• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1807-1824
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• 2015

As the technologies advance, mobile peer-to-peer (MP2P) networks or systems become one of the major ways to share resources and information. On such a system, the information retrieval (IR), including the development of scalable infrastructures for indexing, becomes more complicated due to a huge increase on the amount of information and rapid information change. To keep the systems on MP2P networks more reliable and consistent, the index structures need to be updated frequently. For a semantic IR system, the index structure is even more complicated than a classic IR system and generally has higher update cost. The most well-known indexing technique used in semantic IR systems is Latent Semantic Indexing (LSI), of which the index structure is generated by singular value decomposition (SVD). Although LSI performs well, updating the index structure is not easy and time consuming. In an MP2P environment, which is fully distributed and dynamic, the update becomes more challenging. In this work, we consider how to update the sematic index generated by LSI and keep the index consistent in the whole MP2P network. The proposed Concept Space Update (CSU) protocol, based on distributed 2-Phase locking strategy, can effectively achieve the objectives in terms of two measurements: coverage speed and update cost. Using the proposed effective synchronization mechanism with the efficient updates on the SVD, re-computing the whole index on the P2P overlay can be avoided and the consistency can be achieved. Simulated experiments are also performed to validate our analysis on the proposed CSU protocol. The experimental results indicate that CSU is effective on updating the concept space with LSI/SVD index structure in MP2P semantic IR systems.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.147-156
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• 2006

Event logging plays increasingly an important role in system and network management, and syslog is a de-facto standard for logging system events. However, due to the semi-structured features of Common Log Format data most studies on log analysis focus on the frequent patterns. The extensible Markup Language can provide a nice representation scheme for structure and search of formatted data found in syslog messages. However, previous XML-formatted schemes and applications for system logging are not suitable for semantic approach such as ranking based search or similarity measurement for log data. In this paper, based on ranked keyword search techniques over XML document, we propose an XML tree structure through a new data modeling approach for syslog data. Finally, we show suitability of proposed structure for semantic retrieval.

• Journal of the Korean Society for information Management
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• v.26 no.4
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• pp.7-34
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• 2009

Structures of stories, paragraphs, and sentences and inferences applied to indexing and searching were studied to construct the full-text and sentence retrieval system for storytelling. The system designed the database of stories, paragraphs, and sentences and the knowledge-base of inference rules to aid to write the story. The Knowledge-base comprised the files of story frames, paragraph scripts, and sentence logics made by mark-up languages like SWRL etc. able to operate in semantic web. It is necessary to establish more precise indexing language represented the sentences and to create a mark-up languages able to construct more accurate inference rules.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.315-322
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• 2008

It is important to retrieve effectively the visual media such as pictures and video in the internet, especially to the application areas such as electronic art museum, e-commerce, and internet shopping malls. It is also needed in these areas to have content-based or even semantic-based multimedia retrieval instead of simple keyword-based retrieval. In our earlier research, we proposed a semantic-based visual media retrieval framework for the effective retrieval of the visual media from the internet. It uses visual media metadata and ontology based on the web service to achieve the semantic-based retrieval. In this research, there are more than one visual media service providers and one central service broker. As a preliminary step to the visual media data retrieval, a method is proposed to retrieve the service providers effectively. The method uses the structure of the ontology tree to obtain the providers and their rankings. It also uses the size of sub nodes and child nodes in the tree. It measures the rankings of providers more effectively than previous method. The experimental results show the accuracy of the method while keeping compatible speed against the existing method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.1
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• pp.114-121
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• 2008

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. In this paper, we propose semantic-based video retrieval system for Environment Education Contents 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 form 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 that propose. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.

• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.573-580
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• 2004

As the modern techniques have improved, people intend to store and manage the information on the web. Especially, it is the image data that is given a great deal of weight of the information because of the development of the scan and popularization of the digital camera and the cell-phone's camera. However, most image retrieval systems are still based on the text annotations while many images are creating everyday on the web. In this paper, we suggest the new approach for the semantic image retrieval using the RDF metadata based on the representation of the spatial relationships. For the semantic image retrieval, firstly we define the new vocabularies to represent the spatial relationships between the objects in the image. Secondly, we write the metadata about the image using RDF and new vocabularies. Finally. we could expect more correct result in our image retrieval system.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.789-796
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• 2005

Because existing information retrieval systems, in particular library retrieval systems, use 'exact keyword matching' with user's query, they present user with massive results including irrelevant information. So, a user spends extra effort and time to get the relevant information from the results. Thus, this paper will propose SULRM a Retrieval Model using Subject Classification Table, User profile, and LSI(Latent Semantic Indexing), to provide more relevant results. SULRM uses document filtering technique for classified data and document ranking technique for non-classified data in the results of keyword-based retrieval. Filtering technique uses Subject Classification Table, and ranking technique uses user profile and LSI. And, we have performed experiments on the performance of filtering technique, user profile updating method, and document ranking technique using the results of information retrieval system of our university' digital library system. In case that many documents are retrieved proposed techniques are able to provide user with filtered data and ranked data according to user's subject and preference.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.2
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• pp.141-160
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• 2011

This study suggested knowledge base and search engine for the libraries that have the largescaled data. For this purpose, 3 components of knowledge bases(triple ontology, concept-based knowledge base, inverted file) were constructed and 3 search engines(search engine JENA for rule-based reasoning, Concept-based search engine, keyword-based Lucene retrieval engine) were implemented to measure their performance. As a result, concept-based retrieval engine showed the best performance, followed by ontology-based Jena retrieval engine, and then by a normal keyword search engine.

• Journal of Korean Library and Information Science Society
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• v.22
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• pp.1-26
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• 1995

Indexes, especially subject indexes, are major tools for information retrieval. To enhance the retrieval effectiveness of subject indexes, the semantic and syntactic relationships of indexing languages are very important elements. This paper examines the afore-mentioned relationships, based on purely the syntax and semantics of Korean language. The outlines of this study are as follows: 1. The characteristics and usages of controlled vocabularies, particularly subject headings lists and thesaury, are reviewed. 2. The semantic relationships, such as equivalence, hierarchical and associative relationships, are defined, and their categories are investigated in detail. Accordingly, the usages of 'See' and 'See also' references are suggested circumstantially. 3. The syntactic relationships are also examined. Particularly, for the syntactic relationships of multiword indexing terms, two kinds of subject entry formats are compared. Since it is more rational for subject headings organized by the principle of context-dependency, the two-fine entry format is recommended for subject indexes. 4. Computerized production techniques of 'See' and 'See also' reference for the semantic relationships of indexing terms are presented. 5. Computerized production techniques of subject indexes representing the syntactic relationships of indexing terms are also presented.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.957-962
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• 2007

본 논문에서 제안하는 정보 검색기는 일반적인 불리언(Boolean) 질의를 통해서 정보를 검색하는 것이 아니라, 문장으로 입력된 질의형태의 패턴을 분석하여 그에 맞는 정보를 직접 제공하는 것에 목적을 둔다. 이를 위해 어휘 의미 패턴(Lexical Semantic Pattern)과 온톨로지(Ontology) 기술이 정보검색기 개발에 적용되었다. 제안된 시스템에서는 다양한 형태로 표현된 문장 질의를 어휘 의미 패턴을 사용해서 문장의 질의 패턴을 추출하고 사용자 질의를 하나의 온톨로지(Ontology) 추론 질의와 매칭함으로써 질의에 대한 정확한 해답을 추출할 수 있다. 또한, 자연어 문장 입력에 대한 검색 질의 생성기를 구축하고 온톨로지로 표현된 지식을 사용하여 정보검색기 질의를 자동으로 확장함으로써 더욱 정확한 정보 검색 결과를 만들어 낼 수 있다.