TWI515687B - Automatic travel planning system and its method - Google Patents

Description

Automatic trip planning system and method thereof

The present invention relates to an automatic trip planning system and method thereof, and more particularly to an automatic trip planning system and method for automatically discharging a suitable travel planning trip via information and grouping methods such as historical interest point groups.

At present, most of the conventional tourism planning systems or methods mainly focus on providing various types of tourism materials, providing users with more convenient tools to arrange the order of their travels, but users still need to manually sort the attractions. Have a sequence of play; or focus on providing information that can be modified by the navigation device to flexibly change the itinerary and calculation time and cost information, and to correct the itinerary planning information by instant positioning and calculation, but still can not provide a variety of automatically generated itinerary planning information for User selection, users still have to spend a lot of energy and time to arrange and adjust the order of play.

Based on the above limitations of the prior art, the present invention proposes a system and method for automatically generating a plurality of itinerary planning results, so that the user can adopt the planned completion according to his/her own needs without additional effort and time. Recommended itinerary.

In view of the above-mentioned problems of the prior art, the object of the present invention is to provide an automatic trip planning system and a method thereof, so that the user only needs to select a plurality of scenic spots to be played, and the system will refer to information such as historical interest point groups. And the grouping method automatically discharges the more suitable scenic spots for the user's reference, so as to achieve the effect of focusing on the play in the area, avoiding spending extra time and energy before the user's trip, in the order of visiting the sights, and avoiding unnecessary time. And energy in unnecessary journeys.

In accordance with the purpose of the present invention, an automatic trip planning system is provided, comprising: a service host for receiving a plurality of points of interest transmitted by a network-connected device; And analyze and calculate one of the trip planning information back to the device with network function; a trip group analysis server analyzes and counts the plurality of points of interest information according to the plurality of itinerary planning historical information. And grouping the plurality of points of interest information; and a trip planning server, configured to receive the plurality of points of interest information by the group, and plan the plurality of points of interest information according to the information of the points of interest to generate Itinerary planning information, and the travel planning information is transmitted to the service host to transmit the travel planning information to the networked device through the service host. Among them, the information about the points of interest includes maps, traffic, weather and other information.

Preferably, the automatic trip planning system of the present invention further includes a trip planning history database for storing a plurality of trip planning history information.

Preferably, the automatic travel planning system of the present invention further comprises a comprehensive information database for storing information related to the interest points.

Preferably, the trip group analysis server analyzes and counts the plurality of points of interest information according to the plurality of trip planning history information, and uses a grouping parameter (eg, "one day") as The benchmark performs one grouping to generate at least one time group, and the trip planning server generates the trip planning information according to each group, and when the trip planning server determines that the number of playing hours of the points of interest in the group exceeds a preset When the number of hours (such as eight hours of scheduled play time is eight hours, the predetermined number of hours is eight hours), the analysis and recursive calculation of the group algorithm will be based on the secondary grouping parameters (like the group). The geographical points of the group's points of interest are sub-grouped, and then the points of interest of the second group are planned according to the information of the points of interest to adjust the travel planning information.

Preferably, the trip group analysis server further comprises a point of interest information receiving module for receiving a plurality of points of interest information transmitted by the service host; and a historical itinerary information analyzing module for planning a plurality of itinerary history The information is analyzed and statistically, and the historical information of each trip planning is classified and marked; and the clustering module is used to analyze the plurality of interest point information according to the analyzed plurality of trip planning historical information. Grouping parameters are grouped to generate a group.

Preferably, the trip planning server includes a point of interest group information receiving module for receiving a plurality of points of interest information of a group that has been grouped once; and a trip planning related auxiliary information receiving module for receiving interest Point related information; a trip planning module for Interest point related information is planned for a plurality of interest point information of a group to generate travel planning information, and the trip planning module is further used to determine whether the accumulated play time of the interest points in the group exceeds the preset hours And one or two sub-grouping modules, when the trip planning module determines that the accumulated play time of the interest points in the group exceeds the preset number of hours, the secondary clustering module is used to analyze the clustering algorithm according to the clustering algorithm. The recursive calculation divides the interest points of a group according to the secondary grouping parameters (such as geographical location) for secondary grouping, and then adjusts the itinerary planning information by the trip planning module.

According to the purpose of the present invention, an automatic trip planning method is further provided, which comprises the steps of: receiving, by a service host, a plurality of points of interest information transmitted by a network-connected device; A plurality of itinerary planning historical information is analyzed and statistic to group a plurality of interest point information; and a plurality of interest point information is received by a trip planning server, and the plurality of points of interest are grouped according to a point of interest information The information of interest points is planned to generate travel planning information, and the travel planning information is transmitted to the service host to transmit the travel planning information to the networked device through the service host. Among them, the information about the points of interest includes maps, traffic, weather and other information.

As described above, the automatic trip planning system and method thereof according to the present invention have one or more of the following advantages:

1. The present invention intelligently inputs the plurals input by the user by analyzing and establishing the historical interest point group information and the opening and suggesting play time, traffic, map and weather information of each interest point in advance in the database. The points of interest are divided into different groups, and the points of interest in each group show that most users will play them in the same period (such as: one day), and these historical points of interest group information follow-up It will be used by the trip planning module to assist in automatically generating travel itinerary results as a travel reference for users.

2. If there is no historical interest point group information, the present invention can also automatically divide the interest points into several clusters (cluster, ie, the secondary grouping as described above) through the grouping method (K-means) technology, so that each The geographical similarity between the points of interest in the cluster is higher than the similarity of the points of interest in other clusters, thus ensuring that users can spend less travel time and distance if they travel to and from each cluster. The subsequent follow-up of these cluster information will also be used by the trip planning module to assist in automatically generating travel itineraries.

3. The invention can also be combined with the adoption of "the shortest distance", "the least time", "fees" With the lowest parameters and other factors, the daily optimization of the itinerary and the combined optimization of the overall optimization of the travel according to individual needs, the user can finally get a variety of travel itinerary automatically generated by the system.

100‧‧‧Devices with networking capabilities

102‧‧‧Base station

103‧‧‧Multiple points of interest information

104‧‧‧Internet

105‧‧‧Service Host

107‧‧‧Travel Planning History Database

108‧‧‧Travel planning history information

109‧‧‧Travel Group Analysis Server

110‧‧‧ Points of interest after grouping

111‧‧‧Comprehensive information database

112‧‧‧Information on interest points

113‧‧‧Travel Planning Server

114‧‧‧Travel planning information

200‧‧‧Automatic Travel Planning System

21‧‧‧Point of Interest Information Receiver Module

22‧‧‧Historical Information Analysis Module

23‧‧‧One time grouping module

31‧‧‧Point of Interest Group Information Receiver Module

32‧‧‧Travel planning related auxiliary information receiving module

33‧‧‧Secondary grouping module

34‧‧‧Travel Planning Module

S1~S4‧‧‧ steps

Figure 1 is a schematic diagram of the architecture of the present invention.

Figure 2 is a schematic diagram of an embodiment of a trip group analysis server of the present invention.

Figure 3 is a schematic diagram of an embodiment of a trip planning server of the present invention.

Figures 4(a) through 4(d) are schematic diagrams of the embodiment of the K-means clustering algorithm.

Figure 5 is a flow chart of the automatic travel planning method of the present invention.

The technical features, contents, and advantages of the present invention, as well as the advantages thereof, can be understood by the present inventors, and the present invention will be described in detail with reference to the accompanying drawings. The subject matter is only for the purpose of illustration and description. It is not intended to be a true proportion and precise configuration after the implementation of the present invention. Therefore, the scope and configuration relationship of the attached drawings should not be interpreted or limited. First described.

In order to achieve the object of the present invention, the automatic travel planning system and method thereof can use the user history travel planning experience to perform a group analysis of interest points, and return the final travel planning information to the user so that the user can follow the preferences and The demand was then adjusted flexibly, and finally the travel itinerary was successfully completed. Users can connect to this automatic trip planning system through networked devices (such as smart phones, PDAs or tablets, laptops and desktops). The automatic trip planning system uses the trip group analysis server and The trip planning server provides the user with a pre-arranged trip service.

The user can connect to the automatic travel planning system via the Internet through a device with a network connection. After browsing the introduction and description of the attraction, the user can add and store the points of interest to be included in the itinerary. The service host of the system will transmit a plurality of points of interest information to the trip group analysis server and the trip planning server for automatic scheduling.

The trip group analysis server includes three modules, namely, a point of interest information receiving module, a historical itinerary information analyzing module, and a grouping module; the main function of the historical itinerary information analyzing module is to periodically view the travel planning history information, Sort out the history of each trip plan Information and tagging, for example: analyzing the most frequently used points of interest on the same day and categorizing them to be stored as multiple "same day points collections" and recording their order of play. When the interest point information receiving module receives the plurality of points of interest information input by the user, the grouping module divides the plurality of points of interest information into different groups by using the "same day point of interest collection" information. The order of the points in each group is the point that the system suggests to play on the same day. In order to avoid too few or too many points of interest in the same group, or if there is an unreasonable time of travel, it needs to be transferred to the itinerary planning server for further processing.

The trip planning server mainly includes four modules, which are a point group information receiving module, a trip planning related auxiliary information receiving module, a trip planning module, and a secondary grouping module. After the interest point group information receiving module receives the plurality of interest point primary group information transmitted by the travel group analysis server, the travel planning module checks one by one whether the order of interest points in each group is consistent. Suggested play time points (morning, afternoon, evening), and the cumulative play time in each group is not greater than the daily reasonable play time; this analysis is based on the opening and recommended play time of each interest point, and The local traffic and road condition information and weather information received by the auxiliary information receiving module related to the itinerary planning are used as reference. If the accumulated play time in a single group is too large, the transfer to the secondary cluster module is performed in groups of eight to ten hours for secondary grouping; if the accumulated play time in the secondary group is too small, then The analysis is performed to select other suitable one or two groups for merging. At the same time, you can also add the parameters such as "the shortest distance", "the least time" and "the lowest cost" to generate the daily optimized itinerary and the combined optimization of the overall optimization according to individual needs.

If the user temporarily changes the itinerary during the game, he can also connect to the service host for immediate trip planning, and the system will retain the travel plan of all users to continuously update the historical group record. At the same time, the trip plan that is passed back to the user includes not only the daily interest point play sequence and the recommended play time, but also other life information such as traffic and weather; and the user can make a travel comprehension or feedback after the play.

Please refer to FIG. 1 , which is a schematic diagram of the architecture of the present invention. The figure mainly includes: (1) a device 100 with a network capability held by a user and (2) an automatic route planning system 200.

The device 100 with the network capability of the user may include a smart phone, a tablet computer, a notebook computer and a desktop computer, and the main function is to provide a wireless signal. The base station 102 is connected to the Internet 104. The user can upload the plurality of points of interest information 103 to be planned to the network through the device 100 having the network capability, and finally receive the trip planning information 114 to the device for display and editing.

The automatic trip planning system 200 includes a service host 105, a trip planning history database 107, a trip group analysis server 109, an integrated information database 111, and a trip planning server 113. The service host 105 is responsible for receiving the plurality of point of interest information 103 transmitted by the user through the network capable device 100, and transmitting the backend analysis and the calculated trip plan 114 result to the network capable device 100. To display information for the user's reference, the itinerary 114 can be a daily itinerary, transportation, and other related information. The trip group analysis server 109 first reads the trip plan history database 107, analyzes and counts the trip plan history information 108 for all users, and uses the grouped interest point information 110 result as the trip plan server 113. Input. The function of the trip planning server 113 is to determine the plurality of "the same day interest point collection" information results formed by the grouped interest points 110 according to the preset time of the day (which can be set to eight to ten hours of play time). If there is any accumulated play time in the set of points of interest over the day, then the analysis and calculation are performed by the quadratic clustering algorithm; and the trip planning server 113 is further used to retrieve the comprehensive information database 111 for storing therein. The interest point related information 112 is used as information for the auxiliary trip planning, and the daily travel planning information 114 is output, and the travel planning information 114 is transmitted back to the user through the service host 105.

Please refer to FIG. 1 and FIG. 2 together. FIG. 2 is a schematic diagram of an embodiment of a trip group analysis server according to the present invention. The composition of the trip group analysis server 109 mainly includes: a point of interest information receiving module 21, a historical itinerary information analyzing module 22, and a primary grouping module 23.

Interest point information receiving module 21: when the user wants to plan a trip, the module is responsible for receiving a plurality of points of interest information 103 included in the travel request by the user 100 and the service host 105 transmitted by the network capable device, and It is input to the primary clustering module 23 for preliminary grouping.

The historical itinerary information analysis module 22: when there is a trip to be planned, the module is responsible for capturing the trip planning history information 108 of the trip planning history database 107, and marking the points of interest in the historical record divided into the same day. The sequence and storage are used to facilitate the use of the subsequent grouping module 23.

The primary grouping module 23 divides the plurality of points of interest information 103 into different primary groups according to the plurality of itinerary planning history information 108 and the plurality of points of interest information 103, and each of the primary groups includes a certain degree of interest points. The geographical relevance and the play order are in line with the recommendations of most people, and each group of the grouping results is used as the preliminary trip planning result.

Please refer to FIG. 1 , FIG. 2 and FIG. 3 together. FIG. 3 is a schematic diagram of an embodiment of a trip planning server according to the present invention, which mainly comprises: a point of interest group information receiving module 31 and a trip planning. The related auxiliary information receiving module 32, the secondary grouping module 33 and the trip planning module 34 are provided.

The interest point group information receiving module 31: the module is responsible for receiving the interest point information 110 of the corresponding group after the preliminary planning is analyzed by the itinerary planning history information 108, and inputting it to the itinerary planning module 34 for planning and processing. .

The travel planning related auxiliary information receiving module 32: after receiving the interest point related information 112 stored in the comprehensive information database 111, the module is responsible for taking out the recommended playing time, geographical location, traffic information and weather information of each interest point. The information for the trip planning is assisted and input to the trip planning module 34 for processing.

The trip planning module 34: the point of interest information 110 captured by the point of interest group information receiving module 31, and the interest points of the interest points, maps, traffic, and weather obtained by the trip planning related auxiliary information receiving module 32 are related. The information 112 is subjected to a daily time-course review, and is re-grouped by the secondary clustering module 33 by the secondary clustering algorithm 33 for the group that has accumulated too many playing hours in the group;

The second grouping module 33: for the second group of the accumulated playing time in the group group, the group is merged after the analysis; or the group is adjusted for the interest points that do not meet the playing time of the group; The trip planning information 114 is output to the user; the group that has accumulated the accumulated playing hours in the trip planning module 34, the geographical attribute of the interest point region of the user selected by the K-means grouping algorithm Values are similarly grouped together. The information of the interest points 110 of the second group is relatively high, and the similarity of the data in the same cluster is relatively high, and the similarity of the data in different clusters is relatively low, so that the travel route is further effectively planned for the user.

Please refer to FIG. 4(a) to FIG. 4(d), which are schematic diagrams of an embodiment of a K-means grouping algorithm, and the process steps are as follows: Step 1 as shown in Figure 4(a): randomly assign k cluster centers according to the number of days k to be finely divided.

Step 2 as shown in Figure 4(b): Generate k initial clusters.

Step 3 as shown in Figure 4(c): Observe the dependencies within the cluster and generate new quality centers.

Step 4 as shown in Figure 4(d): Repeat steps 2~3 to change the cluster boundary and finally reach convergence.

Please refer to FIG. 5, which is a flow chart of the automatic travel planning method of the present invention, and the process steps are as follows:

Step S1: receiving, by a service host, a plurality of points of interest information transmitted by a networked device.

Step S2: analyzing and counting a plurality of trip planning history information via a trip group analysis server to group the plurality of point of interest information.

Step S3: receiving, by a trip planning server, the plurality of interest point information of the group, and determining whether the accumulated play time of the interest points of the group generated by the group under the group (ie, one time group parameter) is used as a reference More than a preset number of hours, if not, based on a point of interest related information to plan a plurality of points of interest information of a group to generate trip planning information; if so, the analysis and recursive calculation of the grouping algorithm will The interest points of a group are sub-grouped according to their respective geographical locations, and then the points of interest of the second group are planned according to the information of the points of interest to adjust the travel planning information. Among them, the information about the points of interest includes maps, traffic, weather and other information.

Step S4: The generated trip planning information is transmitted to the service host via the trip planning server, and the travel planning information is transmitted to the network-enabled device through the service host for reference by the user.

In summary, the present invention periodically analyzes the travel planning history data of all users, counts the distribution of the interest point play dates in each trip, and labels and classifies the points of interest suitable for the same day play in advance, thereby generating different regions. The group of points of interest can be used as a reference for the points of interest in the itinerary planning. If the cumulative number of hours of interest in a group (on the same day) exceeds the daily reasonable number of hours (eight to ten hours), then the geographic location of each point of interest is used. Perform analysis and recursive calculation of the collocation group algorithm, and then regroup the points of interest according to the distance position, so that the daily planning journey can be subdivided to make the itinerary conform to the regional play concept, and the arrangement can be efficiently arranged. And browse the points of interest and make good use of the travel time. In addition, for the daily interest point group, through the open time, recommended play time and weather, traffic conditions and other information, the system automatically intelligently plans the sequence of interest points, and further provides reference information on diet and accommodation; In addition, the itinerary planning information also includes driving and mass transit information (road conditions, regional event information, etc.) to provide users with better traffic information. The present invention cooperates with the Web2.0 sharing mechanism and provides downloading to the user's personal portable device. Instant navigation services are available on the itinerary. In this way, by the assistance of the present invention, it is possible to overcome the inconvenience that the travel planning requires the user to spend a lot of effort and time, and the user only needs to join the points of interest and the number of days to be used in the system. The result of the trip planning can be automatically generated by this method, which is very convenient and convenient.

The above is intended to be illustrative only and not limiting. Any equivalent modifications or alterations to the spirit and scope of the invention are intended to be included in the scope of the appended claims.

100‧‧‧Devices with networking capabilities

102‧‧‧Base station

103‧‧‧Multiple points of interest information

104‧‧‧Internet

105‧‧‧Service Host

107‧‧‧Travel Planning History Database

108‧‧‧Travel planning history information

109‧‧‧Travel same day group analysis server

110‧‧‧ Points of interest after grouping

111‧‧‧Comprehensive information database

112‧‧‧Information on interest points

113‧‧‧Travel Planning Server

114‧‧‧Travel planning information

200‧‧‧Automatic Travel Planning System

Claims (12)

An automatic trip planning system includes: a service host for receiving a plurality of points of interest information transmitted by a networked device, and transmitting and analyzing one of the trip planning information to the link a network function device; a trip group analysis server for analyzing and counting a plurality of trip planning history information to group the plurality of point of interest information; and a trip planning server for receiving the grouping The plurality of points of interest information, and the plurality of points of interest information of the group are planned according to a point of interest related information to generate the trip planning information, and the trip planning information is transmitted to the service host to pass the service The host transmits the trip planning information to the device with the network function. The automatic trip planning system according to claim 1, wherein the information related to the point of interest includes one or a combination of the map, the traffic, and the weather information. The automatic trip planning system of claim 1, further comprising a trip planning history database for storing the plurality of trip planning history information. The automatic trip planning system described in claim 3, further comprising a comprehensive information database for storing information related to the point of interest. The automatic trip planning system according to claim 4, wherein the trip group analysis server performs the grouping of the plurality of points of interest information on a primary grouping parameter to generate at least one primary group. When the trip planning server determines that the accumulated play time of the interest point in any one of the groups exceeds a preset number of hours, the interest of the group is analyzed by the analysis and recursive calculation of the grouping algorithm. The points are sub-grouped according to the secondary grouping parameters, and the points of interest of the second group are planned according to the information of the points of interest to generate the trip planning information. The automatic trip planning system of claim 5, wherein the trip group analysis server further comprises: a point of interest information receiving module, configured to receive the plurality of points of interest information transmitted by the service host; a historical travel information analysis module for analyzing and statisticing the plurality of trip planning historical information, so as to extract and classify each travel planning historical information; and once-grouping module for The plurality of trip planning history information after the analysis will The plurality of points of interest information are grouped according to the primary grouping parameter to generate at least one of the group. The automatic trip planning system according to claim 6, wherein the trip planning server comprises: a point of interest group information receiving module, configured to receive each of the once group groups; one trip planning related The auxiliary information receiving module is configured to receive the information about the point of interest; and a trip planning module is configured to plan the plurality of points of interest information of each of the first group according to the information about the point of interest to generate the trip plan Information, and the trip planning module is further configured to determine whether the accumulated play time of the point of interest in the primary group exceeds the preset number of hours; and a quadratic grouping module, when the trip planning module determines When the accumulated play time of the interest point in the primary group exceeds the preset number of hours, the secondary cluster module is used to calculate the interest point of the primary group according to the analysis and recursive calculation of the clustering algorithm. The second grouping is performed according to the secondary grouping parameter, and the trip planning information is adjusted by the itinerary planning module. An automatic trip planning method includes the following steps: receiving, by a service host, a plurality of points of interest information transmitted by a networked device; and analyzing a plurality of trip planning history information by using a trip group analysis server And counting, the plurality of points of interest information are grouped by the plurality of points of interest information; and the plurality of points of interest information of the group are received by the one-way planning server, and the plurality of points of interest information of the group are grouped according to the information related to the points of interest Planning to generate the trip planning information, and transmitting the trip planning information to the service host to transmit the trip planning information to the networked device through the service host. For example, the automatic trip planning method described in claim 8 includes the map, the traffic, and the weather information. For example, the automatic trip planning method described in claim 8 further includes storing the plurality of trip planning history information by using a trip planning history database. For example, the automatic trip planning method described in claim 10, wherein the interest point related information is stored by an integrated information database. The automatic trip planning method as described in claim 11, wherein the trip group is divided into The step of generating the travel planning information by the server and the route planning server further includes: the travel group analysis server is configured to perform the grouping of the plurality of points of interest information once by using the grouping parameter once. a group; the trip planning server determines whether the accumulated play time of the point of interest in the primary group exceeds a preset number of hours, and if so, analyzes and recursively calculates the group by the group algorithm The point of interest is further sub-grouped according to the secondary grouping parameter, and the points of interest of the second group are planned according to the information of the point of interest to adjust the trip planning information.