Location-Sensitive Tour Guide Services Using the Semantic Web

Kim, Jong-Woo; Kim, Ju‐Yeon; Hwang, Hyun-Suk; Kim, Chang-Soo

doi:10.1007/11552451_125

Cited by 5 publications

(5 citation statements)

References 3 publications

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“…Recommendation is based on the user profiles and features of the shops. [3] and [4] are other examples of studies to integrate LBS and Semantic Web. In [3] a semantic web based tour guide system is developed on hotel domain.…”

Section: Related Workmentioning

confidence: 99%

“…[3] and [4] are other examples of studies to integrate LBS and Semantic Web. In [3] a semantic web based tour guide system is developed on hotel domain. An ontology is defined to describe the properties of hotels, which is populated by crawling the web sites of desired hotels.…”

Section: Related Workmentioning

confidence: 99%

“…Given a POI name and its city, a web search is run using the Yahoo API. Among the returning top web pages, most distinguishing terms are 1 Google Maps -http://code.google.com/apis/maps/index.html 2 GeoNames -http://www.geonames.org 3 DBpedia -http://dbpedia.org identified using an information extraction technique, namely TF-IDF. These terms are then used to identify the category of the POI.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Ontology-based recommendation for points of interest retrieved from multiple data sources

Özdikiş

Orhan

Danismaz

2011

Proceedings of the International Workshop on Semantic Web Information Management

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Introduction of powerful mobile devices and increasing availability of online services make it possible to develop a wide range of mobile applications. Making recommendations to the users on their mobile devices based on their location is a wellknown application area of location based services. In this work we introduce an ontology based approach to find reasonable recommendations for sites (Points of Interest) like restaurants, hotels, and touristic places. We extend an existing OWL ontology in order to keep semantic relationships between different site types. Our application populates this ontology with site instances collected from several data sources, namely Google Maps, GeoNames, DBpedia and a local database. During this integration process, solutions for ontology mapping, site categorization, and duplicate site detection are developed. The ontology is then used to make recommendations on a mobile augmented reality application based on user's inputs on his device.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Ontology-based recommendation for points of interest retrieved from multiple data sources

Özdikiş

Orhan

Danismaz

2011

Proceedings of the International Workshop on Semantic Web Information Management

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“…The system was developed based on data from the National Museum of Natural Science -one of the largest museums in Taiwan. Kim et al (2005) presented the architecture of tour information services based on semantic web technologies. The aim of the service is to provide the exact tour information and interoperability between the server systems.…”

Section: Related Workmentioning

confidence: 99%

Semantic approach to travel information search and itinerary recommendation

Cao

Nguyen

2012

International Journal of Web Information Systems

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Purpose -The growth of online data and services on the Web have have led to the Web become an indispensable tool for the tourist industry. It is not denied that various approaches bring benefits for visitors, in supporting their searching for tourist attractions, such as interesting places for the visit, eating or staying. However, like a coin has two sides, too much information would present a difficulty for people when planning their journeys. Generally, tourists usually have problems when trying to find satisfactory accommodation if references to nearby restaurants, sights or event locations are lacking. In addition, travelers suffer from the information overload when they look for information about potential destinations, events and related services. Providing relevant and up-to-date information for the tourists with different personal interests is still a challenging task for the tourist guide information systems. The purpose of this paper is to propose a semantic approach for searching tourist information and generating travel itinerary. Design/methodology/approach -The paper focus on introducing an ontological model for representation of tourist resources as well as traveler's profile. Based on this model, smart user interfaces facilitating the semantic search have been implemented in the mobile travel guide application. In addition, the authors propose an algorithm for generating travel itinerary which combines semantic matching with ant colony optimization technique. Findings -The Semantic Tourist informAtion Access and Recommending (STAAR) system, which has been implemented to promote the travel activity in Hanoi, reveals the advantages of the semantic approach in the development of smart application with ontology-based, user-friendly interface and high precision information search features. An experiment was conducted to show that the proposed algorithm generates travel itinerary relevant to both criteria of itinerary length and user interest. Originality/value -This paper presents a novel algorithm for planning a travel itinerary that is optimized on the length as well as semantically matching the user interests.

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“…Earlier work on mobile systems in changing contexts has focused on applications like tour guide systems: how well the information adapts to location; how location awareness can be represented. The GUIDE system and its follow-on work using multi-modal interactions for the delivery of information on a location-aware device is an exemplar of this kind of work [Bornträger et al 2003], while more recent work [Fujii et al 2005;Kim et al 2005] focuses on the effectiveness of more dynamically constructed, location aware tours. While changing context is an important aspect of mobile device interaction especially that which is focused on location discovery tasks, mobility per se and its effect on performance, is not a core part of design or evaluation in these systems.…”

Section: Related Workmentioning

confidence: 99%

mSpace Mobile: Exploring Support for Mobile Tasks

Wilson

Russell

Smith

et al.

People and Computers XX — Engage

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In the following paper we present a formative study comparing two Web application interfaces, mSpace Mobile and Google Local in supporting Web-based location discovery tasks on mobile devices while stationary and while on the move. While mSpace Mobile performed well in both stationary and mobile conditions, performance in Google Local dropped significantly in the mobile condition. We postulate that mSpace Mobile performed better because it breaks the paradigm of the page for delivering Web content, thereby enabling new and more powerful interfaces to be used to support mobility.

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Location-Sensitive Tour Guide Services Using the Semantic Web

Cited by 5 publications

References 3 publications

Ontology-based recommendation for points of interest retrieved from multiple data sources

Ontology-based recommendation for points of interest retrieved from multiple data sources

Semantic approach to travel information search and itinerary recommendation

mSpace Mobile: Exploring Support for Mobile Tasks

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