• Journal of Information Technology and Architecture
• /
• v.11 no.1
• /
• pp.63-73
• /
• 2014

As the advance of WWW, unstructured data including texts are taking users' interests more and more. These unstructured data created by WWW users represent users' subjective opinions thus we can get very useful information such as users' personal tastes or perspectives from them if we analyze appropriately. In this paper, we provide various analysis efficiently for unstructured text documents by taking advantage of OLAP (On-Line Analytical Processing) multidimensional cube technology. OLAP cubes have been widely used for the multidimensional analysis for structured data such as simple alphabetic and numberic data but they didn't have used for unstructured data consisting of long texts. In order to provide multidimensional analysis for unstructured text data, however, Text Cube model has been proposed precently. It incorporates term frequency and inverted index as measurements to search and analyze text databases which play key roles in information retrieval. The primary goal of this paper is to apply this text cube model to a real data set from in an Internet site sharing hotel information and to provide multidimensional analysis for users' reviews on hotels written in texts. To achieve this goal, we first build text cubes for the hotel review data. By using the text cubes, we design and implement the system which provides multidimensional keyword search features to search and to analyze review texts on various dimensions. This system will be able to help users to get valuable guest-subjective summary information easily. Furthermore, this paper evaluats the proposed systems through various experiments and it reveals the effectiveness of the system.

• The Journal of the Korea Contents Association
• /
• v.9 no.11
• /
• pp.54-62
• /
• 2009

To avoid the redundant investment on the project selection process, it is necessary to check whether the submitted research topics have been proposed or carried out at other institutions before. This is possible through the search engines adopted by the keyword matching algorithm which is based on boolean techniques in national-sized research results database. Even though the accuracy and speed of information retrieval have been improved, they still have fundamental limits caused by keyword matching. This paper examines implemented TFIDF-based algorithm, and shows an experiment in search engine to retrieve and give the order of priority for similar and redundant documents compared with research proposals, In addition to generic TFIDF algorithm, feature weighting and K-Nearest Neighbors classification methods are implemented in this algorithm. The documents are extracted from NDSL(National Digital Science Library) web directory service to test the algorithm.

• Journal of Digital Contents Society
• /
• v.13 no.3
• /
• pp.317-324
• /
• 2012

Recently, coordination task of similarity between national R&D programs is emphasized on view from the R&D investment efficiency. But the previous similarity search method like text-based similarity search which using keyword of R&D projects has reached the limit due to deviation of document's quality. For the solve the limitations of text-based similarity search using the keyword extraction, in this study, utilization of R&D project's technical classification will be discussed as a new similarity search method when analyzed of similarity between national R&D programs. To this end, extracts the Science and Technology Standard Classification of R & D projects which are collected when national R&D Survey & analysis, and creates peculiar vector model of each R&D programs. Verify a reliability of this study by calculate the cosine-based and Euclidean distance-based similarity and compare with calculated the text-based similarity.

• Journal of dental hygiene science
• /
• v.21 no.2
• /
• pp.104-110
• /
• 2021

Background: Regardless of countries, the myth that rain makes the body ache has been worded in various forms, and a number of studies have been reported to investigate this. However, these studies, which depended on the patient's experience or memory, had obvious limitations. Google Trends is a big data analysis service based on search terms and viewing videos provided by Google LLC, and attempts to use it in various fields are continuing. In this study, we endeavored to introduce the 'value as a research tool' of the Google Trends, that has emerged along with technological advancements, through research on 'whether toothaches really occur frequently on rainy days'. Methods: Keywords were selected as objectively as possible by applying web crawling and text mining techniques, and the keyword "bi" meaning rain in Korean was added to verify the reliability of Google Trends data. The correlation was statistically analyzed using precipitation and temperature data provided by the Korea Meteorological Agency and daily search volume data provided by Google Trends. Results: Keywords "chi-gwa", "chi-tong", and "chung-chi" were selected, which in Korean mean 'dental clinic', 'toothache', and 'tooth decay' respectively. A significant correlation was found between the amount of precipitation and the search volume of tooth decay. No correlation was found between precipitation and other keywords or other combinations. It was natural that a very significant correlation was found between the amount of precipitation, temperature, and the search volume of "bi". Conclusion: Rain seems to actually be a cause of toothache, and if objective keyword selection is premised, Google Trends is considered to be very useful as a research tool in the future.

• The Korean Society of Law and Medicine
• /
• v.18 no.1
• /
• pp.103-141
• /
• 2017

The (Korean) Medical Services Act revised in 2009 introduces the accreditation of specialty hospital. When a hospital meets prescribed standards, passes a board review, and is accredited as a specialty hospital by the Minister of Health and Welfare, then it may use 'specialty hospital' in its name and certification mark of specialty hospital. The problem is that the (Korean) Fair Trade Commission and the (Korean) Ministry of Health and Welfare, both of which have authorities to regulate advertising in general and in health care service in turn, announced the guidelines to prohibit internet (portal) service providers to provide keyword search ads service using key-words such as 'specialty' or 'specialized in' for those who are not accredited by the Minister of Health and Welfare. In this article, whether these guidelines can be justified by the current regime and whether the current specialty hospital policy is agreeable would be examined. To do this, the legal nature of accreditation of specialty hospital, the limit of advertisement regulation, the law of keyword search ads, and the liability of internet service providers also would be analyzed.

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

• Journal of Korea Multimedia Society
• /
• v.3 no.1
• /
• pp.41-52
• /
• 2000

This paper introduces the design and implementation of product search support agent for an efficient Internet shopping. In existing shopping malls, electronic catalogs provide the product information by subject or keyword, or the buying information by purchasing history. This proposed product search support agent system is designed to analyze navigating patterns of customers, extract more effective buying information with regard to the current trend in customer navigating . In conclusion, this product search support agent can propose more suitable buying information to customers that he can be proposed to make purchases more efficiently.

• International Journal of Advanced Culture Technology
• /
• v.10 no.4
• /
• pp.230-237
• /
• 2022

The Community Social Service Investment project started as a state subsidy project in 2007 and has grown very rapidly in quantitative terms in a short period of time. It is a bottom-up project that discovers the welfare needs of people and plans and provides services suitable for them. The purpose of this study is to analyze using big data to determine the social response to local community service investment projects. For this, data was collected and analyzed by crawling with a specific keyword of community service investment project on Google and Naver sites. As for the analysis contents, monthly search volume, related keywords, monthly search volume, search rate by age, and gender search rate were conducted. As a result, 10 items were found as related keywords in Google, and 3 items were found in Naver. The overall results of Google and Naver sites were slightly different, but they increased and decreased at almost the same time. Therefore, it can be seen that the community service investment project continues to attract users' interest.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.04a
• /
• pp.1287-1290
• /
• 2011

Because of the rapid development of internet, there are more and more documents stored by the XML-based format. When there is a great deal of XML documents, how to get the valuable Information is an important subject. This paper proposes an effective XML document search method to search text contents and structures of XML documents. We build the keyword matrix of text contexts and structure matrixes of structures in XML documents to improve the efficiency of query time. When there is a great deal of XML documents, the search method we propose can improve much efficiency of query time.

• Journal of Broadcast Engineering
• /
• v.13 no.1
• /
• pp.43-52
• /
• 2008

We study the problem of search in which a server contains various multimedia contents and a user wishes to retrieve some multimedia items containing a specific without revealing to the server which items they are. Recently, Ogata and Kurosawa introduced a search scheme by using the notion of oblivious transfer. In their scheme, a user must inefficiently search and compare all the data stored in the seuer for each search query. In this paper, we propose an efficient oblivious search by using the oblivious transfer, in which a user needs not to search and compare all the data. We formally prove that the proposed scheme is secure under the hardness of RSA known target inversion problem.