• Journal of the Korean Society for information Management
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• v.7 no.1
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• pp.79-95
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• 1990

A retrieval technique was defined as a technique for comparing the document representations. So this study classified retrieval technique in terms of the charactristics of the retrieved set of documents and the representations that are used. The distinction is whether the set of retrieved documents contains only documents whose representations are an exact match with the query, or a partial match with query. For a partial match, the set of retrieved document will include also those that are an exact match with the query. Boolean-logic as one of the exact match retrieval techniques is in current in most of the large operational information retrieval systems despite of its problems and limitatlons. Partial match as an alternative technique has also various problems. Existing information retrieval systems are successful in aSSisting the user whose needs are well- defined (e.g. Boolean-logic), to retrieve relevant documents but it should be successful in providing retrieval assistance to the browser whose information requirements is ill-defined.

• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.111-127
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• 2003

The purpose of this study is to ascertain whether event tracking is more effective in event retrieval than information filtering. This study examined the two techniques for event retrieval to suggest the more effective one. The event-retrieval performances of the event tracking technique based on a kNN classifier and the query-based information filtering technique were compared. Two event tracking experiments, one with the static training set and the other with the dynamic training set , were carried out. Two information filtering experiments, one with initial queries and the other with refined queries, were also carried out to evaluate the event-retrieval effectiveness. We found that the event tracking technique with the static training set performed better than on with the dynamic training set. It was also found that the information fitering technique using intial queries performed better than one using the refined queries. In conclusion, the comparison of the best cases of event tracking and information filtering revealed that the information filtering technique outperformed the event tracking technique in event retrieval.

• Journal of Korean Library and Information Science Society
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• v.31 no.2
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• pp.279-302
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• 2000

This study is to develop a new automatic system for the Korean thesaurus browser by which we can automatically control all the processes of searching queries such as, representation, generation, extension and construction of searching strategy and feedback searching. The system in this study is programmed by Delphi 4.0(PASCAL) and consists of database system, automatic indexing, clustering technique, establishing and expressing thesaurus, and automatic information retrieval technique. The results proved by this system are as follows: 1)By using the new automatic thesaurus browser developed by the new algorithm, we can perform information retrieval, automatic indexing, clustering technique, establishing and expressing thesaurus, information retrieval technique, and retrieval feedback. Thus it turns out that even the beginner user can easily access special terms about the field of a specific subject. 2) The thesaurus browser in this paper has such merits as the easiness of establishing, the convenience of using, and the good results of information retrieval in terms of the rate of speed, degree, and regeneration. Thus, it t m out very pragmatic.

• Journal of the Korean Society for information Management
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• v.15 no.1
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• pp.129-148
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• 1998

The objective of this study is to develop a useful relevance feedback retrieval technique that can be applied to the current Boolean retrieval system. A feedback retrieval technique based on user model is recommended here to achieve this objective. To prove the usefulness of this feedback retrieval technique, two enhanced Boolean retrieval models including DNF model and P-norm model were evaluated first through retrieval effectiveness experiments. After selecting DNF model as the retrieval model, two feedback retrieval experiments were performed using initial and extended user models. It is proved that the feedback retrieval based on user model can greatly enhance the effectiveness of a Boolean retrieval system with a small modification.

• Journal of Korean Library and Information Science Society
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• v.30 no.3
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• pp.427-456
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• 1999

This paper deals with the problems of information retrieval through full-test database which arise from both the deficiency of searching strategies or methods by information searcher and the difficulties of query representation, generation, extension, etc. In oder to solve these problems, we should use automatic retrieval instead of manual retrieval in the past. One of the ways to make the gap narrow between the terms by the writers and query by the searchers is that the query should be searched with the terms which the writers use. Thus, the preconditions which should be taken one accorded way to solve the problems are that all areas of information retrieval such as should taken one accorded way to solve the problems are that all areas of information retrieval such as contents analysis, information structure, query formation, query evaluation, etc. should be solved as a coherence way. We need to deal all the ares of automatic information retrieval for the efficiency of retrieval thought this paper is trying to solve the design of thesaurus browser. Thus, this paper shows the theoretical analyses about the form of information retrieval, automatic indexing, clustering technique, establishing and expressing thesaurus, and information retrieval technique. As the result of analyzing them, this paper shows us theoretical model, that is to say, the thesaurus browser by clustering algorithm. The result in the paper will be a theoretical basis on new retrieval algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.143-149
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• 2010

In ubiquitous environment, information retrieval using collaborative filtering is a popular technique for reducing information overload. Collaborative filtering systems can produce personal recommendations by computing the similarity between your preference and the one of other people. We integrate the collaboration filtering method and context-aware information retrieval method. The proposed method enables to find some relevant information to specific user's contexts. It aims to makes more effective information retrieval to the users. The proposed method is conceptually comprised of two main tasks. The first task is to tag context tags by automatic tagging technique. The second task is to recommend items for each user's contexts integrating collaborative filtering and information retrieval. We describe a new integration method algorithm and then present a u-commerce application prototype.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.324-328
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• 2012

With the recent advances in information retrieval, cross-media retrieval has been attracting lot of attention, but several issues remain problems such as constructing effective correlations, calculating similarity between different kinds of media objects. To gain better cross-media retrieval performance, it is crucial to mine the semantic correlations among the heterogeneous multimedia data. This paper introduces a new method for cross-media retrieval which uses ontology to organize different media objects. The experiment results show that the proposed method is effective in cross-media retrieval.

• Journal of Korean Library and Information Science Society
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• v.31 no.1
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• pp.229-258
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• 2000

The growth of digital image an video archives is increasing the need for tools that efficiently search through large amount of visual dta. Retrieval of visual data is important issue in multimedia database. We are using contented-based visual data retrieval method for efficient retrieval of visual data. In this paper, we introduced fundamental techniques using characteristic values of image data and indexing techniques required for content-based visual retrieval. In addition we introduced content-based visual retrieval system for use of digital library.

• Journal of the Korean Society for Library and Information Science
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• v.15
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• pp.197-224
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• 1988

The kernel technique in game theory is introduced and modified in the notion of super kernel, which creates searching maps through the hierarchic clustering technique. The results show more Improved retrieval efficiency in terms of precision and recall.