An Intelligent Customization Framework for Tourist Trip Design Problems

In the era of the experience economy, “customized tours” and “self-guided tours” have become mainstream. This paper proposes an end-to-end framework for solving the tourist trip design problems (TTDP) using deep reinforcement learning (DRL) and data analysis. The proposed approach considers heterogeneous tourist preferences, customized requirements, and stochastic traffic times in real applications. With various heuristics methods, our approach is scalable without retraining for every new problem instance, which can automatically adapt the solution when the problem constraint changes slightly. We aim to provide websites or users with software tools that make it easier to solve TTDP, promoting the development of smart tourism and customized tourism

観光スポットとルート推薦のためのユーザ適応型旅行プラン生成アルゴリズム

早大学位記番号:新8428早稲田大

A FRAMEWORK OF ADAPTED TRAVEL REFERENCES IN ONLINE SOCIAL MEDIA

Location information collected from mobile users, knowingly and unknowingly, can reveal not only a user’s latitude and longitude. In this paper, we study approximate k nearest neighbor queries where the mobile user queries the area based company about approximate k nearest sights according to his current location. To judge the security within our solutions, we define a crook model internet hosting in queries. The security analysis has shown our solutions ensures both location privacy meaning the client does not reveal any longer understanding about his place for that LBS provider and query privacy meaning the client does not reveal what type of POIs he's interested in the LBS provider. We're feeling the mobile user can purchase his location from satellites anonymously, coupled with base station coupled with LBS provider don't collude to comprise the customer location privacy or susceptible to anonymous funnel. RSA is not a probabilistic file encryption plan. To alter RSA acquiring a probabilistic file encryption plan, we must be adding random bits for your message m before encrypting m with RSA. The goal of transporting this out must be to ensure the mobile user can buy only one in POIs per query. In addition, once the mobile user can buy a string of encrypted k nearest POIs inside the response within the LBS server, they may frequently run the RR formula simply when using the LBS server to get a sequence of k nearest POIs without passion for query generation and response generation. Performance has shown our fundamental protocol performs much well compared to present PIR based LBS query protocols with regards to both parallel computation and communication overhead

Rethinking summarization and storytelling for modern social multimedia

Traditional summarization initiatives have been focused on specific types of documents such as articles, reviews, videos, image feeds, or tweets, a practice which may result in pigeonholing the summarization task in the context of modern, content-rich multimedia collections. Consequently, much of the research to date has revolved around mostly toy problems in narrow domains and working on single-source media types. We argue that summarization and story generation systems need to re-focus the problem space in order to meet the information needs in the age of user-generated content in different formats and languages. Here we create a framework for flexible multimedia storytelling. Narratives, stories, and summaries carry a set of challenges in big data and dynamic multi-source media that give rise to new research in spatial-temporal representation, viewpoint generation, and explanatio

Opening new dimensions for e-Tourism

In this paper we describe an e-Tourism environment that takes a community-driven approach to foster a lively society of travelers who exchange travel experiences, recommend tourism destinations or just listen to catch some interesting gossip. Moreover, business transactions such as booking a trip or getting assistance from travel advisors or community members are constituent parts of this environment. All these happen in an integrated, game-like e-Business application where each e-Tourist is impersonated as an avatar. More precisely, we apply 3D Electronic Institutions, a framework developed and employed in the area of multi-agent systems, to the tourism domain. The system interface is realized by means of a 3D game engine that provides sophisticated 3D visualization and enables humans to interact with the environment. We present "itchy feet", a prototype implementing this 3D e-Tourism environment to showcase first visual impressions. This new environment is a perfect research playground for examining heterogeneous societies comprising humans and software agents, and their relationship in e-Tourism. © Springer-Verlag London Limited 2006

Business intelligence and big data in hospitality and tourism: a systematic literature review

Purpose This paper aims to examine the extent to which Business Intelligence and Big Data feature within academic research in hospitality and tourism published until 2016, by identifying research gaps and future developments and designing an agenda for future research. Design/methodology/approach The study consists of a systematic quantitative literature review of academic articles indexed on the Scopus and Web of Science databases. The articles were reviewed based on the following features: research topic; conceptual and theoretical characterization; sources of data; type of data and size; data collection methods; data analysis techniques; and data reporting and visualization. Findings Findings indicate an increase in hospitality and tourism management literature applying analytical techniques to large quantities of data. However, this research field is fairly fragmented in scope and limited in methodologies and displays several gaps. A conceptual framework that helps to identify critical business problems and links the domains of business intelligence and big data to tourism and hospitality management and development is missing. Moreover, epistemological dilemmas and consequences for theory development of big data-driven knowledge are still a terra incognita. Last, despite calls for more integration of management and data science, cross-disciplinary collaborations with computer and data scientists are rather episodic and related to specific types of work and research. Research limitations/implications This work is based on academic articles published before 2017; hence, scientific outputs published after the moment of writing have not been included. A rich research agenda is designed. Originality/value This study contributes to explore in depth and systematically to what extent hospitality and tourism scholars are aware of and working intendedly on business intelligence and big data. To the best of the authors’ knowledge, it is the first systematic literature review within hospitality and tourism research dealing with business intelligence and big data

GIST: A generative model with individual and subgroup-based topics for group recommendation

© 2017 Elsevier Ltd In this paper, a Topic-based probabilistic model named GIST is proposed to infer group activities, and make group recommendations. Compared with existing individual-based aggregation methods, it not only considers individual members’ interest, but also consider some subgroups’ interest. Intuition might seem that when a group of users want to take part in an activity, not every group member is decisive, instead, more likely the subgroups of members having close relationships lead to the final activity decision. That motivates our study on jointly considering individual members’ choices and subgroups’ choices for group recommendations. Based on this, our model uses two kinds of unshared topics to model individual members’ interest and subgroups’ interest separately, and then make final recommendations according to the choices from the two aspects with a weight-based scheme. Moreover, the link information in the graph topology of the groups can be used to optimize the weights of our model. The experimental results on real-life data show that the recommendation accuracy is significantly improved by GIST comparing with the state-of-the-art methods

Perspectives on the road: narratives of motoring in Britain

This thesis is a study of the travel writing inspired by automobile journeys in Britain in the period 1896 to 1930 and the new modes of subjectivity afforded by the motor car. In permitting greater access to the countryside away from railway stations, motorists were able to gain fresh perspectives on the landscape. Their journeys in the countryside invited them to ‘rediscover’ England and shape new versions of national identity based on a revival of pre-industrial pastoral idylls. This model of Englishness was directly influenced by car travel, particularly ideas of getting ‘off the beaten track’. A comparative study of the travelogues of American writers visiting Britain looks at their search for a shared heritage and the contrasting vision of England that they convey. The different experience of automotive travel and freedom to use the car as described by female writers in the period is also explored in two case studies. Many of the texts analysed in this work have never been discussed in scholarly studies and so this thesis aims to apply new material to the catalogue of home tour narratives, and to shed new light on the early years of automobile travel. This thesis also explores the car’s relationship to modernity in the narratives and concerns about the impact of motorised tourism on the landscape. By weaving together different theoretical concepts from travel writing, such as notions of the tourist and traveller, with historical studies of the car’s cultural impact in Britain, this work aims to establish the travelogues featured as a distinct sub-genre of travel writing studies