• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.137-146
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• 2022

In relation to the travel itinerary recommendation service, which has recently become in high demand, our previous work introduces a method to quantify the popularity of places including tour spots, restaurants, and accommodations through social big data analysis, and to create a travel schedule based on the analysis results. On the other hand, the generated schedule was mainly composed of travel routes that connected tour spots with the shorted distance, and detailed schedule information including restaurants and accommodation information for each travel date was not provided. This paper presents an algorithm for constructing a detailed travel route using a scenario template in a travel schedule created based on social big data, and introduces a prototype system that implements it. The proposed system consists of modules such as place information collection, place-specific popularity score estimation, shortest travel rout generation, daily schedule organization, and UI visualization. Experiments conducted based on social reviews collected from 63,000 places in the Gyeongnam province proved effectiveness of the proposed system.

• ETRI Journal
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• v.46 no.3
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• pp.473-484
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• 2024

We introduce a machine learning-based web application to help travel agents plan a package tour schedule. K-nearest neighbor (KNN) classification predicts the optimal tourists' dwelling time based on a variety of information to automatically generate a convenient tour schedule. A database collected in collaboration with an established travel agency is fed into the KNN algorithm implemented in the Python language, and the predicted dwelling times are sent to the web application via a RESTful application programming interface provided by the Flask framework. The web application displays a page in which the agents can configure the initial data and predict the optimal dwelling time and automatically update the tour schedule. After conducting a performance evaluation by simulating a scenario on a computer running the Windows operating system, the average response time was 1.762 s, and the prediction consistency was 100% over 100 iterations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.112-123
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• 2017

The accurate forecasting of the public transportation's transit and arrival time has become increasingly important as more people use buses and subways instead of personal vehicles under the government's public transportation promotion policy. Using bus management system (BMS) data, which provide information on the real-time bus location, operation interval, and operation history, it is now possible to analyze the bus schedule reliability. However, the punctuality should always be considered together with the operation safety. Therefore, this study suggests a new methodology to secure both reliability and safety using the BMS data. Unlike other studies, we calculated the bus travel time between two bus stops by dividing the total travel length into 6 sections using 5 different measuring points. In addition, the optimal travel time for each bus route was proposed by analyzing the mean, standard deviation and coefficient of variation of the each section's measurement. This will ensure the reliability, safety and mobility of the bus operation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.257-259
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• 2017

본 논문은 여행상품 일정의 POI정보를 기반으로 생성된 여행 스케줄러에 따라 실제 여행이 이루어지고 여행 중에 촬영된 사진과 여행자가 작성한 여행상품 리뷰 및 여행기 등의 정보를 매시업하여 여행노트를 생성하는 시스템을 구현하였다. 무엇보다 여행자가 일일이 자신의 여행 스케줄을 입력해야하는 번거로움을 없이 여행중에 편리성을 제공받을 수 있다.

• Journal of Service Research and Studies
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• v.4 no.2
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• pp.49-56
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• 2014

Lately, We have experienced increasing of Smartphone. Therefore we have experienced increasing of Application for Smartphone. This study suggested Tour Management Application using the smartphone. When you travel, you need various information This study of Development for Application provide that guide of travel destination provide means of transportation, time of travel, traveling expensives management. This application will use conveniently This application provide various information of travel and this application will use tool of new mobile business.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.140-149
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• 2001

The paper discusses the problem of finding the Origin-Destination(O-D) shortest paths in internodal transportation networks with time-schedule constraints. The shortest path problem on the internodal transportation network is concerned with finding a path with minimum distance, time, or cost from an origin to a destination using all possible transportation modalities. The time-schedule constraint requires that the departure time to travel from a transfer station to another node takes place only at one of pre-specified departure times. The scheduled departure times at the transfer station are the times when the passengers are allowed to leave the station to another node using the relative transportation modality. Therefore, the total time of a path in an internodal transportation network subject to time-schedule constraints includes traveling time and transfer waiting time. In this paper, a genetic algorithm (GA) approach is developed to deal with this problem. The effectiveness of the GA approach is evaluated using several test problems.

• 공원문화
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• s.26
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• pp.26-32
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• 1984

There have been few researches on the factors affecting forest recreation demand and demand for and value of forest recreation in Korea. This study has three main objectives as follows; First, to introduce the nature of recreation demand, the factors affecting forest recreation demand, and the methods of measuring demand for and benefits from forest recreation by reviewing related literatures. Secondly, to investigate the visitors' characteristics, patterns of recreation activities, and their attitudes for the recreation environments at the Deogyu National Park through interviewing them with the questionaire. Thirdly, to estimate the demand for and benefits of forest recreation at the National Park by Travel Cost Method. The survey was dealt by three trained interviewers at the enterance of the park for 5 days from September 26 to October 10, 1982. The 430 respondents were sampled randomly among 9,391 visitors with 4.6% of sampling rate. As the results, the study revealed that most of visitors to Deogyu National Park were from urban areas and belonged to the intermediate-upper income classes, and that most of them traveled more than 250 km or 4 hours to the site from their origins. And more respondents answered that the recreation environments of the cite were more or less better than other recreation areas. From the date of travel distances and participation rates of 13 cities or counties, the demand schedule of forest recreation at the National Park was established. The estimated equation of total experience demand curve is; Log $VR_i$ 2.6353 – 1.021 Log $D_i$ $R^2=0.9451$ where, $VR_i$ $(%\times1000)$ = Participation rate of the ith origin $D_i$ (km) = Travel distance from the ith origin From the total experience demand curve, the demand curve of recreation resources was built by adding travel cost in distance (km). The regression equation of the recreation resources at the Nation park is; Log V = 4.0304 – 0.8167 Log D $R^2=0.9060$ From the demand schedule of recreation resources, the recreational bendfits of Deogyu National Park was estimated. The estimated bendfits to a visitor from the forest is equivalent to the travel cost of 2,372 km. The study also found out that the demand for recreation resources was less elastic than the demand for the total recreation experience at the Deogyu National Park.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.89-108
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• 2006

Korea has been entering the ageing society as the population of age over 65 shared over 7% since the year 2000. The ageing society needs to have transportation facility considering elderly people's travel behavior. This study aims to understand the elderly people's travel behavior using recent data in Korea. The activity schedule approach begins with travel outcomes are part of an activitv scheduling decision. For tho?e approach. used discrete choice models (especially. Nested Logit Model) to address the basic modeling problem capturing decision interaction among the many choice dimensions of the immense activity schedule choice set The day activity schedule is viewed as a sot of tours and at-home activity episodes tied togather with overarching day activity pattern using the Seoul Metropolitan Area Transportation Survey data, which was conducted in June, 2002. Decisions about a specific tour in the schedule are conditioned by the choice of day activity pattern. The day activity scheduling model estimated in this study consists of tours interrelated in a day activity pattern. The day activity pattern model represents the basic decision of activity participation and priorities and places each activity in a configuration of tours and at-home episodes. Each pattern alternative is defined by the primary activity of the day, whether the primary activity occurs at home or away, and the type of tour for the primary activity. In travel mode choice of the elderly and non-workers, especially, travel cost was found to be important in understanding interpersonal variations in mode choice behavior though, travel time was found to be less important factor in choosing travel mode. In addition, although, generally, the elderly was likely to choose transit mode, private mode was preferred for the elderly over 75 years old owing to weakened physical health for such things as going up and down of stairs. Therefore. as entering the ageing society, transit mode should be invested heavily in transportation facility Planning tor improving elderly transportation service. Although the model has not yet been validated in before-and-after prediction studies. this study gives strong evidence of its behavioral soundness, current practicality. and potential for improving reliability of transportation Projects superior to those of the best existing systems in Korea.

• Journal of the Korean Society for Railway
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• v.12 no.2
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• pp.302-308
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• 2009

This paper presents a comprehensive analysis of intercity rail passengers' and travel patterns based on the 2001 Seoul-Busan rail passengers' Travel Survey. Results representing personal characteristics such as age and income seem to affect on destination the income was not seen to be a critical effect on destination choice. The variables such as travel time, transfer status, and date for travel seem to be and recreation activity. However, the destination choice would be relationship between Seoul and all four destination cities. The insights gained of an activity-based rail travel demand model.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.176-184
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• 2023

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.