• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.87-95
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• 2020

The Science and Technology Information Service provided by the Korea Institute of Science and Technology Information (KISTI) is a service designed to allow users to easily and conveniently search and view content that is built similar to the general information service. NDSL is KISTI's core science, technology and information service, providing about 138 million content and having about 93 million page views in a year of 2019. In this paper, various insights were derived through the analysis of how science and technology information such as academic papers, reports and patents provided by NDSL is searched and utilized through web services (https://www.ndsl.kr) and search query words. In addition to general statistics such as the status of content construction, utilization status and utilization methods by type of content, monthly/weekly/time-of-day content usage, content view rate per one-time search by content type, the comparison of the use status of academic papers by year, the relationship between the utilization of domestic academic papers and the KCI index we analyzed the usability of each content type, such as academic papers and patents. We analyzed query words such as the language form of query words, the number of words of query words, and the relationship between query words and timeliness by content type. Based on the results of these analyses, we would like to propose ways to improve the service. We suggest that NDSL improvements include ways to dynamically reflect the results of content utilization behavior in the search results rankings, to extend query and to establish profile information through non-login user identification for targeted services.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.93-107
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• 2007

In this paper, an adaptive range aggregation spatial index method is proposed for spatial range query in ubiquitous sensor networks. As the ubiquitous sensor networks are the new information-oriented paradigm, many energy efficient spatial range query methods in ubiquitous sensor networks environment are studied vigorously. In sensor networks, users can monitor environment scalar data such as temperature and humidity during user defined time and spatial ranges. In order to execute spatial range query efficiently, rectangle based index methods are proposed, such as SPIX. But they define the return path as the opposite of its query transmit path. However, the sensor nodes in queried ranges are closed to each other, they can't aggregate the sensed value in a queried range because their query transmission paths are different. As a result, the previous methods waste energy unnecessarily to aggregate sensing data out of the queried range. In this paper, an adaptive aggregation index method is proposed that can aggregate values in a user defined range adaptively by using its neighbor information. It is shown that sensor power is saved efficiently by using the proposed method over the performance evaluation.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.414-422
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• 2011

IR (Information Retrieval) systems have the methods that compare relationships between query and index to identify document that may be fit to the user's query keyword. However, the methods usually ignore the importance of relations that are not expressed in the query. Therefore, in this study, we describe how to refine the queries' relation from keyword and to reveal the hidden intent. A useful relationship between query and keyword in IR wth studied and we classified the tion fromrelation. Firstfromall, we did researchmrelated on semantic relationship and ontolhiical researchmin foreign and domestic research, and also analyzed semantic network practices, information retrieval technolhiy, extracted and classified the tion fromrelationships s' relasite's real-world datamin whichminformation retrieval technolhiin fare applied. Next, we souiht to solve the problems occurred frequently i' relasituation that searchers tioically face. I' relacurrent search technolhiy, the mesh searchmresult fare poured by simply comparn ina query with index terms. Therefore, the need for an intelligent search fittn inusers' intent is required. The relationships between two queries to re hiddee and identify relasearcher's intent have to be revealed. By analyzn inthe practical cthes s' queries and classifyn inthem into nine kind fromrelationship tion, we proposed the method to design relation revealn inand role namn i, and we have also illustrated limitations of that methods.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.217-236
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• 2013

Ranking thousands of web documents so that they are matched in response to a user query is really a challenging task. For this purpose, search engines use different ranking mechanisms on apparently related resultant web documents to decide the order in which documents should be displayed. Existing ranking mechanisms decide on the order of a web page based on the amount and popularity of the links pointed to and emerging from it. Sometime search engines result in placing less relevant documents in the top positions in response to a user query. There is a strong need to improve the ranking strategy. In this paper, a novel ranking mechanism is being proposed to rank the web documents that consider both the HTML structure of a page and the contextual senses of keywords that are present within it and its back-links. The approach has been tested on data sets of URLs and on their back-links in relation to different topics. The experimental result shows that the overall search results, in response to user queries, are improved. The ordering of the links that have been obtained is compared with the ordering that has been done by using the page rank score. The results obtained thereafter shows that the proposed mechanism contextually puts more related web pages in the top order, as compared to the page rank score.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.585-592
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• 2013

CBIR is an effective tool to search and extract image contents in a large remote sensing image database queried by an operator or end user. However, as imaging principles are different by sensors, their visual representation thus varies among image modality type. Considering images of various modalities archived in the database, image modality difference has to be tackled for the successful CBIR implementation. However, this topic has been seldom dealt with and thus still poses a practical challenge. This study suggests a cross modality CBIR (termed as the CM-CBIR) method that transforms given query feature vector by a supervised procedure in order to link between modalities. This procedure leverages the skill of analyst in training steps after which the transformed query vector is created for the use of searching in target images with different modalities. Current initial results show the potential of the proposed CM-CBIR method by delivering the image content of interest from different modality images. Despite its retrieval capability is outperformed by that of same modality CBIR (abbreviated as the SM-CBIR), the lack of retrieval performance can be compensated by employing the user's relevancy feedback, a conventional technique for retrieval enhancement.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.1-4
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• 2009

이 논문에서는 메타데이터 레지스트리(ISO/IEC 11179: Metadata Registry)들이 가지고 있는 메타데이터 정보를 검색하고, 공유하기 위해 일관성 있는 질의 언어를 제안한다 메타데이터 레지스트리는 국제 표준으로서 메타데이터들을 정의하고 이들을 관리 및 공유를 하기 위해 만들어졌다. 이와 같은 국제 표준을 기반으로 한 메타데이터 레지스트리들이 서지, 환경, 의료 분야 등의 다양한 영역에서 사용되고 있다. 이와 함께 메타데이터 레지스트리를 기반으로 하여 기존에 저장된 메타데이터들을 검색하고, 공유하고, 관리하고자 하는 이슈에 대한 연구가 진행되고 있다. 하지만 현재까지 다양한 분야에 있는 메타데이터 레지스트리가 가지고 있는 정보를 가져오기 위한 표준 인터페이스가 제공되고 있지 않다. 이러한 문제를 해결하기 위한 연구로 SQL에 메타데이터 레지스트리를 위한 공통 연산자들을 추가하여 메타데이터 레지스트리에 존재하는 데이터들을 활용하는 연구가 있다. 하지만 이런 연산자들을 이용하기 위해서는 상용 DBMS 엔진에 추가되어야 하며, 연산자들이 없는 경우 일관된 질의어를 수행할 수 없다는 문제를 가지고 있다. 따라서 이 논문에서는 이와 같은 문제를 해결하기 위해서 국제 표준인 SQL(ISO/IEC 9075) 에서 정의하고 있는 사용자 정의 타입(User-defined types) 을 기반으로 한 일관성 질의 언어를 제안한다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2108-2115
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• 2000

The conventional Boolean retrieval systems based on vector spae model can provide the results of retrieval fast, they can't reflect exactly user's retrieval purpose including semantic information. Consequently, the results of retrieval process are very different from those users expected. This fact forces users to waste much time for finding expected documents among retrieved documents. In his paper, we designed a bayesian SOM(Self-Organizing feature Maps) in combination with bayesian statistical method and Kohonen network as a kind of unsupervised learning, then perform classifying documents depending on the semantic similarity to user query in real time. If it is difficult to observe statistical characteristics as there are less than 30 documents for clustering, the number of documents must be increased to at least 50. Also, to give high rank to the documents which is most similar to user query semantically among generalized classifications for generalized clusters, we find the similarity by means of Kohonen centroid of each document classification and adjust the secondary rank depending on the similarity.

• The Journal of Korean Association of Computer Education
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• v.4 no.2
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• pp.85-95
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• 2001

Since documents on the Web are naturally partitioned into many document databases, the efficient information retrieval process requires identifying the document databases that are most likely to provide relevant documents to the query and then querying the identified document databases. We propose a neural net based user feedback learning mechanism for such an efficient information retrieval. Presented learning mechanism learns about underlying document databases using the relevance feedbacks obtained from user's retrieval experiences. For a given query, the learning mechanism, which is sufficiently trained, discovers the document databases associated with the relevant documents and retrieves those documents effectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.387-388
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• 2012

In order to solve problem which User sometime visits the wrong page with respect to user intention when uses snippet. this paper proposes a new snippet extraction method using fuzzy. The proposed method uses pseudo relevance feedback to expand the use's query. It uses the fuzzy association between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2840-2861
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• 2020

The purpose of this survey-based study is to make an analysis of search engine users' behaviors on the Search Engine Results Pages (SERPs) based on the three demographic characteristics gender, age, and program studying. In this study, a questionnaire was designed with 12 closed-ended questions. Remaining questions other than the demographic characteristic related ones were about "tab", "advertisement", "spelling suggestion", "related query suggestion", "instant search suggestion", "video result", "image result", "pagination" and the amount of clicking results. The questionnaire was used and the data collected were analyzed with the descriptive statistics as well as the inferential statistics. 84.2% of the study population was reached. Some of the major results are as follows: Most of each demographic characteristic category (i.e. female, male, under-20, 20-24, above-24, English computer engineering, Turkish computer engineering, software engineering) have rarely or more click for tab, spelling suggestion, related query suggestion, instant search suggestion, video result, image result, and pagination. More than 50.0% of female category click advertisement rarely; however, for the others, 50.0% or more never click advertisement. For every demographic characteristic category, between 78.0% and 85.4% click 10 or fewer results. This study would be the first attempt with its complete content and design. Search engine providers and researchers would gain knowledge to user behaviors about the usage of the SERPs based on the demographic characteristics.