• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.849-856
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• 2011

This paper proposes a method for transforming unstructured text contents of engineering documents, which have complex hierarchical structure of subtitles with various heading symbols, into a semi-structured XML document according to the hierarchical subtitle structure. In order to extract the hierarchical structure from plain text information, this study employed a method of document structure extraction which is an analysis technique of the document structure. In addition, a method for processing enumerative text contents was developed to increase overall accuracy during extraction of the subtitles and construction of a hierarchical subtitle structure. An application module was developed based on the proposed method, and the performance of the module was evaluated with 40 test documents containing structural calculation records of bridges. The first test group of 20 documents related to the superstructure of steel girder bridges as applied in a previous study and they were used to verify the enhanced performance of the proposed method. The test results show that the new module guarantees an increase in accuracy and reliability in comparison with the test results of the previous study. The remaining 20 test documents were used to evaluate the applicability of the method. The final mean value of accuracy exceeded 99%, and the standard deviation was 1.52. The final results demonstrate that the proposed method can be applied to diverse heading symbols in various types of engineering documents to represent the hierarchical subtitle structure in a semi-structured XML document.

• Journal of Korea Multimedia Society
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• v.7 no.10
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• pp.1354-1369
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• 2004

This paper presents a logical structure analysis method which transforms Web documents into XML ones. The proposed method consists of three phases: visual grouping, element identification, and logical grouping. To produce a logical structure more accurately, the proposed method defines a document model that is able to describe logical structure information of topic-specific document class. Since the proposed method is based on a visual structure from the visual grouping phase as well as a document model that describes logical structure information of a document type, it supports sophisticated structure analysis. Experimental results with HTML documents from the Web show that the method has performed logical structure analysis successfully compared with previous works. Particularly, the method generates XML documents as the result of structure analysis, so that it enhances the reusability of documents.

• 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.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.209-217
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• 2014

It is very important to classify a lot of table-form documents into the same type of classes or to extract information filled in the template automatically. For these, it is necessary to accurately analyze table-form structure. This paper proposes an algorithm to extract corner points based on line edge segments and to classify the type of junction from table-form images. The algorithm preprocesses image through binarization, skew correction, deletion of isolated small area of black color because that they are probably generated by noises.. And then, it processes detections of edge block, line edges from a edge block, corner points. The extracted corner points are classified as 9 types of junction based on the combination of horizontal/vertical line edge segments in a block. The proposed method is applied to the several unconstraint document images such as tax form, transaction receipt, ordinary document containing tables, etc. The experimental results show that the performance of point detection is over 99%. Considering that almost corner points make a correspondence pair in the table, the information of type of corner and width of line may be useful to analyse the structure of table-form document.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.571-574
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• 2003

This research is aimed to automate the generating process of the database from paper based table forms like this work. The registration table has so complicate table structures, ana in this research we used the registration tables as an example of general table structure understanding. We propose a table structure understanding system for some table types, and it has some steps. The first step is that the document images on paper are read from the image scanner. The second step is that a document image segments into some tables. In the third step, the character strings is extracted using image processing technology and the property of the character strings is determined. And the structured database is generated automatically. The proposed system consists of two systems. "Master document generation system" is used for the table form definition, and it doesn′t include the handwritten characters. "Structure analysis system for complete d table" is used for the written form, and it analyzes the table form filled in the handwritten character. We implemented the system using MS Visual C＋＋ on Windows, and it can get the correct extraction rate 98％ among 51 registration tables written by the different students.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.886-892
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• 2022

In construction projects, it is common to exchange documents using email because of convenience. In this study, a method extracting and organizing block information automatically based on email was developed. This method is composed of document exchange and archiving processes, which are difficult to manage and vulnerable to loss. Therefore, this study aims to develop a solution that can automatically link email and block information. The block data components are designed to derive from email exchange and user-additional input information. Also, automatically generating blocks process including extraction and conversion of information was proposed. This solution can lead to promote the convenience of project document management in terms of identifying the document flow and preventing loss of information.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.201-204
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• 1991

In this paper the method of representing the document image by the quadtree data structure, and extracting each character seperately from the constructed quadtree are described. The document image is represented by a binary encoded quadtree and the segmentation is performed according to the information of each leaf node of the quadtree. Then, each character is extracted by the relation of positions of segments. This method enables to extract characters without examining every pixel in the image and the required storage of document image is decreased.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.98-101
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• 2003

To classify desired and undesired documents on the web according to each user's view, FOCUS (Fuzzy dOCUment ordering System) is developed based on fuzzy concept extraction, fuzzy fish eye matching, and fuzzy selection. Experiments are done using the concept-system-dictionary by EDR (Electronic Dictionary Research Institute) including 140,000 words and web-based documents related to movie.

• International Journal of Contents
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• v.1 no.2
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• pp.5-9
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• 2005

Currently most Internet documents including data are made based on predefined templates, but templates are usually formed only for main data and are not helpful for information retrieval against indexes, advertisements, header data etc. Templates in such forms are not appropriate when Internet documents are used as data for information retrieval. In order to process Internet documents in various areas of information retrieval, it is necessary to detect additional information such as advertisements and page indexes. Thus this study proposes a method of detecting the layout of Web pages by identifying the characteristics and structure of block tags that affect the layout of Web pages and calculating distances between Web pages. This method is purposed to reduce the cost of Web document automatic processing and improve processing efficiency by providing information about the structure of Web pages using templates through applying the method to information retrieval such as data extraction.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.42-52
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• 2002

Information extraction(IE) is a process of recognizing and fetching particular information fragments from a document. In previous work, most IE systems generate the extraction rules called the wrappers manually, and although this manual wrapper generation may achieve more correct extraction, it reveals some problems in flexibility, extensibility, and efficiency. Some other researches that employ automatic ways of generating wrappers are also experiencing difficulties in acquiring and representing useful domain knowledge and in coping with the structural heterogeneity among different information sources, and as a result, the real-world information sources with complex document structures could not be correctly analyzed. In order to resolve these problems, this paper presents an agent-based information extraction system named XTROS that exploits the domain knowledge to learn from documents in a semi-structured information source. This system generates a wrapper for each information source automatically and performs information extraction and information integration by applying this wrapper to the corresponding source. In XTROS, both the domain knowledge and the wrapper are represented as XML-type documents. The wrapper generation algorithm first recognizes the meaning of each logical line of a sample document by using the domain knowledge, and then finds the most frequent pattern from the sequence of semantic representations of the logical lines. Eventually, the location and the structure of this pattern represented by an XML document becomes the wrapper. By testing XTROS on several real-estate information sites, we claim that it creates the correct wrappers for most Web sources and consequently facilitates effective information extraction and integration for heterogeneous and complex information sources.