• Journal of Korea Multimedia Society
• /
• v.19 no.8
• /
• pp.1498-1504
• /
• 2016

The progress of mobile computing technology is bringing a large amount of multimedia contents such as image. Thus, we need an image retrieval system which searches semantically relevant image. In this paper, we propose a semantic image annotation and retrieval in mobile environments. Previous mobile-based annotation approaches cannot fully express the semantics of image due to the limitation of current form (i.e., keyword tagging). Our approach allows mobile devices to annotate the image automatically using the context-aware information such as temporal and spatial data. In addition, since we annotate the image using RDF(Resource Description Framework) model, we are able to query SPARQL for semantic image retrieval. Our system implemented in android environment shows that it can more fully represent the semantics of image and retrieve the images semantically comparing with other image annotation systems.

• Journal of the Korean Society for Library and Information Science
• /
• v.21
• /
• pp.249-290
• /
• 1991

Theoretical developments in the information retrieval have offered a number of alternatives to traditional Boolean retrieval. Probability theory and fuzzy set theory have played prominent roles here. Fuzzy set theory is an attempt to generalize traditional set theory by permitting partial membership in a set and this means recognizing different degrees to which a document can match a request. In this study, an experimentation of a document retrieval system using the fuzzy relation matrix of the keywords is described and the results are offered. The queries composed of keywords and Boolean operaters AND, OR, NOT were processed in the retrieval method, and the method was implemented on the PC of 32bit level (30 MHz) in an experimental system. The measurement of the recall ratio and precision ratio verified the effectiveness of the proposed fuzzy relation matrix of keywords and retrieval method. Compared to traditional crisp method in the same document database, the recall ratio increased $10\%$ high although the precision ratio decreased slightly. The problems, in this experiment, to be resolved are first, the design of the automatic data input and fuzzy indexing modules, through which the system . can have the ability of competition and usefulness. Second, devising a systematic procedure for assigning fuzzy weights to keywords in documents and in queries.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.240-245
• /
• 1998

Fuzzy information retrieval which uses the concept of fuzzy relation is able to retrieve documents in the way based on not morphology but semantics, dissimilar to traditional information retrieval theories. Fuzzy information retrieval logically consists of three sets : the set of documents, the set of terms and the set of queries. It maintains a fuzzy relational matrix which describes the relationship between documents and terms and creates a thesaurus with fuzzy relational product. It also provides the user with documents which are relevant to his query. However, there are some problems on building a thesaurus with fuzzy relational product such that it has big time complexity and it uses fuzzy values to be processed with flating-point. Actually, fuzzy values have to be expressed and processed with floating-point. However, floating-point operations have complex logics and make the system be slow. If it is possible to exchange fuzzy values with binary values, we could expect sp eding up building the thesaurus. In addition, binary value expressions require just a bit of memory space, but floating -point expression needs couple of bytes. In this study, we suggest a new method of building a thesaurus, which accelerates the operation of the system by pre-applying an ${\alpha}$-cut. The experiments show the improvement of performance and reliability of the system.

• Journal of the Korean Society for Library and Information Science
• /
• v.34 no.4
• /
• pp.69-95
• /
• 2000

The purpose of this study is to derive system design factors and to analyze user needs of university library for design of user-centered information retrieval system. The result of this study can be summarized as follows: First, the concept of 'users-centered' in digital environment where the supporting role of intermediaries is growing bigger than before in the interaction with remote information retrieval system can be defined as the new concept of 'expansion of knowledge'. Second, 6 kinds of system design factors derived for user-centered information retrieval system design of the university libraries. Third, The user needs that examined and analyzed through the questionnaires made by user-centered approach according to the design factors should be considered for system design.

• Smart Media Journal
• /
• v.2 no.3
• /
• pp.17-22
• /
• 2013

The growth of the propagated NFC provides the various services with respect to internet applications, which it can be predicted from the simple internet services to the privated services. This paper proposes the clustering of information retrieval system model using NFC tag of access information for utilizing the similar information of the tag. The proposed model can search the similar information of the tag using the access information of NFC tag. In addition, it can cluster the similar retrieval information into topic cluster for utilizaing users.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.4
• /
• pp.95-102
• /
• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency md requires many efforts of system administrator or annotator because of imperfect automatic processing. In this paper, we propose semantics-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method and optimized comparison area extracting that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantics-based retrieval.

• Journal of the Korean Society for information Management
• /
• v.22 no.2 s.56
• /
• pp.41-56
• /
• 2005

For the purpose of extending the Web that is able to understand and process information by machine, Semantic Web shared knowledge in the ontology form. For exquisite query processing, this paper proposes a method to use semantic relations in the ontology as relevance feedback information to query expansion. We made experiment on pharmacy domain. And in order to verify the effectiveness of the semantic relation in the ontology, we compared a keyword based document retrieval system that gives weights by using the frequency information compared with an ontology based document retrieval system that uses relevant information existed in the ontology to a relevant feedback. From the evaluation of the retrieval performance. we knew that search engine used the concepts and relations in ontology for improving precision effectively. Also it used them for the basis of the inference for improvement the retrieval performance.

• Journal of the Korean Dietetic Association
• /
• v.15 no.3
• /
• pp.286-297
• /
• 2009

Studies based on food analysis or food databases use the national standard food database. Although Internet information services are increasing gradually, users are only able to get definitive and profitable information using standard food terms. Until now, it has been uncommon to find food retrieval services that include users' regional or historical characteristics. Thus, this study introduces a prototype for Food and Dish Synonym Retrieval (NutriSyn) that includes synonyms and related words. The environments which NutriSyn was implemented were Linux for the server operating system, the Microsoft Windows series for the users' operating system and Apache for a web server. The development languages used are PHP, JavaScript and HTLM with a MySQL database. Users can access NutriSyn using Internet browsers. The main menu items are (1) Food Synonym DB, (2) Dish Synonym DB, (3) Food Information DB, (4) Dish Information DB, and (5) Food and Menu Synonym Retrieval. This system is expected to be a useful tool for food experts and interdisciplinary research.

• The Journal of Society for e-Business Studies
• /
• v.14 no.3
• /
• pp.15-37
• /
• 2009

This study presents a new retrieval system developed to consider various preferential requirements for buyers in the real estate market. The paper analyses essential factors affecting the price of real estate and then a set of factors are classified by region-related factor and individual-related factor. After endowing the buyer's selected factors with weights in the retrieval system, the optimal solutions have been drawn by comparing with the others through an entropy measure of Multi-attribute Decision Making. This retrieval system is applied to the Busan real estate market to estimate the solutions of retrieval. Evaluation results indicate that the retrieval system can provide useful information to analyse the price determination factors of real estate, as well as to save the searching cost of the buyers.

• Journal of Korea Multimedia Society
• /
• v.13 no.8
• /
• pp.1245-1255
• /
• 2010

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.