CN-122019893-A - Dynamic travel recommendation data analysis method and system

Abstract

The invention relates to the technical field of data processing, in particular to a method and a system for analyzing dynamic travel recommended data, which comprises the following steps of combing the dynamic track of tourists based on the data of the tourist mobile terminal and a scenic spot monitoring terminal, and (3) structuring node-to-departure time and space distribution, analyzing traffic pressure and resource limited conditions, adjusting node sequence and connection arrangement, screening travel conflict and resource aggregation, and outputting a time-sharing recommended path group. According to the invention, through full-flow dynamic collection and structuring processing of tourist journey and scenic spot multisource states, mapping and fusion are carried out on node-to-departure information and scenic spot space capacity under time sequence, dynamic retrieval of node resource pressure and traffic accessibility is realized, space-limited node and path sequence adjustment is efficiently completed according to real-time changing resources and journey elastic intervals, time-sharing path output generates diversified access sequences aiming at resource distribution and passenger flow trend, and the problems of conflict and resource unbalance caused by a single static rule are avoided.

Inventors

• LIU YIZHEN
• YANG XUEYAN

Assignees

• 山东经贸职业学院

Dates

Publication Date

20260512

Application Date

20260203

Claims (10)

1. 1. A method for analyzing dynamic travel recommendation data, the method comprising: S1, analyzing the reported departure time and the current position based on a tourist mobile terminal, judging the matching of a tourist journey and scenic spot opening by combining the opening period and the reception capacity of a scenic spot monitoring terminal, and carding the arrival and departure time of nodes to obtain a tourist time sequence track set; S2, searching each node to the departure time based on the tourist time sequence track set, analyzing the tourist distribution of the scenic spot in the same period, comparing the traffic process among the nodes, and structuring the node space distribution and the tourist interval according to the path sequence to obtain the resource dynamic distribution data; S3, analyzing traffic jam and stay limitation in a moving period among nodes based on the dynamic resource distribution data, screening an elastic section, carrying out space and traffic allocation, and judging a dual limited area to obtain a space limited node group; s4, based on the space limited node group, adjusting nodes in a behavior sequence to leave time, analyzing connection conditions of the front and rear nodes, comparing non-conflict section resource pressures, and reordering access sequences according to space and traffic states to obtain a node optimization time sequence chain; And S5, based on the node optimization time sequence chain, screening traffic intervals of departure and arrival of each node, analyzing spatial distribution and reception capacity of each time period, judging travel conflict and resource aggregation, and carding node access and stay arrangement to obtain a time-sharing recommended path group.
2. 2. The method of claim 1, wherein the set of guest timing trajectories includes a departure reference time, a node arrival schedule, and a node departure schedule, the dynamic distribution of resources includes a node traffic occupancy state, a node admission margin state, and a node stay bearer state, the set of spatially restricted nodes includes a congestion entry node, a congestion exit node, and a stay restricted node, the node optimization timing chain includes a node access order table, a node-to-departure schedule, and a neighboring node engagement schedule, and the set of time-sharing recommended paths includes time-sharing access path information, time-sharing node stay information, and time-sharing path switch information.
3. 3. The method for analyzing dynamic travel recommendation data according to claim 1, wherein the step of obtaining the tourist timing track set specifically comprises the steps of: S101, analyzing the reported departure time and the current position parameter based on the visitor mobile terminal, judging the consistency of the equipment identification numbers, combining the continuous positioning data sequence, and arranging all positioning coordinates in an equal time interval extraction mode, and arranging according to the extraction time sequence to obtain a time sequence positioning group; S102, based on the time sequence positioning group, comparing the space positions of the nodes set by each terminal coordinate point and the scenic spot monitoring terminal, synchronizing the numbers of the matched nodes, searching the open time period and the reception capacity state of each node, identifying the overlapping item of the terminal time of the track segment and the open time period of the node, and judging the reception state of the node to obtain a node access permission set; And S103, sorting the segment numbers with the entry conditions based on the node access permission set, analyzing the start and end moments of the corresponding track segments, and pairing the end and start moments of the adjacent segments in the sorting sequence to obtain the tourist timing sequence track set.
4. 4. The method for analyzing dynamic travel recommendation data according to claim 1, wherein the step of obtaining the dynamic distribution data of the resources specifically comprises: S201, analyzing the arrival time and the departure time of each node based on the tourist time sequence track set, judging the continuity of the start and stop moments of each access node in the path, screening the stay period and the movement interval between adjacent nodes in the path, and optimizing the data sequence according to the time sequence relationship in the path to obtain a time sequence engagement sequence; S202, based on the time sequence connection sequence, comparing the position data of tourists in the time period recorded by a scenic spot monitoring terminal, judging the distribution density of the tourists in the space range of the nodes, screening the node numbers of dense tourists, and labeling the node and the density state of the corresponding time period to the original node data to obtain a space aggregation labeling set; S203, analyzing arrival and departure time of adjacent nodes based on the space aggregation label set, calculating space distance and movement interval of node geographic coordinates, judging space distribution and tourist interval characteristics among the nodes, and structuring and integrating all the nodes and tourist information to obtain resource dynamic distribution data.
5. 5. The method for analyzing dynamic travel recommendation data according to claim 1, wherein the step of obtaining the space-constrained node group specifically comprises: S301, analyzing traffic tension and stay limited conditions of a moving period between access nodes based on the dynamic resource distribution data, judging passenger flow occupation states and stay bearing states of adjacent nodes, comparing passenger flow distribution and stay pressure changes in a moving section, and identifying node sections with blocked traffic and limited stay to obtain limited section identification data; S302, based on the limited section identification data, screening an elastic section with an adjustment window, analyzing the adjustable characteristic of the elastic section in a corresponding period, comparing the overlapping condition of the elastic section and the limited section in time sequence, judging the replacement space of the elastic section to the limited section, and setting the elastic section with the replacement as a switching relation to obtain an elastic switching mapping group; s303, based on the elastic switching mapping group, combining tourist movement track data and scenic spot node resource distribution trend, analyzing conflict states in inter-node time periods, judging passenger flow aggregation states and traffic conditions of conflict nodes, and comparing overlapping ranges of resource limitation and traffic limitation to obtain a space limitation node group.
6. 6. The method for analyzing dynamic travel recommendation data according to claim 1, wherein the step of obtaining the node optimization timing chain specifically comprises: S401, analyzing the arrival and departure time of each node in a behavior sequence based on the space limited node group, judging the limited time period of the node in a path time sequence, comparing the original arrival and departure time of the node with the connection logic of adjacent nodes, and identifying the node time combination to be adjusted to obtain a time sequence adjustment factor set; S402, judging the connection condition between the adjacent nodes and the front and back nodes based on the time sequence adjustment factor set, comparing traffic and passing parameters corresponding to the arrival and departure intervals of the adjacent nodes, screening node sections with connection time intervals smaller than a preset safety threshold, adjusting the node sequence and the association state of the sections, and aggregating rearrangement data to obtain connection conflict mapping information; s403, based on the engagement conflict mapping information, comparing the non-conflict section resource pressure recorded by the server, judging the passenger flow occupation state and the available round allowance state of the non-conflict section node, and recombining adjacent node engagement time information to obtain a node optimization time sequence chain.
7. 7. The method for analyzing dynamic travel recommendation data according to claim 1, wherein the step of acquiring the time-sharing recommendation path group specifically comprises: S501, based on the node optimization time sequence chain, screening the departure time of each access node and the arrival time of the next node, calculating traffic intervals among the nodes, judging the influence of the traffic intervals on path continuity, and identifying node combinations with the intervals smaller than a first preset threshold or larger than a second preset threshold and causing connection conflict to obtain a traffic connection abnormal index; S502, based on the traffic connection abnormal index, judging the space distribution and reception capacity of the time period where the node is located, comparing the passenger flow occupation state and the space bearing state of each node, screening the node numbers with obvious resource aggregation risk, and integrating the space and time period characteristics of each node to obtain resource aggregation characteristic information; and S503, analyzing the continuity of node sequencing and the accessibility of stay arrangement based on the resource aggregation characteristic information, adjusting the node sequence and the arrival and departure arrangement, and optimizing the space connection relation of all nodes to obtain a time-sharing recommended path group.
8. 8. The method according to claim 1, wherein the scenic spot monitoring terminal is a device installed in each area, entrance and node of the scenic spot for collecting the data of the open state, number of people in the scenic spot, passenger flow and resource bearing condition of the scenic spot in real time, and the tourist journey is the schedule of departure, arrival, tour, stay and departure of the tourist at different stages in the tourist process.
9. 9. The method according to claim 1, wherein the scenic spot opening refers to an outward opening state of a scenic spot or a scenic spot at a certain period, each node refers to each tourist target point in a tourist trip, and the traffic process refers to a travel process that a tourist moves from one access node to the next access node.
10. 10. A dynamic travel recommendation data analysis system for implementing the dynamic travel recommendation data analysis method according to any one of claims 1 to 9, the system comprising: The travel track construction module is used for analyzing the reported departure time and the current position based on the tourist mobile terminal, judging the matching property of the tourist travel and the scenic spot opening by combining the opening period and the reception capacity of the scenic spot monitoring terminal, and carding the arrival and departure time of the nodes to obtain a tourist time sequence track set; The resource distribution association module searches each node to the departure time based on the tourist time sequence track set, analyzes the tourist distribution of the scenic spot in the same period, compares the traffic process among the nodes, and constructs the node space distribution and the tourist interval according to the path sequence to obtain the resource dynamic distribution data; The limited node allocation module analyzes traffic pressure and stay limitation in a moving period among nodes based on the dynamic resource distribution data, screens elastic sections, performs space and traffic allocation, and judges dual limited areas to obtain a space limited node group; The time sequence chain rearrangement module adjusts nodes in the behavior sequence to leave time based on the space limited node group, analyzes the connection condition of the front and rear nodes, compares the non-conflict section resource pressure, and reorders the access sequence according to the space and traffic state to obtain a node optimization time sequence chain; the time-sharing path generation module screens traffic intervals of departure and arrival of each node based on the node optimization time sequence chain, analyzes spatial distribution and reception capacity of each time period, judges travel conflict and resource aggregation, and combines node access and stay arrangement to obtain a time-sharing recommended path group.

Description

Dynamic travel recommendation data analysis method and system Technical Field The invention relates to the technical field of data processing, in particular to a dynamic travel recommendation data analysis method and system. Background The data processing relates to collection, storage, organization, analysis and utilization of various types of data, and the technical field is widely applied to a plurality of application scenes such as internet service, artificial intelligence, intelligent recommendation systems, information retrieval and management and the like. The traditional dynamic travel recommendation data analysis method is a technology for recommending by adopting a rule matching mode after collecting and primarily analyzing related data based on dynamic factors such as user positions, behavior habits and travel history records, generally, a user interest model or a scenic spot preference model is constructed by setting static recommendation rules, keyword association or user scoring and sorting modes, and the recommendation is performed according to the current positions and time information of users and by combining travel routes and scenic spot information preset in the existing database. The traditional dynamic travel recommendation is only developed on the user information collection and rule matching level, continuous linkage of travel dynamics and scenic spot space-time state change is lacking, recommendation is output according to a static model, actual conflicts caused by traffic delay, scenic spot opening adjustment or resource occupation change among nodes in a path cannot be dynamically identified, connection of arrival and departure moments of the nodes is not dynamically checked, the travel recommendation is easily separated from an actual scene, the problems of tourist aggregation, node congestion and non-executable route occur, and the data processing and recommendation capability depending on space-time evolution is lacking. Disclosure of Invention In order to solve the technical problems in the prior art, the embodiment of the invention provides a method and a system for analyzing dynamic travel recommendation data. The technical scheme is as follows: in one aspect, a method for analyzing dynamic travel recommendation data is provided, including the following steps: S1, analyzing the reported departure time and the current position based on a tourist mobile terminal, judging the matching of a tourist journey and scenic spot opening by combining the opening period and the reception capacity of a scenic spot monitoring terminal, and carding the arrival and departure time of nodes to obtain a tourist time sequence track set; S2, searching each node to the departure time based on the tourist time sequence track set, analyzing the tourist distribution of the scenic spot in the same period, comparing the traffic process among the nodes, and structuring the node space distribution and the tourist interval according to the path sequence to obtain the resource dynamic distribution data; S3, analyzing traffic pressure and stay limitation of a moving period among nodes based on the dynamic resource distribution data, screening elastic sections, carrying out space and traffic allocation, and judging dual limited areas to obtain a space limited node group; s4, based on the space limited node group, adjusting nodes in a behavior sequence to leave time, analyzing connection conditions of the front and rear nodes, comparing non-conflict section resource pressures, and reordering access sequences according to space and traffic states to obtain a node optimization time sequence chain; And S5, based on the node optimization time sequence chain, screening traffic intervals of departure and arrival of each node, analyzing spatial distribution and reception capacity of each time period, judging travel conflict and resource aggregation, and carding node access and stay arrangement to obtain a time-sharing recommended path group. In another aspect, the tourist timing track set includes a departure reference time, a node arrival schedule and a node departure schedule, the dynamic resource distribution data includes a node passenger flow occupancy state, a node accessible round allowance state and a node stay bearing state, the space-limited node group includes a congestion entering node, a congestion leaving node and a stay-limited node, the node optimization timing chain includes a node access sequence table, a node departure schedule and a neighboring node connection schedule, and the time-sharing recommended path group includes time-sharing access path information, time-sharing node stay information and time-sharing path switching information. On the other hand, the step of obtaining the tourist time sequence track set specifically comprises the following steps: S101, analyzing the reported departure time and the current position parameter based on the visitor mobile terminal, judging the consistency o