• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.27-34
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• 2001

Utterance verification is used in variable vocabulary word recognition to reject the word that does not belong to in-vocabulary word or does not belong to correctly recognized word. Utterance verification is an important technology to design a user-friendly speech recognition system. We propose a new utterance verification algorithm for no-training utterance verification system based on the minimum verification error. First, using PBW (Phonetically Balanced Words) DB (445 words), we create no-training anti-phoneme models which include many PLUs(Phoneme Like Units), so anti-phoneme models have the minimum verification error. Then, for OOV (Out-Of-Vocabulary) rejection, the phoneme-based confidence measure which uses the likelihood between phoneme model (null hypothesis) and anti-phoneme model (alternative hypothesis) is normalized by null hypothesis, so the phoneme-based confidence measure tends to be more robust to OOV rejection. And, the word-based confidence measure which uses the phoneme-based confidence measure has been shown to provide improved detection of near-misses in speech recognition as well as better discrimination between in-vocabularys and OOVs. Using our proposed anti-model and confidence measure, we achieve significant performance improvement; CA (Correctly Accept for In-Vocabulary) is about 89％, and CR (Correctly Reject for OOV) is about 90％, improving about 15-21％ in ERR (Error Reduction Rate).

• Journal of Oriental Neuropsychiatry
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• v.22 no.3
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• pp.101-113
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• 2011

Objectives : Trend of R&D of herbal medicine for dementia treatment was examined based on the quantitative information analysis for establishing the national strategy of research on dementia treatment with oriental medicine. Methods : Definition was made to clarify the technology for development of herbal medicine for dementia treatment. Based on the initial keyword provided by experts in the field, queries were compounded to conduct search in the search engines of WoS and DWPI. The raw data (papers or patents) extracted from the initial search were examined by expert-review before objects of analysis were determined. Then, the accumulated data was analyzed in terms of year, country and organization, which led to examination of the trend of R&D. And the research performance evaluation for dementia treatment technologies was also made in terms of country, organization and researcher based on the forward citation analysis. The international cooperation intensity was examined on the basis of analysis of network by researcher before analysis results were put together to select lead researchers. Results : According to the quantitative information analysis of 1,330 articles that were selected as analysis objects, the number of papers on natural products research for dementia treatment has increased by around 4.6 times in recent five years. This indicates that the intensive studies have been underway recently. It was found to be the US that had the highest level in research filed of herbal medicine for dementia treatment and the highest capacity of international cooperation for that purpose. On the contrary, Korea had the share of papers at 5.1%, the number of countries in cooperation research at 8, and the article quality index at 0.40, showing that the qualitative level was insufficient, compared to the quantitative outcome. In particular, Korea was found to have no intensity of international cooperation among researchers. In case of patent, the results of information analysis of 305 patents selected as analysis objects demonstrated that China had the highest share while Korea had the very low frequency of patent application quantitatively. Conclusions : In this study, the research to develop herbal medicine for dementia treatment has recently drawn much attention that has spread around the globe. Therefore, these results suggest establishing the strategy to develop technology for dementia treatment with oriental medicine in the future based on quantitative information analysis.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.23-33
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• 2019

Research and development(R&D) activities consist of analytical survey and state-of-the-art report writing for technical information. As R & D activities become more concrete, it often happens that they refer to related technical documents that were created in previous steps or created in previous similar projects. This paper proposes a research-task based reuse recommendation framework(RTRF), which is a reuse recommendation system that enables researchers to efficiently reuse the existing artifacts. In addition to the existing keyword-based retrieval and reuse, the proposed framework also provides reusable information that researchers may need by recommending reusable artifacts based on task similarity; other developers who have a similar task to the researcher's work can recommend reusable documents. A case study was performed to show the researchers' efficiency in the process of writing the technology trend report by reusing existing documents. When reuse is performed using RTRF, it can be seen that documents of different stages or other research fields are reused more frequently than when RTRF is not used. The RTRF may contribute to the efficient reuse of the desired artifacts among huge amount of R&D documents stored in the repository.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.33-42
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• 2021

As smartphone-based tourism platforms have become active, policy establishment and service enhancement using review data are being made in various fields. In the case of the preceding studies using tourism review data, most of the studies centered on domestic tourists were conducted, and in the case of foreign tourist studies, studies were conducted only on data collected in some languages and text mining techniques. In this study, 3,515 review data written by foreigners were collected by designating the "Daegu attractions" keyword through the online review site. And LDA-based topic modeling was performed to derive tourism topics. The spatial approach through global and local spatial autocorrelation analysis for each topic can be said to be different from previous studies. As a result of the analysis, it was confirmed that there is a global spatial autocorrelation, and that tourist destinations mainly visited by foreigners are concentrated locally. In addition, hot spots have been drawn around Jung-gu in most of the topics. Based on the analysis results, it is expected to be used as a basic research for spatial analysis based on local government foreign tourism policy establishment and topic modeling. And The limitations of this study were also presented.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.59-72
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• 2011

The research of psychological supporting systems as safety and welfare for disaster victims damaged psychologically as well as physically by a sudden disaster to return to effectively their social life has been carried. The domestic National Emergency Management Agency(NEMA) is operating the Disaster Victim Psychology Support Center that helps with curing damaged psychology and studies the transmission system of psychology management services, the classification of victims for disaster psychology support, and emergency consultation method to systemically support disaster psychology management. However, current psychology supporting centers provide the simple information for supporting centers such as medical and social welfare organizations. The development research of IT-based management systems to obtain needed information to construct the proposed systems curing psychological damage is still primitive step. Therefore, this paper shall propose a GIS-based integrated management system for victims and managers to effectively share related information one another and to return to victims' social life as soon as possible. Also, we implement a simple prototype system based on the Web. The proposed system supports the spatial search and statistical analysis based on map as well as keyword search, because having the location information on disaster victims, damage occurrence places, welfare and medical institutions, and psychological supporting centers. In addition, this system has the advantage reducing the frequency of disaster damage by providing aids in making efficient policy systems for the managers.

• The Journal of Korean society of community based occupational therapy
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• v.6 no.1
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• pp.49-60
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• 2016

Objective : By organizing systematically the study case that use Robot Therapy as intervention tool according to PICO (Patient, Intervention, Comparison, Outcome), This study aims to investigate the domestic Robot Therapy's present condition. Methods : We searched 710 pieces of domestic scientific journal and master's thesis during the past nine years in 'Research Information Sharing Service' and 'National Digital Science Library' database using the keyword 'Robot therapy'. We finally chose 15 pieces of domestic scientific journal and master's thesis among the domestic studies that based on the full text which is affordable and used robot by therapeutic intervention tool. Chosen studies were layed out by PICO that could organize the resources systematically. Results : The quality of study tool was used to the method of evidence-based study level of 5 step classification. More than three stages of quality level study was 13. Result of dividing the studies using robot therapy by intervention field, language, lower extremity(gait), cognition, development and study for the region of the upper extremity of five is advancing. Conclusion : Nationally, the robot therapy has been used in various area that include the upper extremity and lower extremity's intervention of language, cognition, growth and others. We hope that this study for baseline data will be utilized in various area engaging to domestic robot therapy.

• Journal of KIISE:Databases
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• v.34 no.4
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• pp.283-303
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• 2007

Recently, the study of efficient way to store and retrieve enormous music data is becoming the one of important issues in the multimedia database. Most general method of MIR (Music Information Retrieval) includes a text-based approach using text information to search a desired music. However, if users did not remember the keyword about the music, it can not give them correct answers. Moreover, since these types of systems are implemented only for exact matching between the query and music data, it can not mine any information on similar music data. Thus, these systems are inappropriate to achieve similarity matching of music data. In order to solve the problem, we propose an Efficient Query-By-Humming System (EQBHS) with a content-based indexing method that efficiently retrieve and store music when a user inquires with his incorrect humming. For the purpose of accelerating query processing in EQBHS, we design indices for significant melodies, which are 1) frequent melodies occurring many times in a single music, on the assumption that users are to hum what they can easily remember and 2) melodies partitioned by rests. In addition, we propose an error tolerated mapping method from a note to a character to make searching efficient, and the frequent melody extraction algorithm. We verified the assumption for frequent melodies by making up questions and compared the performance of the proposed EQBHS with N-gram by executing various experiments with a number of music data.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.369-380
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• 2004

In this paper, we propose a web page weighting scheme based on WordNet-based collaborative evaluation and hyperlink to improve the precision of web search engine. Generally search engines use keyword matching to decide web page ranking. In the information retrieval from huge data such as the Web, simple word comparison cannot distinguish important documents because there exist too many documents with similar relevancy. In this paper, we implement a WordNet-based user interface that helps to distinguish different senses of query word, and constructed a search engine in which the implicit evaluations by multiple users are reflected in ranking by accumulating the number of clicks. In accumulating click counts, they are stored separately according to lenses, so that more accurate search is possible. Weighting of each web page by using collaborative evaluation and hyperlink is reflected in ranking. The experimental results with several keywords show that the precision of proposed system is improved compared to conventional search engines.

• The Journal of Society for e-Business Studies
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• v.15 no.3
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• pp.131-145
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• 2010

Until now, popular paradigms to provide e-catalog documents that are adapted to users' needs are keyword search or collaborative filtering based recommendation. Since users' queries are too short to represent what users want, it is hard to provide the users with e-catalog documents that are adapted to their needs(i.e., queries and preferences). Although various techniques have beenproposed to overcome this problem, they are based on index term matching. A conventional Bayesian belief network-based approach represents the users' needs and e-catalog documents with their corresponding concepts. However, since the concepts are the index terms that are extracted from the e-catalog documents, it is hard to represent relationships between concepts. In our work, we extend the conventional Bayesian belief network based approach to represent users' needs and e-catalog documents with a concept network which is derived from the Web directory. By exploiting the concept network, it is possible to search conceptually relevant e-catalog documents although they do not contain the index terms of queries. Furthermore, by computing the conceptual similarity between users, we can exploit a semantic collaborative filtering technique for recommending e-catalog documents.