining influence factors which obviously influence each travel activity type based on the attribute factors, determining key factors which influence travel activities of the traveler by utilizing an inter-class inspection mode, generating the user portrait based on the key factors and the like, wherein personalized information service is provided for a client according to the attribute factors of gender, occupation, age, education degree, income, private car and common transportation modes of the user and the actual requirements of the user on different travel activities are comprehensively considered, and service experience of the traveler is improved.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
FIG. 1 is a schematic flow chart of a user image acquisition method according to the present invention;
FIG. 2 is a cumulative frequency distribution graph of expected durations of different travel activities;
FIG. 3 is a user representation of a travel activity type when traveling in a train;
FIG. 4 is a schematic structural diagram of a device for acquiring a user image according to the present invention;
wherein the reference numerals in fig. 4 are:
1. an acquisition unit; 2. a first determination unit; 3. a second determination unit; 4. a verification unit; 5. and a generating unit.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description of the embodiments, structures, features and effects according to the present invention with reference to the accompanying drawings and preferred embodiments is as follows:
as shown in FIG. 1, the present invention discloses a method for obtaining a user portrait, comprising:
acquiring attribute factors of a traveler;
determining the type of the travel activity of the traveler;
determining influence factors which obviously influence each type of travel activities based on the attribute factors;
determining key factors influencing the trip activities of travelers by utilizing an inter-class inspection mode;
a user representation is generated based on the key factors.
In the present invention, the user profile refers to a travel user category divided according to a travel activity type and a personal attribute.
As a further preferred scheme, the determined travel activity type of the traveler is determined according to an expected reserved time length of the traveler for the travel activity.
As a further preferable aspect, the attribute factors include sex, occupation, age, education level, income, presence or absence of private cars, and common transportation means of a traveler.
As a further preferable scheme, the travel activity types include a high-arrival-ahead-of-time demand travel activity, a low-arrival-ahead-of-time demand travel activity, and a no-arrival-ahead-of-time demand travel activity.
As a further preferred aspect, the high-early-arrival-demand travel activities include train riding activities and airplane riding activities; the low-early-arrival-demand travel activities include daily commuting activities and movie watching activities; the no-advance-arrival-demand travel activities include general leisure activities.
As a further preferable scheme, based on the attribute factors, determining the influence factors that significantly influence each type of travel activity is to determine the significant influence factors of each type of travel activity by means of chi-square test.
As shown in fig. 4, the present invention further provides an apparatus for obtaining a user portrait, comprising an obtaining unit 1, a first determining unit 2, a second determining unit 3, a verifying unit 4 and a generating unit 5, wherein the obtaining unit 1 is used for obtaining attribute factors of a traveler; the first determining unit 2 is configured to determine a type of travel activity of a traveler; the second determining unit 3 determines influencing factors which significantly influence each type of travel activity based on attribute factors, the verifying unit 4 is used for determining key factors which influence travel activities of travelers by means of inter-class inspection, and the generating unit 5 is used for generating user portraits based on the key factors.
Specific examples are as follows.
A method for obtaining a user portrait comprises the following steps:
(1) the method comprises the steps of obtaining attribute factors of travelers, specifically, taking a certain number and range of travelers as an example, determining the attribute factors of the travelers by adopting a questionnaire survey mode, wherein the attribute factors comprise sex, occupation, age, education level, income, private car and common traffic mode of the travelers, and classification methods and statistical results of different attributes are respectively shown in table 1 and table 2.
TABLE 1
TABLE 2
(2) Determining travel activity types of a traveler, specifically, the travel activity types include high-early-arrival-demand travel activity, low-early-arrival-demand travel activity and no-early-arrival-demand travel activity.
More specifically, the high-early-arrival-demand travel activities include train taking activities and airplane taking activities, and since the departure times of trains and airplanes are strictly limited, when a traveler is late, the traveler may face a large loss, so that the traveler is sensitive to the time of the type of activities, strict attitude can be kept in travel time arrangement, and meanwhile, due to the existence of cumbersome procedures such as ticket checking, a great amount of time needs to be reserved for the type of activities by the traveler according to related experiences to ensure travel reliability; the low-advance-arrival-demand travel activities comprise daily commuting activities such as work attendance, school attendance and the like and movie watching activities, and the activities are sensitive to time; the travel activities without the requirement of reaching in advance comprise general leisure activities, and for the activities of the type, a traveler only needs to refer to the planned arrival time of the traveler without considering whether the traveler will arrive late, the reserved time length can be flexibly regulated and controlled according to the own time arrangement, and the specific result is shown in fig. 2.
(3) And determining influence factors which obviously influence each type of the travel activities based on the attribute factors, and specifically determining the influence factors which obviously influence each type of the travel activities by using a chi-square test mode.
For different types of travel activities, when the p-value is less than 0.05, the attribute factor is considered as an influence factor which obviously influences each type of travel activities, and specifically, the influence factors which obviously influence train taking activities comprise occupation, age, academic calendar and common transportation mode; influence factors which obviously influence the activities of taking the plane comprise occupation, age and common traffic modes; the influence factors which obviously influence the daily commuting activities comprise occupation, age, income, the presence or absence of private cars and common traffic modes; influencing factors which obviously influence the movie watching activities comprise sex, occupation and school calendar; the influencing factors which obviously influence the general leisure activities comprise sex, occupation and common transportation modes, and the p-value values of different attribute factors are shown in the table 3 aiming at each travel activity.
TABLE 3
(4) The key factors influencing the trip activities of travelers are determined by utilizing an inter-class inspection mode, specifically, as the dividing methods of the same attribute factor in different trip activities are different, in order to know the difference of the same influence factor in different trip activities, taking the influence factor of occupation as an example, a man-hutney inspection method is adopted to perform difference analysis on different values of occupation in different trip activities, and the result is shown in table 4.
TABLE 4
Taking a train as an example, occupation 1 and occupation 2 have no significant difference, and occupation 3 and occupation 4 have no significant difference, but occupation 1 and occupation 2 have significant difference with occupation 3 and occupation 4, so that the traveler can be divided into two categories, occupation 1 and 2 and occupation 3 and 4 according to the 'occupation' attribute for taking the train as the type of travel activity.
(5) The user portrait is generated based on key factors, specifically, taking a train riding scene as an example, influence factors which obviously influence train riding activities include occupation, age, academic history and common traffic modes, difference tests among different types of travel activities are carried out on the four influence factors, and results show that: the influence of common transportation modes on different types of travel activities is not obviously different, two types of travelers of fixed occupation time (full-time employees and students) and elastic time (part-time employees and retirees) show obvious difference, the school calendar takes the high school as a demarcation point, three types of travelers below the high school, the high school and the high school show obvious difference, and two types of travelers of aged middle-aged and old people (60 years and above) and non-aged people (60 years and below) show obvious difference; then, the optimized classification levels are freely combined to obtain user images in a scene of riding a train, 12 groups (2 × 3 — 12) are provided, wherein 3 groups of logic conflict images exist, and 3 groups of images are 3 images of people over 60 years old and people with fixed working time, because most people over 60 years old are retired people (the highest statutory age, male is over 60 years old, female is over 55 years old), and 9 groups of user images can be obtained after being eliminated, as shown in fig. 3 specifically.
The above embodiments are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby, and any insubstantial changes and substitutions made by those skilled in the art based on the present invention are within the protection scope of the present invention.
Claims (7)
1. A method for obtaining a user representation, comprising:
acquiring attribute factors of a traveler;
determining the type of the travel activity of the traveler;
determining influence factors which obviously influence each type of travel activities based on the attribute factors;
determining key factors influencing the trip activities of travelers by utilizing an inter-class inspection mode;
a user representation is generated based on the key factors.
2. The user representation acquisition method of claim 1, wherein determining the type of travel activity of the traveler is determined based on a desired reserved duration of travel activity of the traveler.
3. The user representation acquisition method of claim 1, wherein the attribute factors include gender, occupation, age, education level, income, presence or absence of private cars, and general transportation.
4. The user representation acquisition method of claim 3, wherein the types of travel activities include high-reach-ahead demand travel activities, low-reach-ahead demand travel activities, and no-reach-ahead demand travel activities.
5. The user representation acquisition method of claim 4, wherein the high advance arrival demand travel activities include train and airplane activities; the low-early-arrival-demand travel activities include daily commuting activities and movie watching activities; the no-advance-arrival-demand travel activities include general leisure activities.
6. The user representation acquisition method of claim 1, wherein determining the influencing factors that significantly influence each type of travel activity based on the attribute factors is determining the influencing factors for each type of travel activity using chi-square test.
7. The user portrait acquisition device is characterized by comprising an acquisition unit, a first determination unit, a second determination unit, a verification unit and a generation unit, wherein the acquisition unit is used for acquiring attribute factors of a traveler; the first determining unit is used for determining the type of the travel activity of the traveler; the second determining unit determines significant influence factors which significantly influence each type of travel activity based on the attribute factors, the verifying unit is used for determining key factors which influence travel activities of travelers by means of inter-class inspection, and the generating unit generates the user portrait based on the key factors.
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Citations (5)
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- 2020-11-16 CN CN202011279714.2A patent/CN112380414A/en active Pending
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| KR20060072633A (en) * | 2004-12-23 | 2006-06-28 | 포스데이타 주식회사 | System and method for transportation forecast service using the wireless internet |
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| CN107277103A (en) * | 2017-04-27 | 2017-10-20 | 华晓燕 | It is a kind of based on the commuting service system accurately pushed and implementation method |
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