CN112699194B - Intelligent map target prediction bubble presentation method in map scaling scene - Google Patents
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Abstract
The invention discloses an intelligent map target prediction bubble presentation method in a map scaling scene, which comprises the following steps: pre-acquiring source data information, constructing a random forest model and taking the random forest model as a prediction model; acquiring touch data of a user in the use process of a map scaling scene, and taking the touch data as input operation of a random forest model to acquire an output result; and displaying the acquired output result in the map zoom scene in the form of bubbles for clicking and selecting by a user. The method and the system improve usability of the map target selection function, reduce the threshold of searching by using the map targets of the intelligent equipment, greatly optimize use experience of users in different age groups, introduce the prediction bubbles of the intelligent map targets, reduce operation times of the users, improve interaction efficiency no matter searching single targets or continuously searching a plurality of targets, reduce switching times between a search interface and the map interface, and provide continuous and smooth interaction experience for the users.
Description
Technical Field
The invention relates to the technical field of maps, in particular to an intelligent map target prediction bubble presentation method in a map scaling scene.
Background
With the development of science and technology, many changes have been made in the map-related field, and in the interactive form of presenting a map, a computer-based electronic device is not limited to being represented on paper (or similar medium) by symbols and graphics, and can be represented on a screen through visual processing: that is, large-plane scalable map content is displayed on small-screen touch intelligent terminals (such as smartphones and smartphones, etc.). The current methods for using the mobile terminal map search targets can be divided into two categories according to the principle: the first is to use two-handed touch directly in a map scene to navigate, browse and select target points. The second type is to input the key name of the target point to select the target point indirectly through the software or the search box of the web page.
The technical problems are that: the first type of method is to map the method of searching the target on the paper map onto the intelligent device in reality, is natural and easy to get on hand, accords with subjective use operation of people, but often needs to zoom the map for many times to refer to the current map position information so as to continue the next operation, and the efficiency of searching the single target is far less than that of the other type of method.
The second type of method is suitable for knowing the key name of the target point, if the key name is not known, the target point cannot be searched by the method, and certain requirements are set on the use experience of intelligent equipment of a user; requiring the user to use the search function and be able to use at least one text input technique (e.g., pinyin input, handwriting input, voice input, etc.); and when a plurality of targets are searched continuously, the search interface and the map interface are required to be switched continuously, so that the natural interaction experience of the user is split to a certain extent.
For the problems in the related art, no effective solution has been proposed at present.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides an intelligent map target prediction bubble presentation method in a map scaling scene, so as to overcome the technical problems in the prior art.
The technical scheme of the invention is realized as follows:
an intelligent map target prediction bubble presentation method under a map scaling scene comprises the following steps:
step S1, acquiring source data information in advance, constructing a random forest model and taking the random forest model as a prediction model;
step S2, touch data of a user in the use process of the map scaling scene is obtained, and the touch data is used as input operation of a random forest model to obtain an output result;
and step S3, displaying the acquired output result in a map zoom scene in a bubble mode for clicking and selecting by a user.
Further, the step of constructing a random forest model by pre-acquiring source data information and taking the random forest model as a prediction model comprises the following steps:
map zoom scene information is obtained in advance and used as an operation scene;
collecting test information based on an operation scene, wherein the test information comprises information of collecting touch start data and information of touch end data;
repeatedly acquiring test information based on map information, and acquiring touch data existing in a map zoom scene as source data information;
the database stores and processes the acquired source data information;
a predictive model is generated based on the acquired source data information using the random forest and is used as the predictive model.
Further, the bubble is displayed in the map zoom scene in the form of a bubble, and the bubble is displayed in the form of duration.
Further, the duration is 2 to 5 seconds.
The invention has the beneficial effects that:
according to the intelligent map target prediction bubble presentation method under the map scaling scene, the random forest model is built by acquiring source data information in advance and is used as a prediction model, touch data of a user in the use process of the map scaling scene is obtained, the touch data is used as input operation of the random forest model to obtain output results, the obtained output results are displayed in the map scaling scene in a bubble mode for clicking and selecting by the user, the operation is natural, subjective use feeling of people is met, usability of map target selection functions is improved, the use experience of users using intelligent equipment map targets is reduced, the use experience of users in different age ranges is optimized to a great extent, in addition, the introduction of the intelligent map target prediction bubbles can reduce the operation times of the users, no matter searching single targets or continuously searching multiple targets can be improved, the switching times between a searching interface and the map interface can be reduced, continuous smooth interaction experience can be given to the user, and in addition, the battery endurance of the intelligent equipment is indirectly improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow diagram of a method for intelligent map target prediction bubble presentation in a map zoom scenario according to an embodiment of the present invention;
fig. 2 is a second flowchart of an intelligent map target prediction bubble presentation method in a map zoom scene according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which are derived by a person skilled in the art based on the embodiments of the invention, fall within the scope of protection of the invention.
According to the embodiment of the invention, an intelligent map target prediction bubble presentation method in a map scaling scene is provided.
As shown in fig. 1-2, the method for presenting the intelligent map target prediction bubble in the map zoom scene according to the embodiment of the invention comprises the following steps:
step S1, acquiring source data information in advance, constructing a random forest model and taking the random forest model as a prediction model;
step S2, touch data of a user in the use process of the map scaling scene is obtained, and the touch data is used as input operation of a random forest model to obtain an output result;
and step S3, displaying the acquired output result in a map zoom scene in a bubble mode for clicking and selecting by a user.
The method comprises the following steps of:
map zoom scene information is obtained in advance and used as an operation scene;
collecting test information based on an operation scene, wherein the test information comprises information of collecting touch start data and information of touch end data;
repeatedly acquiring test information based on map information, and acquiring touch data existing in a map zoom scene as source data information;
the database stores and processes the acquired source data information;
a predictive model is generated based on the acquired source data information using the random forest and is used as the predictive model.
Wherein, the steps are shown in the map zoom scene in the form of bubbles, and the bubble forms are presented for duration.
Wherein the duration is 2-5 seconds.
By means of the scheme, the random forest model is built by acquiring the source data information in advance and is used as the prediction model, touch data of a user in the use process of the map scaling scene is obtained, the touch data is used as input operation of the random forest model to obtain output results, the obtained output results are displayed in the map scaling scene in the form of bubbles for clicking and selecting by the user, the operation is natural, subjective use feeling of people is met, usability of map type target selection functions is improved, the threshold of map target searching of intelligent equipment is reduced for the user, use experience of users in different age groups is optimized to a great extent, in addition, the introduction of the intelligent map target prediction bubbles can reduce operation times of the user, interaction efficiency can be improved no matter searching single targets or continuously searching multiple targets is carried out, switching times between a searching interface and a map interface can be reduced, continuous smooth interaction experience can be given to the user, and in addition, battery endurance capacity of the intelligent equipment is indirectly improved.
In addition, specifically, the tester uses the mobile phone map page according to the habit of holding the mobile phone in normal times, taking the first pair of urban points 'Beijing-Tianjin' as an example. The center point of the map initial interface is Beijing, and after a tester clicks Beijing for the first time, the HammerJS library starts recording touch data. And then the user continues to slide towards the southeast direction of the map to search for Tianjin, and the Tianjin area begins to appear on the screen, so that the user can directly click and select Tianjin. At the same time, the HammerJS library finishes collecting touch data, and we store this part of data first. The data collected by HammerJS is shown in table 1:
table 1 HammerJS triggered event object
In addition, the tester continues to complete experiments on city pairs such as "Tianjin-Wuhan" and the like, and the data is similarly stored. Data information between which city pairs is needed, a corresponding basic experiment is completed first, and the data is stored. Our obtained data was processed using the Numpy, pandas library in Python, and then random forests were used to generate predictive models of this process. The input to this model is touch data with information of the first city of the city pair (the starting city) and the output is the second city of the city pair (the ending city). The model we generate is combined with the map page function. When a user starts to use the map to select a target city, the model can acquire touch data of the user in the use process, meanwhile, the data can be used as input operation of the model to acquire an output result, and the input result is displayed in a page in a bubble mode for the user to click and select. If the location in the bubble is the target which the user wants to select, the user can directly click the bubble to directly reach the target point in the process of searching the target, part of the searching sliding process is skipped, and the efficiency of selecting the target is improved; if the location in the bubble is not the target the user wants to select, the user can ignore the bubble and continue to slide the map to select the target, meanwhile, the duration of the bubble is 2 seconds, and after the duration is finished, the bubble disappears. After a plurality of users use the model in a large quantity, the model can be updated according to new user data, and the setting model of the bubble city point is optimized, so that the model is more intelligent.
In summary, by means of the technical scheme, the random forest model is built by acquiring the source data information in advance and is used as the prediction model, touch data of a user in the use process of the map scaling scene is obtained, the touch data is used as input operation of the random forest model to obtain output results, the obtained output results are displayed in the map scaling scene in a bubble mode for clicking and selecting by the user, the operation is natural, subjective use feeling of people is met, usability of map class target selection functions is improved, the threshold of map target searching of the user using intelligent equipment is reduced, use experience of the user in different age groups is optimized to a great extent, in addition, the introduction of the intelligent map target prediction bubbles can reduce the operation times of the user, no matter searching single target or searching multiple targets continuously, interactive efficiency can be improved, switching times between a searching interface and the map interface can be reduced, continuous smooth interactive experience can be given to the user, and in addition, battery endurance of the intelligent equipment is indirectly improved.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (1)
1. The intelligent map target prediction bubble presentation method in the map scaling scene is characterized by comprising the following steps of:
pre-acquiring source data information, constructing a random forest model and taking the random forest model as a prediction model;
acquiring touch data of a user in the use process of a map scaling scene, and taking the touch data as input operation of a random forest model to acquire an output result;
displaying the obtained output result in a map scaling scene in a bubble mode for clicking and selecting by a user;
wherein: the step of pre-acquiring source data information to build a random forest model and serve as a prediction model comprises the following steps:
map zoom scene information is obtained in advance and used as an operation scene;
collecting test information based on an operation scene, wherein the test information comprises information of collecting touch start data and information of touch end data;
repeatedly acquiring test information based on map information, and acquiring touch data existing in a map zoom scene as source data information;
the database stores and processes the acquired source data information;
generating a prediction model by using a random forest based on the acquired source data information and taking the prediction model as the prediction model;
the touch data is: after clicking the center point for the first time by using the center point of the initial interface of the map, the HammerJS library starts to finish from recording, and the HammerJS triggered event object data comprises: the name of the event, the touch points of all new/moved/lost, the movement angle, the center position of the multi-touch, the movement time, the movement direction, the movement distance, the event type, the last input value true, the first input value true, the maximum number of touch points, the movement direction relative to the starting point, the overall speed, and the maximum movement speed on the X axis and the Y axis when the multi-touch is scaled, but the touch value is 1;
the step of displaying the map zoom scene in the form of bubbles, wherein the bubble forms are presented for duration;
the duration is 2 to 5 seconds.
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| JP2006053132A (en) * | 2004-07-13 | 2006-02-23 | Matsushita Electric Ind Co Ltd | Moving destination display, and moving destination display method |
| CN104964693A (en) * | 2014-03-03 | 2015-10-07 | 苹果公司 | Map application with improved navigation tools |
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