• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.2
• /
• pp.439-446
• /
• 2022

Document-type malicious codes are being actively distributed using attachments on websites or e-mails. Document-type malicious code is relatively easy to bypass security programs because the executable file is not executed directly. Therefore, document-type malicious code should be detected and prevented in advance. To detect document-type malicious code, we identified the document structure and selected keywords suspected of being malicious. We then created a dataset by converting the stream data in the document to ASCII code values. We specified the location of malicious keywords in the document stream data, and classified the stream as malicious by recognizing the adjacent information of the malicious keywords. As a result of detecting malicious codes by applying the CNN model, we derived accuracies of 0.97 and 0.92 in stream units and file units, respectively.

• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.2
• /
• pp.11-19
• /
• 2023

In this paper, we propose the methods of invoice document structure recognition and of making a spreadsheet electronic document. The texts and block location information of word blocks are recognized by an optical character recognition engine through deep learning. The word blocks on the same row and same column are found through their coordinates. The document area is divided through arrangement information of the word blocks. The character recognition result is inputted in the spreadsheet based on the document structure. In simulation result, the item placement through the proposed method shows an average accuracy of 92.30%.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.10
• /
• pp.23-33
• /
• 2014

The development of the information retrieval field is evolving to the research field searching accurately for the information from thing finding rapidly a large amount of information. Personalization and the semantic web technology is a key technology. The automatic indexing technology about the web document and throughput go beyond the research stage and show up as the practical service. However, there is a lack of research on the document information retrieval field about the attached document type of except the web document. In this paper, we illustrate about the method in which it analyzed the text content of the unstructured documents prepared in the text, word, hwp form and it how to construction OWL ontology. To build TBox of the document ontology and the resources which can be obtained from the document is selected, and we implement with the system in order to utilize as the instant of the constructed document ontology. It is effectually usable in the information retrieval and document management system using the semantic technology of the correspondence document as the ontology automatic construction of this kind of the unstructured documents.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.569-572
• /
• 2003

A construction process involves many designers, engineers, contractors, consulting engineers and government officials. Thus, it is essential to promote collaboration among such participants through of effective document exchange. There have been efforts to Improve efficiency of document exchange through Web. Also XML/EDI is recommended by its method. So the purpose of the research was to establish the data model for document information management in document exchange for construction participants using web-based XML/EDI. This research proposed a method of modeling document information for systemic management of document information that exchanged by XML/EDI in central and explained concept of application document information that stored in database. This research classified construction document according to its information relation.

• The KIPS Transactions:PartB
• /
• v.12B no.6 s.102
• /
• pp.697-702
• /
• 2005

The focused crawler is a topic-driven document-collecting crawler that was suggested as a promising alternative of maintaining up-to-date web document Indices in search engines. A major problem inherent in previous focused crawlers is the liability of missing highly relevant documents that are linked from off-topic documents. This problem mainly originated from the lack of consideration of structural information in a document. Traditional weighting method such as TFIDF employed in document classification can lead to this problem. In order to improve the performance of focused crawlers, this paper proposes a scheme of locality-based document segmentation to determine the relevance of a document to a specific topic. We segment a document into a set of sub-documents using contextual features around the hyperlinks. This information is used to determine whether the crawler would fetch the documents that are linked from hyperlinks in an off-topic document.

• Journal of the Korean Society for information Management
• /
• v.22 no.3 s.57
• /
• pp.261-287
• /
• 2005

The purpose of this paper is to explore the ways to improve the performance of SVM (Support Vector Machines) text classifier using inter-document similarities. SVMs are powerful machine learning systems, which are considered as the state-of-the-art technique for automatic document classification. In this paper text categorization via SVMs approach based on feature representation with document vectors is suggested. In this approach, document vectors instead of index terms are used as features, and vector similarities instead of term weights are used as feature values. Experiments show that SVM classifier with document vector features can improve the document classification performance. For the sake of run-time efficiency, two methods are developed: One is to select document vector features, and the other is to use category centroid vector features instead. Experiments on these two methods show that we can get improved performance with small vector feature set than the performance of conventional methods with index term features.

• Journal of KIISE:Databases
• /
• v.33 no.5
• /
• pp.538-550
• /
• 2006

XML Keyword search enables us to get information easily without knowledge of structure of documents and returns specific and useful partial document results instead of whole documents. Element level query processing makes it possible, but computational complexity, as the number of documents grows, increases significantly overhead costs. In this paper, we present document-level ranking scheme over XML documents which predicts results of element-level processing to reduce processing cost. To do this, we propose the notion of 'keyword proximity' - the correlation of keywords in a document that affects the results of element-level query processing using path information of occurrence nodes and their resemblances - for document ranking process. In benefit of document-centric view, it is possible to reduce processing time using ranked document list or filtering of low scored documents. Our experimental evaluation shows that document-level processing technique using ranked document list is effective and improves performance by the early termination for top-k query.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.11
• /
• pp.2133-2138
• /
• 2017

The analysis of existing XML documents and other documents was centered on words. It can be implemented using a morpheme analyzer, but it can classify many words in the document and cannot grasp the core contents of the document. In order for a user to efficiently understand a document, a paragraph containing a main word must be extracted and presented to the user. The proposed system retrieves keyword in the normalized XML document. Then, the user extracts the paragraphs containing the keyword inputted for searching and displays them to the user. In addition, the frequency and weight of the keyword used in the search are informed to the user, and the order of the extracted paragraphs and the redundancy elimination function are minimized so that the user can understand the document. The proposed system can minimize the time and effort required to understand the document by allowing the user to understand the document without reading the whole document.

• Journal of Korea Game Society
• /
• v.3 no.1
• /
• pp.67-73
• /
• 2003

Most web caches save documents temporarily into themselves on the basis of those documents. And when a corresponding document exists within the cache on wei s request, web cache sends the document to corresponding user. On the contrary, when there is not any document within the cache, web cache requests a new document to the related server to copy the document into the cache and then rum it back to user. Here, web cache uses a replacement policy to change existing document into a new one due to exceeded capacity of cache. Typical replacement policy includes document-based LRU or LFU technique and other various replacement policies are used to replace the documents within cache effectively. However, these replacement policies function only with regard to the time and frequency of document request, not considering the popularity of each web site. Based on replacement policies with regard to documents on frequent requests and the popularity of each web site, this paper aims to present the document replacement policies with regard to the popularity of each web site, which are suitable for latest network environments to enhance the hit-ratio of cache and efficiently manage the contents of cache by effectively replacing documents on intermittent requests by new ones.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.1
• /
• pp.227-232
• /
• 2008

General web caches save documents temporarily into themselves on the basis of those documents. And when a corresponding document exists within the cache on user's request. web cache sends the document to corresponding user. On the contrary. when there is not any document within the cache, web cache requests a new document to the related server to copy the document into the cache and then turn it back to user. Here, web cache uses a replacement policy to change existing document into a new one due to exceeded capacity of cache. Typical replacement policy includes document-based LRU or LFU technique and other various replacement policies are used to replace the documents within cache effectively. However. these replacement policies function only with regard to the time and frequency of document request. not considering the popularity of each web site. Based on replacement policies with regard to documents on frequent requests and the popularity of each web site, this paper aims to present the document replacement policies with regard to the popularity of each web site, which are suitable for latest network environments to enhance the hit-ratio of cache and efficiently manage the contents of cache by effectively replacing documents on intermittent requests by new ones.