• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.246-251
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• 2016

Recently, the influence of SNS and online media is rapidly growing with a consequent increase in the interest of marketing using these tools. Blog marketing can increase the ripple effect and information delivery in marketing at low cost by prioritizing keyword search results of influential portal sites. However, because of the tough competition to gain top ranking of search results of specific keywords, long-term and proactive efforts are needed. Therefore, we propose a new method that recommends associated keyword groups with the possibility of higher exposure of the blog. The proposed method first collects the documents of blog including search results of target keyword, and extracts and filters keyword with higher association considering the frequency and location information of the word. Next, each associated keyword is compared to target keyword, and then associated keyword group with the possibility of higher exposure is recommended considering the information such as their association, search amount of associated keyword per month, the number of blogs including in search result, and average writhing date of blogs. The experiment result shows that the proposed method recommends keyword group with higher association.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.71-80
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• 2006

In web search engines, there are two main methods: directory searching and keyword searching. Keyword searching shows high recall rate but tends to come up with too many search results to find which users want to see the pages. Directory searching has also a difficulty to find the pages that users want in case of selecting improper category without knowing the exact category, that is, it shows high precision rates but low recall rates. We designed and implemented a new web search engine to resolve the problems of directory search method. It regards a category as a fuzzy set which contains keywords and calculate the degree of inclusion between categories. The merit of this method is to enhance the recall rate of directory searching by expanding subcategories on the basis of similarity.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.29-35
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• 2023

This paper makes it possible to search videos based on sentence by improving the previous research which automatically generates rich metadata from videos and searches videos by key words. For search by sentence, morphemes are analyzed for each sentence, keywords are extracted, weights are assigned to each keyword, and some videos are recommended by applying a ranking algorithm developed in the previous research. In order to evaluate performance of video search in this paper, a sufficient amount of videos and sufficient number of user experiences are re required. However, in the current situation where these are insufficient, three indirect evaluation methods were used: evaluation of overall user satisfaction, comparison of recommendation scores and user satisfaction, and evaluation of user satisfaction by video categories. As a result of performance evaluation, it was shown that the rich metadata construction and video recommendation implementation in this paper give users high search satisfaction.

• Journal of Oriental Neuropsychiatry
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• v.34 no.3
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• pp.235-245
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• 2023

Objectives: The aim of this study was to analyze public and researcher interests in suicide and related illnesses and acupuncture and acupressure treatment using Google Trends and some electronic databases. Methods: Search results for keywords "suicide," "acupuncture," "acupressure," and several illnesses related to suicide were analyzed in Google Trends from January 2004 to June 2023. Illnesses included anxiety, depression (including major depressive disorder), schizophrenia, bipolar disorder, post- traumatic stress disorder (PTSD), eating disorder (including anorexia nervosa and bulimia nervosa), substance use disorder, autism spectrum disorder, personality disorder (including borderline person- ality disorder), and chronic pain. Search results were extracted using relative search volume (RSV) scores between 0 and 100. Search terms were also searched in online databases, including PubMed, CNKI, and OASIS, to estimate the number of related studies, and descriptive analysis was conducted. Results: Google Trends analysis showed a strong positive correlation between the RSVs of "suicide and depression," "acupuncture and chronic pain," and "acupressure and PTSD." The electronic database search results produced numerous studies published on "suicide and depression," "acupuncture and depression," and "acupressure and anxiety." High interest in "suicide and depression," "acupuncture and chronic pain," and "acupressure and anxiety" was seen among the public and researchers. Interest in "suicide and chronic pain," "acupuncture and eating disorder," and "acupressure and PTSD" was higher in the public than among researchers, while "anxiety and suicide" and "anxiety and acu- puncture" showed opposite trends. Conclusions: The results of this research enable an understanding of public and researcher interest in suicide, acupuncture, acupressure, and suicide-related illnesses. The results also provide a basis for fu- ture research and examining public health implications in Korean medicine.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.47-55
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• 2021

Analysis of research trends in specific subject areas is performed by examining related topics and subject changes by using topic modeling techniques through keyword extraction for most of the literature information (paper, patents, etc.). Unlike existing research methods, this paper extracts topics related to the research topic using the LDA topic modeling technique for the project information of national R&D projects provided by the National Science and Technology Knowledge Information Service (NTIS) in the field of artificial intelligence. By analyzing these topics, this study aims to analyze research topics and investment directions for national R&D projects. NTIS provides a vast amount of national R&D information, from information on tasks carried out through national R&D projects to research results (thesis, patents, etc.) generated through research. In this paper, the search results were confirmed by performing artificial intelligence keywords and related classification searches in NTIS integrated search, and basic data was constructed by downloading the latest three-year project information. Using the LDA topic modeling library provided by Python, related topics and keywords were extracted and analyzed for basic data (research goals, research content, expected effects, keywords, etc.) to derive insights on the direction of research investment.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.754-765
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• 2006

In XML keyword search, a search result is defined as a set of the smallest elements (i.e., least common ancestors) containing all query keywords and a granularity of indexing is an XML element instead of a document. Under the conventional index structure, all least common ancestors produced by the combination of the elements, each of which contains a query keyword, are considered as a search result. In this paper, to avoid unnecessary operations of producing the least common ancestors and reduce query process time, we describe a way to construct a partitioned index composed of several partitions and produce a search result by merging those partitions if necessary. When a search result is restricted to be composed of the least common ancestors whose depths are higher than a given minimum depth, under the proposed partitioned index structure, search systems can reduce the query process time by considering only combinations of the elements belonging to the same partition. Even though the minimum depth is not given or unknown, search systems can obtain a search result with the partitioned index, which requires the same query process time to obtain the search result with non-partitioned index. Our experiment was conducted with the XML documents provided by the DBLP site and INEX2003, and the partitioned index could reduce a substantial amount of query processing time when the minimum depth is given.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.1-23
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• 2023

The purpose of this study is to analyze the characteristics of the integrated search services for integrated libraries operated by local governments in Korea. The target of analysis was integrated libraries operated by 25 local governments in Seoul, and the analysis elements were selected from service functions in 12 areas related to integrated search. The results of the study are as follows. First, the integrated library is an association of public libraries and small libraries in autonomous districts and provides integrated search services. The provided integrated search service function, types of bibliographic information, and facets are not diverse. Second, the records in the search results were mostly item types, not title types. Third, enrichment information supplementing book information consists of book introductions, related information, book-related keywords, and loan-related information. Fourth, integrated search shows the form of integrated OPAC based on integrated catalog DB rather than discovery-type search. It concentrates on providing an integrated search for catalog DBs distributed in public libraries or small libraries in the autonomous district. Fifth, most integrated libraries provide similar service types. Based on these results, improvement plans were proposed for domestic public libraries to expect discovery-type integrated search services.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.39-48
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• 2009

This study reviews the limit of image search by considering on the image search methods related to content-based image retrieval and suggests a user interface for more efficient content-based image retrieval and the ways to utilize image properties. For now, most studies on image search are being performed focusing on content-based image retrieval; they try to search based on the image's colors, texture, shapes, and the overall form of the image. However, the results are not satisfactory because there are various technological limits. Accordingly, this study suggests a new retrieval system which adapts content-based image retrieval and the conventional keyword search method. This is about a way to attribute properties to images using texts and a fast way to search images by expressing the attribute of images as keywords and utilizing them to search images. Also, the study focuses on a simulation for a user interface to make query language on the Internet and a search for clothes in an online shopping mall as an application of the retrieval system based on image attribute. This study will contribute to adding a new purchase pattern in online shopping malls and to the development of the area of similar image search.

• Journal of Information Management
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• v.39 no.4
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• pp.173-186
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• 2008

We propose a mash-up system for searching herb, which can search the herbal information in oriental medicine fields using the various Open APIs. We in particular developed and opened two Open APIs which enable to search papers and projects in oriental medicine fields with the general Open APIs. These Open APIs can share and provide the expert knowledge in oriental medicine fields. The information for a herb in oriental medicine fields has various names and descriptions according to their sources unlike other fields. Thus, it is hard to get the results using one or two keywords such as the general search engines. To solve this problem, we in this paper propose a way to provide the more exact and extensive search results using the herb ontology with one hundred herbal information in oriental medicine fields.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.237-245
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• 2017

Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users' needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30's, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.