Context-Awareness in Mobile Tourist Guides

Schwinger, Wieland; Grün, Christoph; Pröll, Birgit; Retschitzegger, Werner

doi:10.4018/978-1-60566-046-2.ch037

Cited by 45 publications

(48 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…As a multiagent system, CRUMPET does not utilize reasoning or the general context ontology. This similar study also proposes a context-aware support for smart phones, helping them learn users' POIs based on the previous interactions with the user as in CRUMPET [3,9,13,17].…”

Section: Crumpetmentioning

confidence: 99%

“…In CRUMPET, an adaptive user model learns user interests from the user's interaction with the system by increasing the interest amount of the object as the user asks for more information about it. Moreover, users' movements are evaluated to infer their interests [3,9,13,17].…”

Section: Crumpetmentioning

confidence: 99%

“…However, it is not clarified if it is rule-based reasoning or not. Ontology models are used to model the context and POIs, and the information presented to the user on the smart phone is simultaneously updated [3,8,13,14].…”

Section: Compassmentioning

confidence: 99%

“…The server, using a precaching strategy, allows the user to view the presentations (information) about the POIs on his/her smart phone. While the mobile phone user is driving or walking toward a certain location, the user's destination is predicted and the related data are downloaded to the mobile device before the user's arrival at the destination [3,7,13]. …”

Section: Gulliver's Geniementioning

confidence: 99%

See 3 more Smart Citations

Matching points of interest with user context: an ANN approach

Yılmaz¹

2017

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

Abstract:In this paper, the design and development of an artificial neural network (ANN) for similarity value calculation in a context-aware system is proposed. This neural network is used by the neural agent of the iConAwa system. Since iConAwa is an intelligent, context-aware, multiagent system, it provides mobile users with context-aware information and services, and also provides communication with each other. Context and points of interest are modeled in a flexible and extensible way by using ontologies. iConAwa derives high-level implicit context from low-level explicit context by inference performed over the context ontology. This approach decouples context reasoning from the source code of the system. With the addition of a neural agent, which uses an ANN, the system has learning capability. By using a neural network for similarity value calculation, the system can adapt to the needs of different people. System owners can introduce their own similarity metric considering their own requirements, which further improves the iConAwa system. Thus, the extended iConAwa system combines expert system characteristics with the capability to learn.

show abstract

Section: Crumpetmentioning

confidence: 99%

Section: Crumpetmentioning

confidence: 99%

Section: Compassmentioning

confidence: 99%

Section: Gulliver's Geniementioning

confidence: 99%

See 2 more Smart Citations

Matching points of interest with user context: an ANN approach

Yılmaz¹

2017

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

show abstract

“…Schwinger et al proposed an evaluation framework for comparing the customization capabilities of context-aware frameworks [23]. Context characteristics are associated with the management of context data, which comprise context properties, extensibility of unforeseen context, availability of context data, history of context records, and context validity.…”

Section: Related Workmentioning

confidence: 99%

Framework for NFC-Based Intelligent Agents: A Context-Awareness Enabler for Social Internet of Things

Lin

2014

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Context-aware applications are required to be aware of user context and ambient intelligent to support nonintrusive humancomputer interaction. However, the uncertain real-world environments make it difficult for a system to perceive enough environmental contexts and achieve user's goal. Therefore, this study proposes a framework for developing an NFC-enabled intelligent agent, which combines the NFC technique with context-acquisition, ontology-knowledgebase, and semantic-adaptation modules to be aware of location, time, device, and activity contexts with respect to personal and social profiles. To cope with the uncertain environment, a credit-based incentive scheme is also proposed to encourage social cooperation and thereby enlarge the value of personal perceptions. By developing a complete ontology knowledgebase, the proposed framework can incorporate with social-cooperation schemes to recommend relevant services for supporting reactive action, proactive achievement, and social cooperation. The resultant social-advertising system shows that this framework can support a wide-range of different functionalities and is indispensable to an NFC-based intelligent agent for social Internet of things.

show abstract

A Light-Weight Framework for Location-Based Services

Schwinger

Grün

Pröll

et al. 2005

On the Move to Meaningful Internet Systems 2005: OTM 2005 Workshops

View full text Add to dashboard Cite

MotivationContext-aware mobile systems aim at delivering information and services tailored to the current user's situation [1], [10]. One major application area of these systems is the tourism domain, assisting tourists especially during their vacation through location-based services (LBS) [4] , and employ their own data repositories, thus falling short in portability and having to deal with time consuming content maintenance. Second, often thick clients are used that may lack out-of-the-box-usage. Third, existing solutions are sometimes inflexible concerning configuration capabilities of the system. To deal with those deficiencies, we present a lightweight framework for LBS that can be used for various application domains. This framework builds on existing GIS standards, incorporates already available Web content, can be employed out-of-the-box, and is configurable by using a Web-based interface. The applicability of the framework is demonstrated by means of a prototype of a mobile tourist guide. Basic Features of our FrameworkIn the following a brief overview of the basic features of our framework is given.Support for LBS. Our framework supports the creation of LBS tailored to the user's position and preferences for arbitrary application domains, e.g. tourism or infrastructure management. The user is provided with a map of his/her surroundings together with points of interests (POIs) and the current position based on GPS.Integration of external data-sources. Integration of existing external data sources is enabled by incorporating existing GIS servers as well as by augmenting the POIs with existing Web content (cf. e.g. [11], [14]).Exploitation of GIS standards. Our framework uses the open OGC Web Map Service (WMS) standard [13] for retrieving geospatial information in form of maps.Application of a thin client approach. A thin client approach is employed allowing to run the application out-of-the-box. On the client side only a graphical, ActiveX enabled browser, an Internet connection and a GPS sensor is required.Configuration of external content inclusion. Our framework offers the possibility of configuring the inclusion of external Web content through a Web-based interface. First, POIs can be added, deleted and updated in the framework's repository (cf. Section 4). Second, for each POI a title, the geographical coordinates and an URL pointing to external Web content describing the POI, can be configured. Third, POIs can be assigned to possibly nested categories, thus forming thematic layers such as

show abstract

Context-Awareness in Mobile Tourist Guides

Cited by 45 publications

References 29 publications

Matching points of interest with user context: an ANN approach

Matching points of interest with user context: an ANN approach

Framework for NFC-Based Intelligent Agents: A Context-Awareness Enabler for Social Internet of Things

A Light-Weight Framework for Location-Based Services

Contact Info

Product

Resources

About