• Journal of Welding and Joining
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• v.34 no.1
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• pp.47-53
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• 2016

WPS/PQR is the essential documents for shipbuilding welding. WPS is the document containing the information related to welding procedure and PQR is the record of approval for welding procedure. Both documents should be approved by the ship owners and the classification societies. It is very important to manage these documents because the welding procedure using these documents could not be carried out before they are approved. Database is an useful tool to manage these documents. It can manage a number of documents and show the processing status of WPS/PQR documents. In this study, all documents related to WPS/PQR documents were investigated and analyzed in the viewpoint of DB. An appropriate DB system was designed for WPS/PQR and the related documents on the basis of CBD methodology. The DB system could make WPS/PQR documents easily and shortly. The grasp of the processing status of WPS/ PQR could help the good management of fabrication schedule in shipbuilding.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1302-1306
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• 2004

This paper proposes a model for information filtering (IF) on the Web. The user information need is described into two levels in this model: profiles on category level, and Boolean queries on document level. To efficiently estimate the relevance between the user information need and documents by fuzzy, the user information need is treated as a rough set on the space of documents. The rough set decision theory is used to classify the new documents according to the user information need. In return for this, the new documents are divided into three parts: positive region, boundary region, and negative region. We modified user profile by the user's relevance feedback and discerning words in the documents. In experimental we compared the results of three methods, firstly is to search documents that are not passed the filtering system. Second, search documents that passed the filtering system. Lastly, search documents after modified user profile. The result from using these techniques can obtain higher precision.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.37-38
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• 2015

A number of documents containing important and useful knowledge have been generated over time in the construction industry. Such text-based knowledge plays an important role in the construction industry for decision-making and business strategy development by being used as best practice for upcoming projects, delivering lessons learned for better risk management and project control. Thus, practical and usable knowledge creation from construction documents is necessary to improve business efficiency. This study proposes a knowledge creating system from construction documents using text mining and the design comprises three main steps - text mining preprocessing, weight calculation of each term, and visualization. A system prototype was developed as a pilot study of the system design. This study is significant because it validates a knowledge creating system design based on text mining and visualization functionality through the developed system prototype. Automated visualization was found to significantly reduce unnecessary time consumption and energy for processing existing data and reading a range of documents to get to their core, and helped the system to provide an insight into the construction industry.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.217-236
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• 2013

Ranking thousands of web documents so that they are matched in response to a user query is really a challenging task. For this purpose, search engines use different ranking mechanisms on apparently related resultant web documents to decide the order in which documents should be displayed. Existing ranking mechanisms decide on the order of a web page based on the amount and popularity of the links pointed to and emerging from it. Sometime search engines result in placing less relevant documents in the top positions in response to a user query. There is a strong need to improve the ranking strategy. In this paper, a novel ranking mechanism is being proposed to rank the web documents that consider both the HTML structure of a page and the contextual senses of keywords that are present within it and its back-links. The approach has been tested on data sets of URLs and on their back-links in relation to different topics. The experimental result shows that the overall search results, in response to user queries, are improved. The ordering of the links that have been obtained is compared with the ordering that has been done by using the page rank score. The results obtained thereafter shows that the proposed mechanism contextually puts more related web pages in the top order, as compared to the page rank score.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.57-62
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• 2002

Recently, due to the development of internet based information technology, organizations Is utilizing electronic documents as important media for processing business work and sharing Information exchange. These electronic documents are mos4 form like documents and are important user interfaces for business applications. But, presently web-based electronic documents are lack of the characteristics that are taken in documents, such as document writing rules and its workflow. This Paper deals with XML-based business document that include the structure, data, and logic and proposes the framework for validating the data and logic included within business documents using Prolog.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.105-111
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• 2010

The air logistics process is complex and need many informations because various agencies participate in the logistics service and there are many stakeholders in air logistics. But it is hard to improve the infra of facilities because of an enormous expense, so it needs to simplify air logistics process for growing air freight. When documents are sent, it needs to change the form of documents in spite of same document due to different form by agencies. Also documents are changed even though different documents have same informations. Consequently, errors are increased because the names of the same data are different from each other and stakeholders reproduce the documents. In order to mitigate these problems, we selected documents and analyzed data of documents for the interface optimization in general air logistics process. Next, we unified the names of data and defined contents of data. Also we set the type of the defined data on DB type, and gave the code to the defined data. It made easy to exchange informations among the stakeholders to match documents corresponding with the defined data.

• Journal of the Korean Society of Safety
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• v.37 no.1
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• pp.41-48
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• 2022

Bridge engineering documents have essential contents that must be referenced continuously throughout a structure's entire life cycle, but research related to the quality of the contents is still lacking. XML schema matching is an excellent technique to improve the quality of stored data; however, it takes excessive computing time when applied to documents with many contents and a deep hierarchical structure, such as bridge engineering documents. Moreover, it requires a manual parametric study for matching elements' weight factors, maintaining a high matching accuracy. This study proposes an efficient weight-factor determination method based on an artificial neural network (ANN) model using the simplified XML schema-matching method proposed in a previous research to reduce the computing time. The ANN model was generated and verified using 580 data of document properties, weight factors, and matching accuracy. The proposed ANN-based schema-matching method showed superiority in terms of accuracy and efficiency compared with the previous study on XML schema matching for bridge engineering documents.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.277-300
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• 2020

This paper presents a method for clustering short text documents, such as news headlines, social media statuses, or instant messages. Due to the characteristics of these documents, which are usually short and sparse, an appropriate technique is required to discover hidden knowledge. The objective of this paper is to identify the combination of document representation, document distance, and document clustering that yields the best clustering quality. Document representations are expanded by external knowledge sources represented by a Distributed Representation. To cluster documents, a K-means partitioning-based clustering technique is applied, where the similarities of documents are measured by word mover's distance. To validate the effectiveness of the proposed method, experiments were conducted to compare the clustering quality against several leading methods. The proposed method produced clusters of documents that resulted in higher precision, recall, F1-score, and adjusted Rand index for both real-world and standard data sets. Furthermore, manual inspection of the clustering results was conducted to observe the efficacy of the proposed method. The topics of each document cluster are undoubtedly reflected by members in the cluster.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.153-158
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• 2015

Nowadays, automatic keyphrase extraction is considered to be an important task. Most of the previous studies focused only on selecting keyphrases within the body of input documents. These studies overlooked latent keyphrases that did not appear in documents. In addition, a small number of studies on latent keyphrase extraction methods had some structural limitations. Although latent keyphrases do not appear in documents, they can still undertake an important role in text mining because they link meaningful concepts or contents of documents and can be utilized in short articles such as social network service, which rarely have explicit keyphrases. In this paper, we propose a new approach that selects qualified latent keyphrases from input documents and overcomes some structural limitations by using deep belief networks in a supervised manner. The main idea of this approach is to capture the intrinsic representations of documents and extract eligible latent keyphrases by using them. Our experimental results showed that latent keyphrases were successfully extracted using our proposed method.

• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.275-284
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• 2010

Offshore software development (OSD) is international business collaboration. OSD projects often encounter intercultural and inter-linguistic problems disturbing the projects. Business documents are formal media of information and knowledge for OSD. While OSD documents should convey common understanding of the OSD products, the documents may contain unsuitable expressions which draw misunderstanding of the required products and offensive issues for the collaboration. Intercultural and inter-linguistic differences cause mistakes and inappropriate expressions. OSD from Japan to China is the largest in Asia, and Japanese language is often used in OSD documents. Large similarity is found between Japanese and Chinese in their languages, while many differences exist even for the same word. The similarity induces to write unsuitable expressions for both sides of OSD. To introduce risks for OSD projects caused by unsuitable or inappropriate expressions in OSD documents, we propose to apply a proofreading system of Japanese documents for OSD. Japanese consignor uses the system to refine OSD documents written by Japanese engineers for Chinese readers, and Chinese consignee uses it to refine Japanese documents written by Chinese Engineers as derivatives of OSD projects. Effectiveness of applying the proofreading system is discussed for actual projects.