• The KIPS Transactions:PartA
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• v.17A no.5
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• pp.229-236
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• 2010

With an increasing number of documents in the Internet or enterprises, it becomes crucial to efficiently support users' queries on those documents. In that situation, the full-text search technique is accepted in general, because it can answer uncontrolled ad-hoc queries by automatically indexing all the keywords found in the documents. The size of index files made for full-text searches grows with the increasing number of indexed documents, and thus the disk cost may be too large to process multi-keyword queries against those enlarged index files. To solve the problem, we propose both of the index file structure and its management scheme suitable to the processing of multi-keyword queries against a large volume of index files. For this, we adopt the structure of inverted-files, which are widely used in the multi-keyword searches, as a basic index structure and modify it to a hierarchical structure for join operations and ranking operations performed during the query processing. In order to save disk costs based on that index structure, we dynamically store in the main memory the results of join operations between two keywords, if they are highly expected to be entered in users' queries. We also do performance comparisons using a cost model of the disk to show the performance advantage of the proposed scheme.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.11
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• pp.367-376
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• 2020

The fourth industrial revolution will greatly contribute to the entry of objects into an intelligent society through technologies such as big data and an artificial intelligence. Through the revolution, we were able to understand human behavior and awareness, and through the use of an artificial intelligence, we established ourselves as a key tool in various fields such as medicine and science. However, the fourth industrial revolution has a negative side with a positive future. In this study, an analysis was conducted using text mining techniques based on unstructured big data collected through social media. We wanted to look at keywords related to the fourth industrial revolution by year (2016, 2017 and 2018) and understand the meaning of each keyword. In addition, we understood how the keywords related to the Fourth Industrial Revolution changed with the change of the year and wanted to use R to conduct a Keyword Analysis to identify the recognition flow closely related to the Fourth Industrial Revolution through the keyword flow associated with the Fourth Industrial Revolution. Finally, people's perceptions of the fourth industrial revolution were identified by looking at the positive and negative feelings related to the fourth industrial revolution by year. The analysis showed that negative opinions were declining year after year, with more positive outlook and future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.5
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• pp.35-44
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• 2009

To protect sensitive personal information, data will be stored in encrypted form. However in order to retrieve these encrypted data without decryption, there need efficient search methods to enable the retrieval of the encrypted data. Until now, a number of searchable encryption schemes have been proposed but these schemes are not suitable when dynamic users who have the permission to access the data share the encrypted data. Since, in previous searchable encryption schemes, only specific user who is the data owner in symmetric key settings or has the secret key corresponding to the public key for the encrypted data in asymmetric key settings can access to the encrypted data. To solve this problem, Stephen S. Yau et al. firstly proposed the controlled privacy preserving keyword search scheme which can control the search capabilities of users according to access policies of the data provider. However, this scheme has the problem that the privacy of the data retrievers can be breached. In this paper, we firstly analyze the weakness of Stephen S. Yau et al.'s scheme and propose privacy preserving keyword search with access control. Our proposed scheme preserves the privacy of data retrievers.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.119-133
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• 2011

With the advent of Web 2.0, the use of RESTful web services is expected to overtake that of the traditional SOAP-based web services. Recently, the growing number of RESTful web services available on the web raises the challenging issue of how to locate the desired web services. However, the existing keyword searching method is insufficient for the bad recall and the bad precision. In this paper, we propose a novel building semantic ontology method which employs both the clustering technique based on association rules and the semantic analysis technique based on patterns. From this method, we can generate ontologies automatically, reduce the burden of semantic annotations, and support more efficient web services search. We ran our experiments on the subset of 168 RESTful web services downloaded from the PregrammableWeb site. The experimental results show that our method achieves up to 35% improvement for recall performance, and up to 18% for precision performance compared to the existing keyword searching method.

• Journal of Korean Library and Information Science Society
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• v.45 no.1
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• pp.103-123
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• 2014

This study investigated general problems concerning the tourism field in the KDC 6th edition based comparative analysis academic characteristics and classification system, and suggested on some ideas for the improvements of them. Results of the study are summarized as follows. First, academic field of tourism is generally divided into a general tourism, tourists, tourism attraction, and tourism media, but classification system of tourism is limited to parts of tourism attraction and a general tourism. Tourism attraction and tourism media are dispersed among the subject. Second, I analyzed on tourism from the collection database at the National Library of Korea. Based on analysis of the data. the keyword frequency of tourism management, type, development, psychology, industry, and convention etc. was relatively high. Third, modified classification of items was basically performed through the academic characteristics of the tourism and the keyword analysis, and maintaining the existing KDC classification system caused less confusion as much as possible. Also, based on this matter was added to the relative indexes.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1419-1425
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• 2017

The ultimate goal of legal knowledge search is to obtain optimal legal information based on laws and precedent. Text mining research is actively being undertaken to meet the needs of efficient retrieval from large scale data. A typical method is to use a word embedding algorithm based on Neural Net. This paper demonstrates how to search relevant information, applying Korean law information to word embedding. First, we extracts reference laws from precedents in order and takes reference laws as input of Law2Vec. The model learns a law by predicting its surrounding context law. The algorithm then moves over each law in the corpus and repeats the training step. After the training finished, we could infer the relationship between the laws via the embedding method. The search performance was evaluated based on precision and the recall rate which are computed from how closely the results are associated to the search terms. The test result proved that what this paper proposes is much more useful compared to existing systems utilizing only keyword search when it comes to extracting related laws.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.215-222
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• 2006

The importance of mobile software test is being addressed to improve the productivity and reliability of the software. Test automation technique based on mobile platform is required for effective application of mobile software test. That is, a technique is needed to generate test case for mobile platform API. When test case generated, software productivity and reliability are improved, while test duration and cost are decreased. In this paper, we identified test case generation scope through previous works about test automation, suggested keyword driven method, a test case generation technique on J2ME platform, and recognized that proposed method can be applicable to generating test case based on J2ME platform.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.3
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• pp.35-46
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• 2016

Social network services (SNS) that help to build relationship network and share a particular interest or activity freely according to their interests by posting comments, photos, videos,${\ldots}$ on online communities such as blogs have adopted and developed widely as a social phenomenon. Several researches have been done to explore the pattern and valuable information in social networks data via text mining such as opinion mining and semantic analysis. For improving the efficiency of text mining, keyword-based approach have been applied but most of researchers argued the limitations of the rules of Korean orthography. This research aims to construct a database of non-standard Korean words which are difficulty in data mining such abbreviations, slangs, strange expressions, emoticons in order to improve the limitations in keyword-based text mining techniques. Based on the study of subjective opinions about specific topics on blogs, this research extracted non-standard words that were found useful in text mining process.

• Journal of The Korean Association of Information Education
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• v.4 no.1
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• pp.109-119
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• 2000

In this paper, we design and implement educational system by using active database technique in www environments. The developed system consists of three modules such as user group interface, active-based monitor, and expert group interface. The roles of each module are summarized as follows. The user group interface provides with system accessibility the users who registered in the developed system. The active-based monitor, triggering modules, consists of three sub-modules such as keyword parser, exception handler, and DB access module. Also it manages five items such as keyword index, Q&A DB, user group mailing list, and expert group mailing list. The expect group interface provides answer filling form for the expert who registered in the developed system.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.24-27
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• 2008

As shown in Wikipedia, tagging or cross-linking through major key-words improves the readability of documents. Recently, the Semantic Web rises the importance of social tagging as a key feature of the Web 2.0 and Tag Cloud has emerged as its crucial phenotype. In this paper we provides an efficient method of automated keyword tagging based on controlled term collection, where the computational complexity of O(mN) - if pattern matching algorithm is used - can be reduced to O(mlogN) - if Information Retrieval is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that IR-based tagging speeds up 5.6 times compared with fast pattern matching algorithm.