CN112699194A - Intelligent map target prediction bubble presenting method under map zooming scene - Google Patents
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Abstract
The invention discloses an intelligent map target prediction bubble presenting method in a map zooming scene, which comprises the following steps: pre-acquiring source data information to build a random forest model and using the random forest model as a prediction model; obtaining touch data of a user in the use process of a map zooming scene, and using the touch data as input operation of a random forest model to obtain an output result; and displaying the obtained output result in a map zooming scene in a bubble form for a user to click and select. The method and the device improve the usability of the map type target selection function, reduce the threshold of searching the map target by using intelligent equipment by a user, greatly optimize the use experience of the users in different age groups, reduce the operation times of the user by introducing the intelligent map target prediction bubbles, improve the interaction efficiency no matter a single target is searched or a plurality of targets are searched continuously, reduce the switching times between the search interface and the map interface, and give continuous and smooth interaction experience to the user.
Description
Technical Field
The invention relates to the technical field of maps, in particular to an intelligent map target prediction bubble presenting method in a map zooming scene.
Background
With the development of scientific technology, many changes have occurred in the field related to maps, and computer-based electronic devices are no longer limited to the interactive form of presenting maps, represented by symbols and graphics on paper (or similar medium), but can be represented on a screen through visual processing: namely, large-plane scalable map content is displayed on a small-screen touch intelligent terminal (such as a smart phone, a smart tablet computer and the like). The existing application methods of mobile terminal map search targets can be divided into two types according to the principle: the first category is to use two-handed touch to navigate, browse, and select a target point directly in a map scene. The second type is to indirectly input the key name of the target point through a search box of software or a webpage to select the target point.
The existing technical problems are as follows: the first method is to map the method for searching the target on the paper map to the intelligent device, which is naturally easy to use and relatively accords with the subjective operation of people, but the map is often required to be zoomed for many times to refer to the current map position information so as to continue the next operation, and the efficiency of searching a single target is far lower than that of the other method.
The second 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 provided for the use experience of the intelligent equipment of the user; requiring the user to use search functionality and be able to use at least one text input technique (e.g., pinyin input, handwriting input, voice input, etc.); when a plurality of targets are searched continuously, the search interface and the map interface need to be switched continuously, and natural interactive experience of the user is split to a certain extent.
An effective solution to the problems in the related art has not been proposed yet.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides an intelligent map target prediction bubble presenting method in a map zooming scene, so as to overcome the technical problems in the prior related art.
The technical scheme of the invention is realized as follows:
an intelligent map target prediction bubble presenting method under a map zooming scene comprises the following steps:
step S1, acquiring source data information in advance to build a random forest model and using the random forest model as a prediction model;
step S2, touch data of a user in the use process of a map zooming 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 the map zooming scene in a bubble form for the user to click and select.
Further, the step of obtaining source data information in advance to build a random forest model and using the random forest model as a prediction model comprises the following steps:
obtaining map zooming scene information in advance and using the map zooming scene information as an operation scene;
acquiring test information based on an operation scene, wherein the test information comprises acquisition starting touch data information and acquisition ending touch data information;
repeatedly acquiring test information based on the map information, and acquiring touch data existing in a map zooming scene as source data information;
the database stores and processes the acquired source data information;
and generating a prediction model based on the acquired source data information by using a random forest and using the prediction model as the prediction model.
Further, the step of presenting in the map zoom scene in the form of bubbles, the bubbles being in the form of a duration presentation.
Further, the duration is 2-5 seconds.
The invention has the beneficial effects that:
the invention relates to a method for presenting intelligent map target prediction bubbles in a map zooming scene, which comprises the steps of constructing a random forest model by pre-obtaining source data information and using the random forest model as a prediction model, obtaining touch data of a user in the use process of the map zooming scene, using the touch data as the input operation of the random forest model to obtain an output result, displaying the obtained output result in the map zooming scene in the form of bubbles for the user to click and select, realizing natural operation and meeting the subjective use feeling of people, improving the usability of a map type target selection function, reducing the threshold of the user for searching the map target by using intelligent equipment, greatly optimizing the use experience of the users in different age groups, introducing the intelligent map target prediction bubbles, reducing the operation times of the user, and improving the interaction efficiency no matter whether the user searches a single target or continuously searches a plurality of targets, the switching frequency between the search interface and the map interface is reduced, continuous and smooth interactive experience can be given to a user, and the battery endurance of the intelligent device 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 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 it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a first flowchart illustrating a method for presenting an intelligent map target prediction bubble in a map zooming scene according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a second method for presenting an intelligent map target prediction bubble in a map zooming scene according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present invention.
According to the embodiment of the invention, an intelligent map target prediction bubble presenting method in a map zooming scene is provided.
As shown in fig. 1-2, the method for presenting the intelligent map target prediction bubble in the map zooming scene according to the embodiment of the present invention includes the following steps:
step S1, acquiring source data information in advance to build a random forest model and using the random forest model as a prediction model;
step S2, touch data of a user in the use process of a map zooming 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 the map zooming scene in a bubble form for the user to click and select.
The method comprises the following steps of pre-acquiring source data information, constructing a random forest model and using the random forest model as a prediction model, and comprises the following steps:
obtaining map zooming scene information in advance and using the map zooming scene information as an operation scene;
acquiring test information based on an operation scene, wherein the test information comprises acquisition starting touch data information and acquisition ending touch data information;
repeatedly acquiring test information based on the map information, and acquiring touch data existing in a map zooming scene as source data information;
the database stores and processes the acquired source data information;
and generating a prediction model based on the acquired source data information by using a random forest and using the prediction model as the prediction model.
Wherein the step of displaying in the map zoom scene in the form of bubbles, the form of bubbles being a duration presentation.
Wherein the duration is 2-5 seconds.
By means of the scheme, a 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 a map zooming scene is acquired, the touch data is used as input operation of the random forest model to acquire an output result, the acquired output result is displayed in the map zooming scene in a bubble mode to be clicked and selected by the user, natural operation is achieved, the subjective use feeling of the user is met, the usability of a map type target selection function is improved, the threshold of searching the map target by the user using intelligent equipment is reduced, the use experience of the user in different age groups is optimized to the greatest extent, the introduction of intelligent map target prediction bubbles can reduce the operation times of the user, the interaction efficiency can be improved no matter a single target is searched or a plurality of targets are searched continuously, and the switching times between a search interface and a map interface are reduced, can give the continuous smooth interactive experience of user, indirectly promote smart machine's battery duration in addition.
In addition, specifically, the tester uses the map page of the mobile phone according to the habit of holding the mobile phone at ordinary times, taking the first city point of "beijing-tianjin" as an example. The central point of the map initial interface is Beijing, and after a tester clicks the 'Beijing' for the first time, the HammerJS library starts to record touch data. 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. Meanwhile, the HammerJS library finishes collecting touch data, and we store the data. The data collected by HammerJS is shown in table 1:
TABLE 1 HammerJS triggered event object
In addition, the tester proceeds to perform experiments on city pairs such as "Tianjin-Wuhan" and similarly stores these data. And completing corresponding basic experiments first when data information between the city pairs is needed, and storing the data. The data we obtained was processed using the Numpy, Pandas library in Python, and then a random forest was used to generate a predictive model of this process. The input to this model is touch data with information for the first city of the city pair (the start city) and the output is the second city of the city pair (the end city). The model we generated is combined with the map page functionality. When a user starts to use the map to select a target city, the model can obtain touch data of the user in the using process, meanwhile, the data can be used as input of the model to operate to obtain 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 place 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, and part of the search sliding process is skipped, so that the target selecting efficiency is improved; if the position in the bubble is not the target which 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 over, 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 above technical scheme of the present invention, a random forest model is built by obtaining source data information in advance and is used as a prediction model, touch data of a user in a map zooming scene is obtained, the touch data is used as input operation of the random forest model to obtain an output result, the obtained output result is displayed in the map zooming scene in a bubble form for the user to click and select, the operation is natural, the subjective use feeling of the user is met, not only is the usability of a map type target selection function improved, the threshold of the user for searching the map target by using an intelligent device reduced, the use experience of the users in different age groups is optimized to a great extent, but also the introduction of the intelligent map target prediction bubble can reduce the operation times of the user, and the interaction efficiency can be improved no matter a single target is searched or a plurality of targets are continuously searched, the switching frequency between the search interface and the map interface is reduced, continuous and smooth interactive experience can be given to a user, and the battery endurance of the intelligent device is indirectly improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (4)
1. An intelligent map target prediction bubble presenting method under a map zooming scene is characterized by comprising the following steps:
pre-acquiring source data information to build a random forest model and using the random forest model as a prediction model;
obtaining touch data of a user in the use process of a map zooming scene, and using the touch data as input operation of a random forest model to obtain an output result;
and displaying the obtained output result in a map zooming scene in a bubble form for a user to click and select.
2. The method for presenting the intelligent map target prediction bubbles in the map zooming scene as claimed in claim 1, wherein the step of pre-acquiring the source data information to build a random forest model and using the random forest model as a prediction model comprises the following steps:
obtaining map zooming scene information in advance and using the map zooming scene information as an operation scene;
acquiring test information based on an operation scene, wherein the test information comprises acquisition starting touch data information and acquisition ending touch data information;
repeatedly acquiring test information based on the map information, and acquiring touch data existing in a map zooming scene as source data information;
the database stores and processes the acquired source data information;
and generating a prediction model based on the acquired source data information by using a random forest and using the prediction model as the prediction model.
3. The method as claimed in claim 1, wherein the step of displaying the bubble in the map zoom scene in the form of bubble, which is in the form of duration presentation, is performed.
4. The method for presenting the intelligent map target prediction bubbles in the map zooming scene according to claim 3, wherein the duration is 2-5 seconds.
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