Beyond Personalization: Research Directions in Multistakeholder Recommendation

Recommender systems are personalized information access applications; they are ubiquitous in today's online environment, and effective at finding items that meet user needs and tastes. As the reach of recommender systems has extended, it has become apparent that the single-minded focus on the user common to academic research has obscured other important aspects of recommendation outcomes. Properties such as fairness, balance, profitability, and reciprocity are not captured by typical metrics for recommender system evaluation. The concept of multistakeholder recommendation has emerged as a unifying framework for describing and understanding recommendation settings where the end user is not the sole focus. This article describes the origins of multistakeholder recommendation, and the landscape of system designs. It provides illustrative examples of current research, as well as outlining open questions and research directions for the field.Comment: 64 page

Three-dimensional context-aware tailoring of information

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2010 EmeraldPurpose – The purpose of this paper is to explore the notion of context in ubiquitous computing. Personal Information Managers exploit the ubiquitous paradigm in mobile computing to integrate services and programs for business and leisure. Recognising that every situation is constituted by information and events, context will vary depending on the situation in which users find themselves. The paper aims to show the viability of tailoring contextual information to provide users with timely and relevant information. Design/methodology/approach – A survey was conducted after testing on a group of real world users. The test group used the application for approximately half a day each and performed a number of tasks. Findings – The results from the survey show the viability of tailoring contextual information to provide users with timely and relevant information. Among the questions in the questionnaire the users were asked to state whether or not they would like to use this application in their daily life. Statistically significant results indicate that the users found value in using the application. Originality/value – This work is a new exploration and implementation of context by integrating three dimensions of context: social information, activity information, and geographical position

Supporting Decisions: Understanding natural resource management assessment techniques

Report to the Land and Water Resources Research and Development Corporation. This document presents a review of NRM decision support techniques. It draws upon previous studies in the fields of management science, operations research, environmental economics and natural resource management. The objectives of the document are to: Explain the workings of the more significant (representative) methods of NRM decision support (including the latest developments); Discuss how these decision support methods may influence the outcome of NRM decisions; and Provide practicing NRM decision makers with guidance for choosing which methods to apply.Australia;natural resource management;assessment;decision support;

A context aware recommender system for tourism with ambient intelligence

Recommender system (RS) holds a significant place in the area of the tourism sector. The major factor of trip planning is selecting relevant Points of Interest (PoI) from tourism domain. The RS system supposed to collect information from user behaviors, personality, preferences and other contextual information. This work is mainly focused on user’s personality, preferences and analyzing user psychological traits. The work is intended to improve the user profile modeling, exposing relationship between user personality and PoI categories and find the solution in constraint satisfaction programming (CSP). It is proposed the architecture according to ambient intelligence perspective to allow the best possible tourist place to the end-user. The key development of this RS is representing the model in CSP and optimizing the problem. We implemented our system in Minizinc solver with domain restrictions represented by user preferences. The CSP allowed user preferences to guide the system toward finding the optimal solutions; RESUMO O sistema de recomendação (RS) detém um lugar significativo na área do sector do turismo. O principal fator do planeamento de viagens é selecionar pontos de interesse relevantes (PoI) do domínio do turismo. O sistema de recomendação (SR) deve recolher informações de comportamentos, personalidade, preferências e outras informações contextuais do utilizador. Este trabalho centra-se principalmente na personalidade, preferências do utilizador e na análise de traços fisiológicos do utilizador. O trabalho tem como objetivo melhorar a modelação do perfil do utilizador, expondo a relação entre a personalidade deste e as categorias dos POI, assim como encontrar uma solução com programação por restrições (CSP). Propõe-se a arquitetura de acordo com a perspetiva do ambiente inteligente para conseguir o melhor lugar turístico possível para o utilizador final. A principal contribuição deste SR é representar o modelo como CSP e tratá-lo como problema de otimização. Implementámos o nosso sistema com o solucionador em Minizinc com restrições de domínio representadas pelas preferências dos utilizadores. O CSP permitiu que as preferências dos utilizadores guiassem o sistema para encontrar as soluções ideais

When and where do you want to hide? Recommendation of location privacy preferences with local differential privacy

In recent years, it has become easy to obtain location information quite precisely. However, the acquisition of such information has risks such as individual identification and leakage of sensitive information, so it is necessary to protect the privacy of location information. For this purpose, people should know their location privacy preferences, that is, whether or not he/she can release location information at each place and time. However, it is not easy for each user to make such decisions and it is troublesome to set the privacy preference at each time. Therefore, we propose a method to recommend location privacy preferences for decision making. Comparing to existing method, our method can improve the accuracy of recommendation by using matrix factorization and preserve privacy strictly by local differential privacy, whereas the existing method does not achieve formal privacy guarantee. In addition, we found the best granularity of a location privacy preference, that is, how to express the information in location privacy protection. To evaluate and verify the utility of our method, we have integrated two existing datasets to create a rich information in term of user number. From the results of the evaluation using this dataset, we confirmed that our method can predict location privacy preferences accurately and that it provides a suitable method to define the location privacy preference

Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research

This paper reviews the published articles on eTourism in the past 20 years. Using a wide variety of sources, mainly in the tourism literature, this paper comprehensively reviews and analyzes prior studies in the context of Internet applications to Tourism. The paper also projects future developments in eTourism and demonstrates critical changes that will influence the tourism industry structure. A major contribution of this paper is its overview of the research and development efforts that have been endeavoured in the field, and the challenges that tourism researchers are, and will be, facing

Social media and tourism : a wishful relationship

For decades hospitality firms were used to domain the communication process. Thematic social network sites such as TripAdvisor became very important tools for travelers when deciding which hotels to book, and what restaurants and tourist attractions to visit, been a visible part of tourism communication evolution. Evidence suggests that e-WOM serves as a primary information source when tourists choose destinations, hotels, and other experiences. The role and use of social media in tourists’ decision making has been widely discuss in tourism and hospitality research, especially in the research phase of the tourist’ travel planning process. With the wide adoption of social media the influence of customers’ word-of-mouth increased and influences not only the research phase, but the repetition and overall customers’ experiences. To answer these questions a model assessing e-wom was developed and data was gathering from TripAdvisor regarding customer’s opinion in restaurant experiences. The results found establish the bases for understanding tourists’ engagement level and profiles.N/