Recommendation techniques are developed to discover user¡¦s real information need among large amounts of information. Recommendation systems help users filter out information and attempt to present those similar items according to user¡¦s tastes. In our work, we focus on discussion threads recommendation in the tourism domain. We assume that when users have traveling information need, they will try to search related information on the websites. In addition to browsing others suggestions and opinions, users are allowed to express their need as a question. Hence, we focus on recommending users previous discussion threads that may provide good answers to the users¡¦ questions by considering the question input as well as their browsing records. We propose a model, which consists of four perspectives: goal similarity, content similarity, freshness and quality. To validate and the effectiveness of our model on recommendation performance, we collected 14348 threads from TripAdvisor.com, the largest travel website, and recruited ten volunteers, who have interests in the tourism, to verify our approach. The four perspectives are utilized by two methods. The first is Question-based method, which makes use of content similarity, freshness and quality and the second is Session-based method, which involves goal similarity. We also integrate the two methods into a hybrid method. The experiment results show that the hybrid method generally has better performance than the other two methods.

Research in the field of travel time measurement using Bluetooth technology has been an area of great interest in recent years as transportation professionals strive to increase the cost-effectiveness, accuracy, anonymity, and safety of travel time data collection methods. Commonly used travel time data collection methods include the use of inductive loops, video cameras, and probe vehicles. However, Bluetooth, a globally accepted wireless technology, serves as the medium being utilized by more and more transportation consultants, public agencies, and academics in the collection of travel time data. This study seeks to develop a methodology for measuring travel times on arterial roads using Bluetooth technology. A literature review of general travel time methods and Bluetooth travel time methods was conducted to provide the context for a Bluetooth field deployment development and implementation. The study presents the deployment plan and data analysis of a case study conducted on Spring Street in Atlanta, Georgia. Variable heights, Bluetooth to Bluetooth interference, and detection of Bluetooth devices in probe vehicles are investigated and recommendations are suggested for future Bluetooth travel time studies.

Dissertation (Ph.D.)--Auburn University, / Abstract. Includes bibliographic references (p.228-235).

The classic time geography concept (space-time path) provides a powerful framework to study travel survey data which is an important source for travel behavior studies. Based on the space-time concept, this research will present a visualizing approach to analyze travel survey data. By inputting the data into GIS software such as TransCAD and ArcGIS and editing the needed information, this study will explain how to create 3D images of travel paths for showing the variation of trip distribution in relation to different social-economic factors deemed as the driving forces of such patterns. Also, this report will address the technical challenges involved in this kind of study and will discuss directions of future research. / text

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Multiple distribution travel time data has been observed in signalized corridors as well as freeway corridors. This behavior is typically caused by congestion, uncoordinated signals, or routes through a coordinated corridor that are not a priority. On the SR140 corridor near the Jimmy Carter Boulevard / I-85 Interchange, it was found that the travel times recorded on the corridor contained multiple distributions and thus a methodology was sought to properly separate the distributions in order to perform more robust statistical analysis. Next, an R statistical language library was found, called “mixtools”, which contained a multiple gamma distribution fitting function called “gammamixEM”. Gamma distributions were chosen for this application as typical travel time distributions tend contain a one sided tail. This function was used in conjunction with a monte-carlo approach to find fits for one to six distributions. The accuracy of the fit was confirmed through visual inspection of the plotted distributions. Then, the Akaike Information Criteria were used to compare the fits to determine the best fit number of distributions. This thesis contains a detailed outline of the algorithm as well as results from the algorithm for the combined Tuesday dataset from this project. It was found that the approach worked well for 60 out of 70 cases. In the 10 cases that were not ideal, the distributional fits make sense on a statistical level, however, for the purposes of the before and after project the next best Akaike Information Criteria value fit may need to used. These 10 cases tended to split obvious single distributions into two distributions, which is not desirable in a before and after analysis where one is not only testing individual distributions before and after construction but also determining if distributions were created or removed as a result of the change in operation of the interchange.

American households spend over $30 billion on tourism and take over 177 million long-distance leisure trips each year. These trips, and the subsequent vehicle miles traveled, have a significant impact on the transportation systems at major destinations across the country, especially those destinations that are still improving their transportation systems. Surprisingly, not much is known related to this type of travel. This dissertation expands the current knowledge of tourism travel behavior, in terms of how people make decisions regarding long-distance leisure activities and time use. Specifically, this dissertation develops and comprehensively examines a behavioral framework for household tourism time use and activity patterns. This framework combines (and builds upon) theory and methods from both transportation and tourism research fields such that it can be used to improve tourism demand modeling. This framework takes an interdisciplinary approach to describe how long distance leisure travelers allocate and maximize their time use across various types of activities. It also considers the many levels of tourism time use and activity patterns, including the structuring the broad annual leisure activity and time budget, forming individual tourism trips within the defined budget, and selecting specific activities and timing during each distinct tourism trip. Subsequently, this dissertation will additionally apply the time use and activity participation behavioral framework to four critical tourism research topics to demonstrate how the tourism behavioral framework can effectively be used to provide behavioral insights into some of the most commonly studied critical tourism issues. These application topics include household participation in broad tourism travel activities, travel parties’ tourism destination and travel mode selection, individuals’ loyalty towards daily and tourism activities, and travel parties’ participation in combinations of specific tourism trip activities. These application studies incorporate a variety of data sources, decision makers, study scales, situation-appropriate modeling techniques, and economic/individual/environmental factors to capture all aspects of the decision and travel activity-making process. / text

This thesis compares actual and perceived travel times and presents a model for predicting traffic flows when there is a network disruption. The goal of this research is to demonstrate the necessity of accounting for possible differences in travel time perception and actual travel times, and also to show trends in how the route choices change based on the transformation of the perceived travel times. A pilot test was done to determine actual travel time perceptions, and the results provided the foundation for the tests presented in this thesis and the model framework. The model is separated into three phases: equilibrium assignment, link travel time transform, and logit assignment. The transform of the link travel times is best represented by an inverse cumulative Normal distribution, and the corresponding values provide quantifiable measure of the severity of a traffic network disruption. The methodology is presented and applied to two test networks to demonstrate the resulting route choice patterns. Both networks are tested for three severity levels and three levels of demand. / text

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In recent years the Internet has greatly changed the travel industry and the emergence of social media has driven this change further. In the past travel companies have been natural links between customers and suppliers but today customers can buy travel directly from the supplier, making it difficult for travel companies to attract new customers and retain existing customers. As social media is revolutionizing the way people communicate, the trend suggests that it is becoming increasingly important for firms to take part in this technological development to interact with customers. Although Internet and social media has a major impact on firm-to-customer and customer-to-customer conversations, there is little guidance in academic literature and organizational contexts on how to use social media in an effective way. Therefore, the aim of this thesis is to describe and explain how social media has transformed the relationships between selected Swedish travel companies and their customers, and how these firms create and sustain value and relationships through social media. Furthermore, we will give implications for management on how to utilize social media to create and sustain value and relationships. The results of our research confirm that social media is transforming the relationships between firms and customers. From our findings we conclude that the customer has become more empowered, that interaction now occurs through a two-way communication and that social media has made industries and relationships more transparent. The results also indicate that firms do not realize the value that can be created through social media for the customer as well as for the firm. The use of social media among the interviewed firms varies with some firms using social media through many tools and some firms not using social media at all.   Our findings implicate that being aware of what value is created and why the firm is involved in a certain social media tool increases the likelihood of success. The firm should further not be afraid to experiment with social media. However, social media also presents challenges. As social media is characterized by rapidly changing trends, it is difficult to predict what will happen not only in a distant future, but even so just a few years ahead.