Tour recommendation for groups

Consider a group of people who are visiting a major touristic city, such as NY, Paris, or Rome. It is reasonable to assume that each member of the group has his or her own interests or preferences about places to visit, which in general may differ from those of other members. Still, people almost always want to hang out together and so the following question naturally arises: What is the best tour that the group could perform together in the city? This problem underpins several challenges, ranging from understanding people’s expected attitudes towards potential points of interest, to modeling and providing good and viable solutions. Formulating this problem is challenging because of multiple competing objectives. For example, making the entire group as happy as possible in general conflicts with the objective that no member becomes disappointed. In this paper, we address the algorithmic implications of the above problem, by providing various formulations that take into account the overall group as well as the individual satisfaction and the length of the tour. We then study the computational complexity of these formulations, we provide effective and efficient practical algorithms, and, finally, we evaluate them on datasets constructed from real city data

The Shortest Path to Happiness: Recommending Beautiful, Quiet, and Happy Routes in the City

When providing directions to a place, web and mobile mapping services are all able to suggest the shortest route. The goal of this work is to automatically suggest routes that are not only short but also emotionally pleasant. To quantify the extent to which urban locations are pleasant, we use data from a crowd-sourcing platform that shows two street scenes in London (out of hundreds), and a user votes on which one looks more beautiful, quiet, and happy. We consider votes from more than 3.3K individuals and translate them into quantitative measures of location perceptions. We arrange those locations into a graph upon which we learn pleasant routes. Based on a quantitative validation, we find that, compared to the shortest routes, the recommended ones add just a few extra walking minutes and are indeed perceived to be more beautiful, quiet, and happy. To test the generality of our approach, we consider Flickr metadata of more than 3.7M pictures in London and 1.3M in Boston, compute proxies for the crowdsourced beauty dimension (the one for which we have collected the most votes), and evaluate those proxies with 30 participants in London and 54 in Boston. These participants have not only rated our recommendations but have also carefully motivated their choices, providing insights for future work.Comment: 11 pages, 7 figures, Proceedings of ACM Hypertext 201

Improving Itinerary Recommendations for Tourists Through Metaheuristic Algorithms: An Optimization Proposal

In recent years, recommender systems have been used as a solution to support tourists with recommendations oriented to maximize the entertainment value of visiting a tourist destination. However, this is not an easy task because many aspects need to be considered to make realistic recommendations: the context of a tourist destination visited, lack of updated information about points of interest, transport information, weather forecast, etc. The recommendations concerning a tourist destination must be linked to the interests and constraints of the tourist. In this research, we present a mobile recommender system based on Tourist Trip Design Problem (TTDP)/Time Depending (TD) – Orienteering Problem (OP) – Time Windows (TW), which analyzes in real time the user’s constraints and the points of interest’s constraints. For solving TTDP, we clustered preferences depending on the number of days that a tourist will visit a tourist destination using a k-means algorithm. Then, with a genetic algorithm (GA), we optimize the proposed itineraries to tourists for facilitating the organization of their visits. We also used a parametrized fitness function to include any element of the context to generate an optimized recommendation. Our recommender is different from others because it is scalable and adaptable to environmental changes and users’ interests, and it offers real-time recommendations. To test our recommender, we developed an application that uses our algorithm. Finally, 131 tourists used this recommender system and an analysis of users’ perceptions was developed. Metrics were also used to detect the percentage of precision, in order to determine the degree of accuracy of the recommender system. This study has implications for researchers interested in developing software to recommend the best itinerary for tourists with constraint controls with regard to the optimized itineraries

Change, Choice, and Commercialization: Backpacker Routes in Southeast Asia

South-East Asia has the oldest and largest backpacker trails. This paper examines the geographies of such flows, drawing upon the largest survey to date of backpackers in Asia using qualitative research to survey the key changes from the 1970s to the 2000s. Backpacker trails have changed significantly and new routes have emerged including the ‘northern trail’ (Bangkok - Cambodia - Vietnam - Laos). It is to be expected that routes change as backpackers constantly seek new places, pioneering for later mass tourism. However, this paper suggests that using institutionalization as a framework, these changing trails and backpacker ‘choices’ can be seen as driven by growing commercialization and institutionalization. This then operates in combination with external variables (travel innovations - low cost airlines, and new transport networks); exogenous shock (political instability, terrorism); and growing regional competition from emerging destinations such as Vietnam and Cambodia

Smart Itinerary Smartphone Tourism Application

Even though tourism is a large and important part of the Armenian economy, Armenia’s tourism infrastructure is not as robust as other more mature tourist locations around the world. This project was focused on designing a mobile tourism application, tailored to Armenia that will help develop and mature its tourism market. We hoped to empower Armenia by bolstering interest in and access to Armenia and developing its tourism industry. Smart Itinerary stands out from other tourist applications due to its vast collection of Armenia-specific information along with its ability to provide a unique itinerary for each individual tourist based on their personal interests. Overall, we believe we have designed a tourism application that will help make Armenia a more accessible tourist location

Smoked marine fish from Western Region, Ghana: a value chain assessment

The value chain analysis of ths report focused on smoked marine fish- overwhelmingly the most important fish product originating in Western Region, Ghana. Smoked fish from Western Region is mainly destined for the domestic market where demand is very strong. Small quantities of smoked fish are destined for markets in Togo, Benin and Nigeria. The underlying objective of the fisheries value chain analysis is to identify opportunities for growth in the fisheries value chain, with an emphasis on those opportunities that have the potential to generate significant additional livelihoods, particularly at the level of the fishing communities and for low-income groups. The results from the value chain analysis will be used to identify pilot interventions to promote those livelihood outcomes. The main focus for the study is smoked fish (major species/product forms) destined for domestic markets. However, work will also be undertaken on the fresh fish trade and frozen fish to find out more about the significance of these value chains

Inclusion and Equity Committee Recommendations for Diverse Recruitment Report

The UNLV University Libraries Inclusion and Equity Committee (IEC) developed the Diverse Recruitment project in order to fulfill its charge in supporting the Libraries’ commitment to increasing representation and retention of historically underrepresented groups at all levels of staff. These recommendations draw upon a range of best practices, procedures, and programs. Largely informed by Duke University’s February 2018 Task Force for Diversity in Recruitment Report, three task forces each investigated a different aspect of understanding diverse recruitment as it related to the Libraries. These results were synthesized into a series of recommendations for the Libraries’ Leadership Team (LLT) and the Libraries to consider implementing

The benefits of opening recommendation to human interaction

This paper describes work in progress that uses an interactive recommendation process to construct new objects which are tailored to user preferences. The novelty in our work is moving from the recommendation of static objects like consumer goods, movies or books, towards dynamically-constructed recommendations which are built as part of the recommendation process. As a proof-of-concept we build running or jogging routes for visitors to a city, recommending routes to users according to their preferences and we present details of this system

CESARSC: Framework for creating Cultural Entertainment Systems with Augmented Reality in Smart Cities

The areas of application for augmented reality technology are heterogeneous but the content creation tools available are usually single-user desktop applications. Moreover, there is no online development tool that enables the creation of such digital content. This paper presents a framework for the creation of Cultural Entertainment Systems and Augmented Reality, employing cloud-based technologies and the interaction of heterogeneous mobile technology in real time in the field of mobile tourism. The proposed system allows players to carry out a series of games and challenges that will improve their tourism experience. The system has been evaluated in a real scenario, obtaining promising results.The areas of application for augmented reality technology are heterogeneous but the content creation tools available are usually single-user desktop applications. Moreover, there is no online development tool that enables the creation of such digital content. This paper presents a framework for the creation of Cultural Entertainment Systems and Augmented Reality, employing cloud-based technologies and the interaction of heterogeneous mobile technology in real time in the field of mobile tourism. The proposed system allows players to carry out a series of games and challenges that will improve their tourism experience. The system has been evaluated in a real scenario, obtaining promising results.This work is supported by the Spanish Ministry of Economy and Competitiveness under the INNPACTO project CL-SMARTVIEW (IPT-2012-1043-410000)