• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.71-92
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• 2008

Currently, hotel search engines may help travelers find hotels, but the returned set of information is usually not satisfactory to them. It is because the engines do not understand what travelers want exactly and cannot deal with the travelers' interest which is expressed in various terms, even including some ambiguous ones. The objective of this research is to build hotel ontology using currently available semantic web technologies such as RDF, OWL and SWRL and to show how it can be used to help travelers find hotels of their interest. To that end, we analyzed available hotel-related ontologies and investigated typical terms which are used when searching for hotels in the Q&A communities. Based on the results of the analysis and investigation, we designed hotel domain ontology which consists of Objective Concepts Ontology(OCO), Universal Concepts Ontology(UCO), and Evaluation Concepts Ontology(ECO). To demonstrate the use of the ontology for a hotel search, we developed a Semantic Hotel Search System (SHSS).

• Culinary science and hospitality research
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• v.24 no.3
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• pp.167-176
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• 2018

In this study, Big Data was used to collect the information related to 'Cooking Academy' keywords. After collecting all the data, we calculated the frequency through the text mining and selected the main words for future data analysis. Data collection was conducted from Google Web and News during the period from January 1, 2013 to December 31, 2017. The selected 64 words were analyzed by using UCINET 6.0 program, and the analysis results were visualized with NetDraw in order to present the relationship of main words. As a result, it was found that the most important goal for the students from cooking school is to work as a cook, likewise to have practical classes. In addition, we obtained the result that SNS marketing system that the social sites, such as Facebook, Twitter, and Instagram are actively utilized as a marketing strategy of the institute. Therefore, the results can be helpful in searching for the method of utilizing big data and can bring brand-new ideas for the follow-up studies. In practical terms, it will be remarkable material about the future marketing directions and various programs that are improved by the detailed curriculums through semantic network of cooking school by using big data.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1552-1559
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• 2006

In a web environment, similar information exists in many different places in diverse formats. Even duplicate information is stored in the various databases using different terminologies. Since most information serviced in the current World Wide Web however had been constructed before the advent of ontology, it is practically almost impossible to construct ontology for all those resources in the web. In this paper, we assume that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and existing RDBMS tables for semantic retrieval. In the processing of extracting a local ontology, some problems such as losing domain in formation can occur since the correlation of domain ontology has not been considered at all. To prevent these problems, we propose an instance-based matching which uses relational information between RDBMS tables and relational information between classes in domain ontology. To verify the efficiency of the method proposed in this paper, several experiments are conducted using the digital heritage information currently serviced in the countrywide museums. Results show that the proposed method increase retrieval accuracy in terms of user relevance and satisfaction.

• The Journal of Information Systems
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• v.20 no.3
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• pp.41-61
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• 2011

In order to buy products through the Internet, consumers dissipate much time and efforts in collecting and comparing product information from various online shopping malls. Consumers can save their efforts by using price comparison sites, but there are some shortcomings in comparison shopping. Firstly, comparison sites do not show the lowest price of some products that are selling in shopping malls. Secondly, the product information provided by comparison sites is sometimes wrong. Thirdly, there are too many results. In order to overcome the shortcomings, we suggested a comparison shopping system based on RSS by using ontology matching. We used the current RSS standard for syntactic interoperability instead of suggesting new standards. Moreover, we used ontology matching for semantic interoperability to compare product information with different ontologies. The suggested ontology matching consists of three steps. The first step is finding exact sense from WordNet for a given product category, and the second step is searching for matching product category candidates from the products of RSS feeds. The final step is calculating similarities of the candidates with the target product category. From the experiments, we could get better recall rates that are suitable for e-commerce environments and the results show that our system is effective in product comparison.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.316-320
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• 2005

We developed Intelligent Product Search Agent based on SWRL, and this agent can search product information with knowledge(facts and rules) on the web, implement price comparison for searched products considering delivery rates. Existing keyword based product search engines is poor at searching intent products though a user has already prefect knowledge about intent produces. Furthermore if a user has insufficient knowledge, it is impossible to implement search. Also, existing price comparison shopping mall gives users comparison service considering total price(product prices, taxes, delivery rates), this service is valid to single product and has limitations of system expansion and up-dating because of not rule base but programming base. If there is appropriate knowledge on the Semantic web and this makes product information retrieval possible, above problems can be solved clearly. In this research, we developed Intelligent Product Search Agent based on SWRL that can search product information efficiently by making agent to handle facts and rules by itself.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.6
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• pp.31-40
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• 2012

Ubiquitous technology influences on various firms of contents needed for self-healthcare, as it fuses into medical services. Particularly, rapid changes in the web and mobile environment, requiring various sorts of healthcare and its related contents, make efficiency of search more important. Personalized contents needs to be more refined as well as the existing simple keyword-centered searching method needs to be more effective in order to meet both requirements and characteristics of each patient or each user. A precise semantic searching method is required for a system to understand promptly the meaning of a contents. In this respect, to build a healthcare ontology has its own significance. This study builds up a system model that can be utilized practically in existing systems by setting up the Food Class and its sub-class among the healthcare contents with Protege tool and then materializing constraints and its relationships between each class. The healthcare contents ontology provides patients or users with a platform which can search the needed information promptly and precisely.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.11-18
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• 2008

One of important Issues in computer graphics field is to communicate among users in virtual world like secondlife. However, in 3D virtual world, users' needs to wish to build their own contents in 3D virtual space are rising, similarly, users produce own homepage and animation, and leave writing in notice board. In this paper, we tried to achieve this by introducing semantic annotation object concept, which is a kind of annotation method in 3D virtual world. User can retrieve an 3D object by searching corresponding annotation data. This method can build semantic 3D virtual world and enable users to search 3D objects by integrating 3D object and 2D semantic multimedia information. Also, through a comparison experiment with proposal system and general 3D virtual world. the performance of proposed system is evaluated.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.66-73
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• 2007

Internet is a part of our common life and tremendous information is cumulated. In these trends, the personalization becomes a very important technology which could find exact information to present users. Previous personalized services use content based filtering which is able to recommend by analyzing the content and collaborative filtering which is able to recommend contents according to preference of users group. But, collaborative filtering needs the evaluation of some amount of data. Also, It cannot reflect all data of users because it recommends items based on data of some users who have similar inclination. Therefore, we need a new recommendation method which can recommend prefer items without preference data of users. In this paper, we proposed the apparel coordination system using personalized preference on the semantic web. This paper provides the results which this system can reduce the searching time and advance the customer satisfaction measurement according to user's feedback to system.

• Journal of Information Technology Services
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• v.16 no.2
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• pp.111-127
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• 2017

Computing Performance, sensor, storage, memory, and network costs have been steadily declining, and IoT services have recently become more active. The Internet of Things is linked with Big Data to create new business, and public institutions and corporations are hurry to import Internet of things. As the importance of the Internet of things has increased, the number of devices supporting the IoT has rapidly increased. With the development of the Internet of Things, various types of Internet services are being developed. For this reason, there is an increasing demand for IoT service designers and developers for IoT service case automatic search technology. IoT service designers can avoid duplication with existing services through service case retrieval and developers can save cost and time by combining existing reusable service equipment. This paper proposes IoT-Lite ontology for IoT and Semantic Web service to solve the above-mentioned problems. The existing ontologies for IoT, despite its many advantages, are not widely used by developers because it has not overcome the relatively slow drawbacks of increasing complexity and searching for development. To complement this, this study uses the IoT-Lite ontology introduced by W3C as a model and a semantic web service for automatic system retrieval. 3D camera, GPS, and 9-axis sensor, and IoT-Lite designed by IoT-Lite technique are integrated with the semantic technique and implemented directly.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.6
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• pp.281-288
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• 2017

In Smart-cities, various types of integrated services must be linked to provide services to applications. Therefore, flexibility must be ensured between services so that various services can be efficiently provided. In order to secure the flexibility among services, it is very important to have a function to dynamically discover and invoke a desired service by searching for a semantic service by reflecting a recognized context through real-time context-aware in smart-cities. To date, quite a number of semantic service discovery techniques have been developed. However, they have not been verified as suitable for use in the smart-city domain. In this study, we tried to verify the existing ones to use a suitable one. We tested most of existing semantic service discovery techniques, but we found that none of them is suitable to our research. Therefore, we developed our own semantic service discovery technique. This paper introduces our work and presents the performance evaluation results that demonstrate that our developed works well and show good performance. For the performance evaluation, the experimental system was actually constructed and the real performance was measured. In the experiment, we implemented the semantic service discovery scenario that dynamically searches and calls the services needed to provide fire accident management services in smart cities.