• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.113-118
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• 2024

Pursuance Sentiment Analysis on Twitter is difficult then performance it's used for great review. The present be for the reason to the tweet is extremely small with mostly contain slang, emoticon, and hash tag with other tweet words. A feature extraction stands every technique concerning structure and aspect point beginning particular tweets. The subdivision in a aspect vector is an integer that has a commitment on ascribing a supposition class to a tweet. The cycle of feature extraction is to eradicate the exact quality to get better the accurateness of the classifications models. In this manuscript we proposed Term Frequency-Inverse Document Frequency (TF-IDF) method is to secure Principal Component Analysis (PCA) with Naïve Bayes Classifiers. As the classifications process, the work proposed can produce different aspects from wildly valued feature commencing a Twitter dataset.

• The Korean Journal of Archival Studies
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• no.22
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• pp.115-155
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• 2009

As Korea was merged into Japan, the official documents during Kabo Reform and The Great Han Empire time were handed over to the Government-General of Chosun and reclassified from section based to ministry based. However they had been reclassified before many times. The footprints of reclassification can be found in the classification stamps and warehouse number stamps which remained on the cover of official documents from Kabo Reform to The Great Han Empire. They classified the documents by Section in the classification system of Ministry-Department-Section, stamped and numbered them. It is consistent with the official document classification system in The Great Han Empire, which shows the section based classification was maintained. Although they stamped by Section and numbered the documents, there were differences in sub classification system by Section. In the documents of Land Tax Section, many institutions can be found. The documents of the same year can be found in different group and documents of similar characteristics are classified in the same group. Customs Section and Other Tax Section seemed to number their documents according to the year of documents. However the year and the order of 'i-ro-ha(イロハ) song' does not match. From Kabo Reform to The Great Han Empire the documents were grouped by Section. However they did not have classification rules for the sub units of Section. Therefore, it is not clear if the document grouping of classification stamps can be understood as the original order of official document classification system of The Great Han Empire. However, given the grouping method reflects the document classification system, the sub section classification system of the Great Han Empire can be inferred through the grouping method. In this inference, it is understood that the classification system was divided into two such as 'Section - Counterpart Institution' and 'Section - Document Issuance Year'. The Government-General of Chosun took over the official documents of The Great Han Empire, stored them in the warehouse and marked them with Warehouse Number Stamps. Warehouse Number Stamp contained the Institution that grouped those documents and the documents were stored by warehouse. Although most of the documents on the shelves in each warehouse were arranged by classification stamp number, some of them were mixed and the order of shelves and that of documents did not match. Although they arranged the documents on the shelves and gave the symbols in the order of 'i-ro-ha(イロハ) song', these symbols were not given by the order of number. During the storage of the documents by the Government-General of Chosun, the classification system according to the classification stamps was affected. One characteristic that can be found in warehouse number stamps is that the preservation period on each document group lost the meaning. The preservation period id decided according to the historical and administrative value. However, the warehouse number stamps did not distinguish the documents according to the preservation period and put the documents with different preservation period on one shelf. As Japan merged Korea, The Great Han Empire did not consider the official documents of the Great Han Empire as administrative documents that should be disposed some time later. It considered them as materials to review the old which is necessary for the colonial governance. As the meaning of the documents has been changed from general administrative documents to the materials that they would need to govern the colony, they dealt with all the official documents of The Great Han Empire as the same object regardless of preservation period. The Government-General of Chosun destroyed the classification system of the Great Han Empire which was based on Section and the functions in the Section by reclassifying them according to Ministry when they reclassified the official documents during Kobo Reform and the Great Han Empire in order to utilize them to govern the colony.

• Journal of the Korean Society for information Management
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• v.18 no.2
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• pp.203-230
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• 2001

The purpose of this study is to develop a document clustering model for automatic classification of knowledge. Two test collections of newspaper article texts and journal article abstracts are built for the clustering experiment. Various feature reduction criteria as well as term weighting methods are applied to the term sets of the test collections, and cosine and Jaccard coefficients are used as similarity measures. The performances of complete linkage and K-means clustering algorithms are compared using different feature selection methods and various term weights. It was found that complete linkage clustering outperforms K-means algorithm and feature reduction up to almost 10% of the total feature sets does not lower the performance of document clustering to any significant extent.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.606-606
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• 2006

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.227-235
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• 2005

Document filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. In this paper, we treat document filtering problem as binary document classification problem and we proposed the News Filtering system based on the Bayesian Classifier. For we perform filtering, we make an experiment to find out how many training documents, and how accurate relevance checks are needed.

• Herbal Formula Science
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• v.5 no.1
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• pp.85-98
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• 1997

Samhwaja-hyangyakbang has been known as the book of herbalogy published by the man, Samhwaja. But there are no records about the additor, and the absence of the document, it is so difficult to be informed about the time when it published and other details. But in this document and Hyangyakgugeubbang, there are similar prescriptions to Sublingual Inflammation, Aphtose, Anthrax, Furoncle, Ulcer, Dysentery, etc. So the time it published is estimated to Goryo-dynasty Gojong epoch(1232-1251) when the Hyangyakgugeubbang was published. In addition, this document seems to be basis of Hyangyakjipseongbang, Because, Hyangyakjipseongbang quoted more than 140 provisions from this document. Prescriptions that are different from other books in dosage or taking method, took those of Biyebaekyobang. In explanation or classification of disease, this document almost copied those of Biyebaekyobang, so this document take Biyebaekyobang for origin and take Sikeuisimkam, Taepyungseonghyebang, etc, for reference.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2603-2608
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• 2009

Document clustering is an important method for document analysis and is used in many different information retrieval applications. This paper proposes a new document clustering model using the clustering method based NMF(non-negative matrix factorization) and refinement of documents in cluster by using coherence of cluster. The proposed method can improve the quality of document clustering because the re-assigned documents in cluster by using coherence of cluster based similarity between documents, the semantic feature matrix and the semantic variable matrix, which is used in document clustering, can represent an inherent structure of document set more well. The experimental results demonstrate appling the proposed method to document clustering methods achieves better performance than documents clustering methods.

• Journal of Korean Library and Information Science Society
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• v.34 no.2
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• pp.233-253
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• 2003

Knowledge organization is the way we humans understand the world. There are two types of information organization mechanisms studied in information retrieval: namely classification md clustering. Classification organizes entities by pigeonholing them into predefined categories, whereas clustering organizes information by grouping similar or related entities together. The system of the Internet information resources extracts a keyword from the words which appear in the web document and draws up a reverse file. Term clustering based on grouping related terms, however, did not prove overly successful and was mostly abandoned in cases of documents used different languages each other or door-way-pages composed of only an anchor text. This study examines infometric analysis and clustering possibility of web documents based on co-link topology of web pages.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.675-676
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• 2010

As the number of documents rapidly increases in the web environment, the efficient document classification approaches have been required to retrieve the desired information from too many documents. In this paper, we propose a corpus construction tool to annotate document classification information such as category, keywords, and usage to each product description document. The proposed tool can help a human annotator to correctly identify this information by providing the verification step to check the input results of other human annotators. Also, the human annotator can construct the corpus anytime anywhere by using the web-based proposed system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.163-172
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• 2007

The web as global network includes text document, video, sound, etc and connects each distributed information using link Through development of web, it accumulates abundant information and the main is text based documents. Most of user use the web to retrieve information what they want. So, numerous researches have progressed to retrieve the text documents using the many methods, such as probability, statistics, vector similarity, Bayesian, and so on. These researches however, could not consider both the subject and the semantics of documents. As a result user have to find by their hand again. Especially, it is more hard to find the korean document because the researches of korean document classification is insufficient. So, to overcome the previous problems, we propose the korean document classification method for semantic retrieval. This method firstly, extracts TF value and RV value of concepts that is included in document, and maps into U-WIN that is korean vocabulary dictionary to select the topic of document. This method is possible to classify the document semantically and showed the efficiency through experiment.