THOR: A Hybrid Recommender System for the Personalized Travel Experience

One of the travelers’ main challenges is that they have to spend a great effort to find and choose the most desired travel offer(s) among a vast list of non-categorized and non-personalized items. Recommendation systems provide an effective way to solve the problem of information overload. In this work, we design and implement “The Hybrid Offer Ranker” (THOR), a hybrid, personalized recommender system for the transportation domain. THOR assigns every traveler a unique contextual preference model built using solely their personal data, which makes the model sensitive to the user’s choices. This model is used to rank travel offers presented to each user according to their personal preferences. We reduce the recommendation problem to one of binary classification that predicts the probability with which the traveler will buy each available travel offer. Travel offers are ranked according to the computed probabilities, hence to the user’s personal preference model. Moreover, to tackle the cold start problem for new users, we apply clustering algorithms to identify groups of travelers with similar profiles and build a preference model for each group. To test the system’s performance, we generate a dataset according to some carefully designed rules. The results of the experiments show that the THOR tool is capable of learning the contextual preferences of each traveler and ranks offers starting from those that have the higher probability of being selected

A Personalized Trip Planner For Vulnerable Road Users

This research presents an adaptive and personalized routing model that enables individuals with disabilities to save their route preferences to a mobility assistant platform. The proactive approach based on anticipated user need accommodates vulnerable road users’ personalized optimum dynamic routing rather than a reactive approach passively awaiting input. Most of the currently available trip planners target the general public’s use of simpler route options prioritized based on static road characteristics. These static normative approaches are only satisfactory when conditions of intermediate intersections in the network are consistent, a constant rate of change occurs per each change of the segment condition, and the same fixed routes are valid every day regardless of the user preference. In this study, we model the vulnerable road user mobility problem by accommodating personalized preferences changing by time, sidewalk segment traversability, and the interaction between sidewalk factors and weather conditions for each segment contributing to a path choice. The developed reinforcement learning solution presents a lower average cost of personalized, accessible, and optimal path choices in various trip scenarios and superior to traditional shortest path algorithms (e.g., Dijkstra) with static and dynamic extensions

Toward personalised and dynamic cultural routing: a three-level approach

This paper introduces the concept of “smart routing” as a recommender system for tourists that takes into account the dynamics of their personal user profiles. The concept relies on three levels of support: 1) programming the tour, i.e. selecting a set of relevant points of interests (POIs) to be included into the tour, 2) scheduling the tour, i.e. arranging the selected POIs into a sequence based on the cultural, recreational and situational value of each, and 3) determining the tour’s travel route, i.e. generating a set of trips between the POIs that the tourist needs to perform in order to complete the tour. The “smart routing” approach intends to enhance the experience of tourists in a number of ways. The first advantage is the system’s ability to reflect on the tourists’ dynamic preferences, for which an understanding of the influence of a tourist’s affective state and dynamic needs on the preferred activities is required. Next, it arranges the POIs together in a way that creates a storyline that the tourist will be interested to follow, which adds to the tour’s cultural value. Finally, the POIs are connected by a chain of multimodal trips that the tourist will have to make, also in accordance with the tourist’s preferences and dynamic needs. As a result, each tour can be personalised in a “smart” way, from the perspective of both the cultural and the overall experience of taking it. We present the building blocks of the “smart routing” concept in detail and describe the data categories involved. We also report on the current status of our activities with respect to the inclusion of a tourist’s affective state and dynamic needs into the preference measurement phase, as well as discuss relevant practical concerns in this regard

Distributed multimodal journey planner based on mashup of individual planners’ APIs

In this research work we describe the creation of the concept of a distributed journey planning system that links as many journey planning services as are available in public transportation operators and willing to participate in one or more networks of journey planners across Europe. This is integrated on European project MASAI and it is part of a development of mobile solutions that allows journey plans in Europe based on public transportation availability, with the possibility of buying tickets in a mobile device with a multi-operator scenario. A semantic context was created in order to identify which Application-Programming Interfaces (APIs) from different public transport operators to use and set start\end trip points.info:eu-repo/semantics/acceptedVersio

The Application of Geographic Information Systems to Support Wayfinding for People with Visual Impairments or Blindness

People with visual impairments or legal blindness are relying on differing, comprehensive information utilized for their individual mobility. Increasing the personal mobility of people with disabilities and thereby achieving a self-determined life are major steps toward a more inclusive society. Research and applications on mobility issues of people with visual impairments or blindness mainly focus on technical applications or assistive orientation and navigation devices, and less work is covering the individual needs, e.g., regarding the information required for wayfinding. Moreover, active participation of people with disabilities in research and development is still limited. ways2see offers a new online application to support individual mobility in context of pre-trip planning for people with visual impairments or blindness based on a Geographic Information System (GIS). Obstacles, barriers, landmarks, orientation hints, and directions for wayfinding are generated by user profiles. The underlying network for GIS analysis is designed as pedestrian network. This individually coded network approach integrates sidewalks and different types of crossings and implements various orientation and navigation attributes. ways2see integrates three research realms: firstly, implementing a participative and transdisciplinary research design; secondly, integrating personalized information aligned with the individual user needs; and thirdly, presenting result of GIS analysis through an accessible designed user interface

Natural Language based Context Modeling and Reasoning with LLMs: A Tutorial

Large language models (LLMs) have become phenomenally surging, since 2018--two decades after introducing context-awareness into computing systems. Through taking into account the situations of ubiquitous devices, users and the societies, context-aware computing has enabled a wide spectrum of innovative applications, such as assisted living, location-based social network services and so on. To recognize contexts and make decisions for actions accordingly, various artificial intelligence technologies, such as Ontology and OWL, have been adopted as representations for context modeling and reasoning. Recently, with the rise of LLMs and their improved natural language understanding and reasoning capabilities, it has become feasible to model contexts using natural language and perform context reasoning by interacting with LLMs such as ChatGPT and GPT-4. In this tutorial, we demonstrate the use of texts, prompts, and autonomous agents (AutoAgents) that enable LLMs to perform context modeling and reasoning without requiring fine-tuning of the model. We organize and introduce works in the related field, and name this computing paradigm as the LLM-driven Context-aware Computing (LCaC). In the LCaC paradigm, users' requests, sensors reading data, and the command to actuators are supposed to be represented as texts. Given the text of users' request and sensor data, the AutoAgent models the context by prompting and sends to the LLM for context reasoning. LLM generates a plan of actions and responds to the AutoAgent, which later follows the action plan to foster context-awareness. To prove the concepts, we use two showcases--(1) operating a mobile z-arm in an apartment for assisted living, and (2) planning a trip and scheduling the itinerary in a context-aware and personalized manner.Comment: Under revie

Sustainable Travel Incentives Optimization in Multimodal Networks

Tripod, an integrated bi-level transportation management system, is a smartphone application from the potential user’s point of view which would be instantly accessed prior to performing the trip. Since there are constantly several alternatives for any trip, Tripod considers a series and combination of various parameters, including departure time, mode and route, and rewards for each alternative with a number of redeemable points for goods and services called “Tokens”. The framework responsible for computing the optimized number of tokens awarded to the set of available alternatives in order to minimize the system-wide energy consumption under a constrained Token budget, is the System Optimization (SO) implemented in Tripod. To do so, a higher number of tokens would be awarded to the alternatives, guaranteeing a larger energy saving, less energy consumption, alternatively. SO is multimodal whereby public transit, private car, carpooling, etc. are being considered as the potential travel modes. Furthermore, SO is dynamic, predictive and personalized: the same alternative is rewarded differently, depending on the current and predicted future condition of the network and on the individual’s profile. In order to solve this problem, a multimodal simulation-based optimization model will be elaborated

Novas soluções para a interação entre operador e passageiro nos transportes públicos

Environmental awareness has been increasing over the years. Since the transportation sector is one of the great contributors of greenhouse gas (GHG) emissions, it is necessary to motivate people to leave their car at home and use public transport. However, service providers must meet passengers' needs in a more personalized way and improve the quality of the service they offer. This project aims to provide a tool that positively impacts the required shift towards sustainability, and it relies on the exchange of passenger information to achieve this goal. The challenge proposed by the company, OPT, is based on the creation of new solutions for the interaction between operator and passenger through the Smartphone. Given that OPT is headquartered in Porto, its area of intervention par excellence is focused on the Metropolitan Area of Porto (MAP). The project focused on the acquisition of passenger data from this same area to characterize it in terms of urban mobility. The study has the MAP as a starting point however, the goal is to create a solution that is scalable to any city. The project began by characterizing the current situation regarding passenger information in the metropolitan area of Porto and a passenger survey was conducted to understand their perception towards information in public transports. Despite the available app offer, there are opportunities for improvement in the context of the integration of essential app functionalities and user experience. In addition, a bilateral interaction between the two stakeholders is needed in order to generate relevant information from user feedback. In this way, a new mobile application concept for public transport was designed to co-create value and improve the quality of service and allow seamless mobility across the travel network. Taking into account the commercial potential of this project, the strategies of innovation and business are based on the optimization of resources and value for the clientAo longo dos anos, a consciencialização das populações relativamente ao meio ambiente tem vindo a aumentar. O setor dos transportes, nomeadamente o de passageiros, tem um grande impacto na emissão de gases poluentes e, por isso, a utilização do veículo próprio como meio de transporte de eleição tem de ser reduzida. Para isto, é necessário que o transporte público se torne apelativo e sirva as necessidades das pessoas de forma personalizada e com qualidade. Este projeto é desenvolvido de acordo com a premissa de melhoria da qualidade dos transportes públicos e baseia-se na troca de informação para atingir este objetivo. O desafio lançado pela OPT assenta na criação de novas soluções para a interação entre operador e passageiro. Tendo em conta que a OPT está sediada no Porto, a sua área de intervenção por excelência foca-se na Área Metropolitana do Porto (AMP) e, por isso, o projeto focou-se na aquisição de dados desta mesma área para a caracterizar em termos de mobilidade. O estudo tem a AMP como ponto de partida, no entanto, o objetivo é criar uma solução que seja escalável para qualquer cidade. Para analisar o estado da informação ao público na área metropolitana do Porto, procedeu-se ao levantamento da oferta e à realização de um inquérito aos passageiros. Apesar de existir alguma oferta relativamente a aplicações móveis que disponibilizam informação, existem oportunidades de melhoria no contexto da integração de funcionalidades essenciais e user experience. Além disso, a evolução indica uma interação entre os intervenientes de forma a que se possa gerar informação relevante a partir do feedback do utilizador. Desta forma, foi concetualizado um novo modelo de aplicação móvel para os transportes públicos. O objetivo é baseado na co-criação de valor para melhorar a qualidade do serviço e permitir uma mobilidade contínua, motivando assim para a utilização dos transportes coletivos. Tendo em conta o potencial comercial deste projeto, reflete-se sobre as estratégias de inovação e negócio tendo por base a otimização dos recursos e o valor para o clienteMestrado em Engenharia e Gestão Industria

ESP For Ecotourism: Discourse Skills,Technology,And Collaboration For Job Contexts

This capstone’s primary aim was to design a companion instructional guide for teachers of English for Specific Purposes for ecotourism professionals in Mexico. It identified gaps left by traditional EFL courses that tend to lack strong connections between language instruction and real-world job requirements for English usage. It looked at curricular reform efforts in other world regions with the intention to innovate ESP instruction in Mexico. Findings include recommendations for student-centered curricula that incorporate multimodal learning activities and authentic contexts for tourism jobs. Multiliteracies pedagogy drove the creation of the instructional guide’s components, which provide support in conducting small-group projects to develop interactive discourse, online research, and digital design skills within communities of practice. The guide includes resources, materials, and instructions to conduct needs analysis, foster mutual support, build collaboration among stakeholders, facilitate situated practice with applied technology, and increase knowledge for cross-cultural communication