Adding Personalization and Social Features to a Context-Aware Application for Mobile Tourism

2013 ◽  
pp. 253-265 ◽  
Author(s):  
Ana Belén Barragáns-Martínez ◽  
Enrique Costa-Montenegro
Keyword(s):  
User Preferences ◽  
Location Based Services ◽  
Personalized Recommendation ◽  
Mobile Service ◽  
Context Aware ◽  
Practical Issue ◽  
Critical Research ◽  
Location Aware ◽  
Information Time ◽  
Social Features

The proliferation of location-aware mobile devices, together with the advent of Web 2.0 services, promotes the creation of hybrid applications which can provide innovative personalized context-aware services. Personalized recommendation services aim at suggesting products and services to meet users’ preferences and needs, while location-based services focus on providing information based on users’ current positions. Due to the fast growing of users’ needs in the mobile tourism domain, the provision of personalized location-based recommendation services becomes a critical research and practical issue. In this proposal, the authors present GiveMeAPlan, a mobile service which supplies tourist recommendations taking into account both the user preferences (personalization) and context information (time, location, weather, etc.) enriched with social features and targeted advertisements to support its business model. An application prototype is also being implemented to illustrate and test the system feasibility and effectiveness.

Adding Personalization and Social Features to a Context-Aware Application for Mobile Tourism

2014 ◽  
pp. 467-480 ◽  
Author(s):  
Ana Belén Barragáns-Martínez ◽  
Enrique Costa-Montenegro
Keyword(s):  
User Preferences ◽  
Location Based Services ◽  
Personalized Recommendation ◽  
Mobile Service ◽  
Context Aware ◽  
Practical Issue ◽  
Critical Research ◽  
Location Aware ◽  
Information Time ◽  
Social Features

The proliferation of location-aware mobile devices, together with the advent of Web 2.0 services, promotes the creation of hybrid applications which can provide innovative personalized context-aware services. Personalized recommendation services aim at suggesting products and services to meet users' preferences and needs, while location-based services focus on providing information based on users' current positions. Due to the fast growing of users' needs in the mobile tourism domain, the provision of personalized location-based recommendation services becomes a critical research and practical issue. In this proposal, the authors present GiveMeAPlan, a mobile service which supplies tourist recommendations taking into account both the user preferences (personalization) and context information (time, location, weather, etc.) enriched with social features and targeted advertisements to support its business model. An application prototype is also being implemented to illustrate and test the system feasibility and effectiveness.

scholarly journals Design and Development of a Context-aware Personalized Recommendation System: Mobile and Web Application

2017 ◽  
Author(s):  
Sara Saeedi ◽  
Xueyang Zou ◽  
Mariel Gonzales ◽  
Steve Liang
Keyword(s):  
Web Application ◽  
Management Practices ◽  
Recommendation System ◽  
Contextual Information ◽  
User Preferences ◽  
Personalized Recommendation ◽  
Context Information ◽  
Context Aware ◽  
Context Reasoning ◽  
Past Behavior

The ubiquity of mobile sensors (such as GPS, accelerometer and gyroscope) together with increasing computational power have enabled an easier access to contextual information, which proved its value in next generation of the recommender applications. The importance of contextual information has been recognized by researchers in many disciplines, such as ubiquitous and mobile computing, to filter the query results and provide recommendations based on different user status. A context-aware recommendation system (CoARS) provides a personalized service to each individual user, driven by his or her particular needs and interests at any location and anytime. Therefore, a contextual recommendation system changes in real time as a user’s circumstances changes. CoARS is one of the major applications that has been refined over the years due to the evolving geospatial techniques and big data management practices. In this paper, a CoARS is designed and implemented to combine the context information from smartphones’ sensors and user preferences to improve efficiency and usability of the recommendation. The proposed approach combines user’s context information (such as location, time, and transportation mode), personalized preferences (using individuals past behavior), and item-based recommendations (such as item’s ranking and type) to personally filter the item list. The context-aware methodology is based on preprocessing and filtering of raw data, context extraction and context reasoning. This study examined the application of such a system in recommending a suitable restaurant using both web-based and android platforms. The implemented system uses CoARS techniques to provide beneficial and accurate recommendations to the users. The capabilities of the system is evaluated successfully with recommendation experiment and usability test.

scholarly journals The Development of Mobile Service Applications for Consumers and Intelligent Networks

Economics ◽  
2015 ◽  
pp. 344-360
Author(s):  
Rebecca De Coster ◽  
Abdulrhman Albesher
Keyword(s):  
Business Models ◽  
Mobile Services ◽  
Mobile Internet ◽  
Location Based Services ◽  
Mobile Service ◽  
Intelligent Networks ◽  
Service Characteristics ◽  
Adoption Factors ◽  
Provision Of Services ◽  
Mobile Handset

The enhanced capabilities of mobile handsets are starting to include activities previously associated with traditional desktop computing capabilities. This extends the mobile handset from being used for connectivity to a range of purposes in both consumer and intelligent networks. This chapter examines the development of mobile service applications from current consumer telecommunication applications including context based services (such as location based services) to mobile internet-based services and the forthcoming applications for intelligent networks. Developments of both consumer and industry services in sectors with complex operations are examined in terms of service interactions by reviewing the adoption factors and the provision of services in terms of service characteristics and business models. This chapter develops conceptual frameworks for better understanding mobile services and mobile use in the context of intelligent networks along with emerging consumer applications.

scholarly journals Personalized Multi-Criteria Decision Strategies in Location-based Decision Support

2021 ◽  
Author(s):  
Claus Rinner ◽  
Martin Raubal
Keyword(s):  
Decision Support ◽  
Evaluation Method ◽  
User Preferences ◽  
Location Based Services ◽  
Weighted Averaging ◽  
Decision Strategy ◽  
Decision Strategies ◽  
Multi Criteria Evaluation ◽  
Current Location ◽  
Decision Alternatives

Location-based services (LBS) assist people in decision-making during the performance of tasks in space and time. Current LBS support spatial and attribute queries, such as finding the nearest Italian restaurant from the current location of the user, but they are limited in their capacity to evaluate decision alternatives and to consider individual decision-makers’ user preferences. We suggest that LBS should provide personalized spatial decision support to their users. In a prototype implementation, we demonstrate how user preferences can be translated into parameters of a multi-criteria evaluation method. In particular, the Ordered Weighted Averaging (OWA) operator allows users to specify a personal decision strategy. A traveler scenario investigating the influence of different types of users and different decision strategies on the outcome of the analysis serves as a case study.

A Context-Aware Smart TV System with Body-Gesture Control and Personalized Recommendation

2013 ◽  
pp. 115-130
Author(s):  
Wei-Po Lee ◽  
Che KaoLi
Keyword(s):  
Control System ◽  
Personalized Recommendation ◽  
Multimedia Content ◽  
Context Aware ◽  
Social Tag ◽  
Gesture Control ◽  
Human Gestures ◽  
Smart Tv ◽  
Interactive Services

Smart TV enables viewers to conveniently access different multimedia content and interactive services in a single platform. This chapter addresses three important issues to enhance the performance of smart TV. The first is to design a body control system that recognizes and interprets human gestures as machine commands to control TV. The second is to develop a new social tag-based method to recommend most suitable multimedia content to users. Finally, a context-aware platform is implemented that takes into account different environmental situations in order to make the best recommendations.

Mobile Location Based Services

2014 ◽  
pp. 214-227
Author(s):  
Hee Jhee Jiow
Keyword(s):  
Mobile Network ◽  
Location Based Services ◽  
Mobile Service ◽  
Positioning System ◽  
System Technology ◽  
Mass Market ◽  
Mobile Location ◽  
Global Positioning ◽  
The World ◽  
Evolution Of Technology

Mobile Location Based Services (MLBS) have been in operation since the 1970s. Conceived initially for military use, the Global Positioning System technology was later released to the world for other applications. As usage of the technology increased, mobile network points, developed by mobile service operators, supplemented its usage in various applications of MLBS. This chapter charts the trajectory of MLBS applications in the mass market, afforded by the evolution of technology, digital, and mobility cultures. Assimilating various MLBS classifications, it then situates examples into four quadrants according to the measures of user-position or device-position focus, and alert-aware or active-aware applications. The privacy implications of MLBS are captured on the economic, social, and political fronts, and its future is discussed.

Service-Oriented Architectures for Context-Aware Information Retrieval and Access

2010 ◽  
pp. 1549-1560
Author(s):  
Lu Yan
Keyword(s):  
Information Retrieval ◽  
Information Exchange ◽  
Exchange Process ◽  
Information Access ◽  
Mobile Service ◽  
Context Aware ◽  
Service Oriented Architectures ◽  
Information Retrieval Systems ◽  
To Come ◽  
Process Context

Humans are quite successful at conveying ideas to each other and retrieving information from interactions appropriately. This is due to many factors: the richness of the language they share, the common understanding of how the world works, and an implicit understanding of everyday situations (Dey & Abowd, 1999). When humans talk with humans, they are able to use implicit situational information (i.e., context) to enhance the information exchange process. Context (Cool & Spink, 2002) plays a vital part in adaptive and personalized information retrieval and access. Unfortunately, computer communications lacks this ability to provide auxiliary context in addition to the substantial content of information. As computers are becoming more and more ubiquitous and mobile, there is a need and possibility to provide information “personalized, any time, and anywhere” (ITU, 2006). In these scenarios, large amounts of information circulate in order to create smart and proactive environments that will significantly enhance both the work and leisure experiences of people. Context-awareness plays an important role to enable personalized information retrieval and access according to the current situation with minimal human intervention. Although context-aware information retrieval systems have been researched for a decade (Korkea-aho, 2000), the rise of mobile and ubiquitous computing put new challenges to issue, and therefore we are motivated to come up with new solutions to achieve non-intrusive, personalized information access on the mobile service platforms and heterogeneous wireless environments.

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