94,983 research outputs found
Hybrid group recommendations for a travel service
Recommendation techniques have proven their usefulness as a tool to cope with the information overload problem in many classical domains such as movies, books, and music. Additional challenges for recommender systems emerge in the domain of tourism such as acquiring metadata and feedback, the sparsity of the rating matrix, user constraints, and the fact that traveling is often a group activity. This paper proposes a recommender system that offers personalized recommendations for travel destinations to individuals and groups. These recommendations are based on the users' rating profile, personal interests, and specific demands for their next destination. The recommendation algorithm is a hybrid approach combining a content-based, collaborative filtering, and knowledge-based solution. For groups of users, such as families or friends, individual recommendations are aggregated into group recommendations, with an additional opportunity for users to give feedback on these group recommendations. A group of test users evaluated the recommender system using a prototype web application. The results prove the usefulness of individual and group recommendations and show that users prefer the hybrid algorithm over each individual technique. This paper demonstrates the added value of various recommendation algorithms in terms of different quality aspects, compared to an unpersonalized list of the most-popular destinations
Advanced recommendations in a mobile tourist information system
An advanced tourist information provider system delivers information regarding sights and events on their users' travel route. In order to give sophisticated personalized information about tourist attractions to their users, the system is required to consider base data which are user preferences defined in their user profiles, user context, sights context, user travel history as well as their feedback given to the sighs they have visited. In
addition to sights information, recommendation on sights to the user could also be provided. This project concentrates on combinations of knowledge on recommendation systems and base information given by the users to build a recommendation component in the Tourist Information Provider or TIP system. To accomplish our goal, we not only examine several tourist information systems but also conduct the investigation on recommendation systems. We propose a number of approaches for advanced recommendation models in a tourist information system and select a subset of these for implementation to prove the concept
Ready To Roll: Southeastern Pennsylvania's Regional Electric Vehicle Action Plan
On-road internal combustion engine (ICE) vehicles are responsible for nearly one-third of energy use and one-quarter of greenhouse gas (GHG) emissions in southeastern Pennsylvania.1 Electric vehicles (EVs), including plug-in hybrid electric vehicles (PHEVs) and all-electric vehicles (AEVs), present an opportunity to serve a significant portion of the region's mobility needs while simultaneously reducing energy use, petroleum dependence, fueling costs, and GHG emissions. As a national leader in EV readiness, the region can serve as an example for other efforts around the country."Ready to Roll! Southeastern Pennsylvania's Regional EV Action Plan (Ready to Roll!)" is a comprehensive, regionally coordinated approach to introducing EVs and electric vehicle supply equipment (EVSE) into the five counties of southeastern Pennsylvania (Bucks, Chester, Delaware, Montgomery, and Philadelphia). This plan is the product of a partnership between the Delaware Valley Regional Planning Commission (DVRPC), the City of Philadelphia, PECO Energy Company (PECO; the region's electricity provider), and Greater Philadelphia Clean Cities (GPCC). Additionally, ICF International provided assistance to DVRPC with the preparation of this plan. The plan incorporates feedback from key regional stakeholders, national best practices, and research to assess the southeastern Pennsylvania EV market, identify current market barriers, and develop strategies to facilitate vehicle and infrastructure deployment
A hybrid strategy for privacy-preserving recommendations for mobile shopping
To calculate recommendations, recommender systems col-lect and store huge amounts of users â personal data such as preferences, interaction behavior, or demographic infor-mation. If these data are used for other purposes or get into the wrong hands, the privacy of the users can be com-promised. Thus, service providers are confronted with the challenge of oâ”ering accurate recommendations without the risk of dissemination of sensitive information. This paper presents a hybrid strategy combining collaborative filtering and content-based techniques for mobile shopping with the primary aim of preserving the customerâs privacy. Detailed information about the customer, such as the shopping his-tory, is securely stored on the customerâs smartphone and locally processed by a content-based recommender. Data of individual shopping sessions, which are sent to the store backend for product association and comparison with simi-lar customers, are unlinkable and anonymous. No uniquely identifying information of the customer is revealed, making it impossible to associate successive shopping sessions at the store backend. Optionally, the customer can disclose demo-graphic data and a rudimentary explicit profile for further personalization
Travel recommendations in a mobile tourist information system
An advanced mobile tourist information system delivers information about sights and events on a tourists travel route. The system should be personalized in its interaction with the tourist. Data that can be used for personalization are: the tourists interest profile, an analysis of their travel history, and the tourists feedback about sights. Existing mobile information systems for tourists do not tailor their information delivery to the tourists interests. In this paper, we propose the use of personalised recommendations that consider all of the personal information a tourist provides. We adopt and modify techniques from recommended systems to the new application area of mobile tourist information. We propose a number of methods for personalised recommendations; and select a subset of these for implementation. This paper then presents the implemented recommended component of our TIP system for mobile tourist informatio
Final report: Workshop on: Integrating electric mobility systems with the grid infrastructure
EXECUTIVE SUMMARY:
This document is a report on the workshop entitled âIntegrating Electric Mobility
Systems with the Grid Infrastructureâ which was held at Boston University on November 6-7
with the sponsorship of the Sloan Foundation. Its objective was to bring together researchers
and technical leaders from academia, industry, and government in order to set a short and longterm research agenda regarding the future of mobility and the ability of electric utilities to meet
the needs of a highway transportation system powered primarily by electricity. The report is a
summary of their insights based on workshop presentations and discussions. The list of
participants and detailed Workshop program are provided in Appendices 1 and 2.
Public and private decisions made in the coming decade will direct profound changes in
the way people and goods are moved and the ability of clean energy sources â primarily
delivered in the form of electricity â to power these new systems. Decisions need to be made
quickly because of rapid advances in technology, and the growing recognition that meeting
climate goals requires rapid and dramatic action. The blunt fact is, however, that the pace of
innovation, and the range of business models that can be built around these innovations, has
grown at a rate that has outstripped our ability to clearly understand the choices that must be
made or estimate the consequences of these choices. The group of people assembled for this
Workshop are uniquely qualified to understand the options that are opening both in the future of
mobility and the ability of electric utilities to meet the needs of a highway transportation system
powered primarily by electricity. They were asked both to explain what is known about the
choices we face and to define the research issues most urgently needed to help public and
private decision-makers choose wisely. This report is a summary of their insights based on
workshop presentations and discussions.
New communication and data analysis tools have profoundly changed the definition of
what is technologically possible. Cell phones have put powerful computers, communication
devices, and position locators into the pockets and purses of most Americans making it possible
for Uber, Lyft and other Transportation Network Companies to deliver on-demand mobility
services. But these technologies, as well as technologies for pricing access to congested
roads, also open many other possibilities for shared mobility services â both public and private â
that could cut costs and travel time by reducing congestion. Options would be greatly expanded
if fully autonomous vehicles become available. These new business models would also affect
options for charging electric vehicles. It is unclear, however, how to optimize charging
(minimizing congestion on the electric grid) without increasing congestion on the roads or
creating significant problems for the power system that supports such charging capacity.
With so much in flux, many uncertainties cloud our vision of the future. The way new
mobility services will reshape the number, length of trips, and the choice of electric vehicle
charging systems and constraints on charging, and many other important behavioral issues are
critical to this future but remain largely unknown. The challenge at hand is to define plausible
future structures of electric grids and mobility systems, and anticipate the direct and indirect
impacts of the changes involved. These insights can provide tools essential for effective private ... [TRUNCATED]Workshop funded by the Alfred P. Sloan Foundatio
A Framework for Integrating Transportation Into Smart Cities
In recent years, economic, environmental, and political forces have quickly given rise to âSmart Citiesâ -- an array of strategies that can transform transportation in cities. Using a multi-method approach to research and develop a framework for smart cities, this study provides a framework that can be employed to: Understand what a smart city is and how to replicate smart city successes; The role of pilot projects, metrics, and evaluations to test, implement, and replicate strategies; and Understand the role of shared micromobility, big data, and other key issues impacting communities.
This research provides recommendations for policy and professional practice as it relates to integrating transportation into smart cities
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