• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.12
• /
• pp.2153-2158
• /
• 2008

XML is one of standard web languages. XML has a syntax architecture consisted of tags, which are used to descript contents and structures of a XML document. In XML documents, missing of markup tag is one of common factors generating incomplete inputs. Usually, editors will recognize incomplete inputs as syntax errors. And so, when editors find them, they will highlight lines in which syntax errors happened, and execute appropriate error handling routines. But, there are no more parsing actions. In this paper, we propose a method to recognize incomplete input strings and keep parsing phases going. To recognize pars missed grammatically in incomplete inputs and create them newly, we use an expanding parsing table. It includes additional parsing actions for newly generated input symbols. Through the information, incomplete inputs will be completed and parsing steps will be finished successively. Therefore, users can be assured that they make always correct XML documents, even if inputs are incomplete, and can not be nervous about input faults.

• Journal of KIISE:Software and Applications
• /
• v.29 no.10
• /
• pp.755-765
• /
• 2002

In this paper, we observe various syntactic information for Korean parsing and propose a method to learn constraints and improve the efficiency of a parsing model by using the constraints. The proposed method has the following three characteristics. First, it improves the parsing efficiency since we use constraints that can prevent the parser from generating unsuitable candidates. Second, it is robust on a given Korean sentence because the attributes for the constraints are selected based on the syntactic and lexical idiosyncrasy of Korean. Third, it is easy to acquire constraints automatically from a treebank by using a decision tree learning algorithm. The experimental results show that the parser using acquired constraints can reduce the number of overgenerated candidates up to 1/2~1/3 of candidates and it runs 2~3 times faster than the one without any constraints.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.161-177
• /
• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Korean Journal of Cognitive Science
• /
• v.22 no.4
• /
• pp.429-447
• /
• 2011

In this paper, we propose a modified deterministic Korean dependency parser using a projectivity. The modified parser is improved by finding errors, such as cross dependency, from the original parsing results and correcting them according to the projectivity and head-final principles. Our parser also uses parsing history information in addition to rich features, which only a deterministic algorithm can use. Results on the modified parser for ETRI(2005) corpus, that consists of complex sentences, show that our parser outperforms other parsers.

• Journal of KIISE:Software and Applications
• /
• v.28 no.5
• /
• pp.448-448
• /
• 2001

The definitions in Korean dictionary not only describe meanings of title, but also include various semantic information such as hypernymy/hyponymy, meronymy/holonymy, polysemy, homonymy, synonymy, antonymy, and semantic features. This paper purposes to implement a parser as the basic tool to acquire automatically the semantic information from the definitions in Korean dictionary. For this purpose, first we constructed the part-of-speech tagged corpus and the tree tagged corpus from the definitions in Korean dictionary. And then we automatically extracted from the corpora the frequency of words which are ambiguous in part-of-speech tag and the grammar rules and their probability based on the statistical method. The parser is a kind of the probabilistic chart parser that uses the extracted data. The frequency of words which are ambiguous in part-of-speech tag and the grammar rules and their probability resolve the noun phrase's structural ambiguity during parsing. The parser uses a grammar factoring, Best-First search, and Viterbi search In order to reduce the number of nodes during parsing and to increase the performance. We experiment with grammar rule's probability, left-to-right parsing, and left-first search. By the experiments, when the parser uses grammar rule's probability and left-first search simultaneously, the result of parsing is most accurate and the recall is 51.74% and the precision is 87.47% on raw corpus.

• Journal of KIISE:Software and Applications
• /
• v.32 no.5
• /
• pp.385-395
• /
• 2005

Long sentence analysis has been a critical problem in machine translation because of high complexity. The methods of intra-sentence segmentation have been proposed to reduce parsing complexity. This paper presents the intra-sentence segmentation method based on maximum entropy probability model to increase the coverage and accuracy of the segmentation. We construct the rules for choosing candidate segmentation positions by a teaming method using the lexical context of the words tagged as segmentation position. We also generate the model that gives probability value to each candidate segmentation positions. The lexical contexts are extracted from the corpus tagged with segmentation positions and are incorporated into the probability model. We construct training data using the sentences from Wall Street Journal and experiment the intra-sentence segmentation on the sentences from four different domains. The experiments show about $88\%$ accuracy and about $98\%$ coverage of the segmentation. Also, the proposed method results in parsing efficiency improvement by 4.8 times in speed and 3.6 times in space.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.3
• /
• pp.105-111
• /
• 2003

This paper presents an approach to automate process planning of press dies for manufacturing of car bodies. Considering that the press-dies used at the same press operations regardless of the panels they produce or the car models of which they produce panels have similar shapes except for the forming part of the dies, general approaches to recognize manufacturing features from CAD models are not necessary. Therefore, a hybrid approach is proposed combining feature-based design and feature-extraction approaches. The proposed method recognizes features by parsing the parameters extracted from CAD models and finds proper operations by querying the database by the recognized features. An internet-based process planning system is developed to demonstrate the proposed approach and to suggest a new paradigm of process planning system that utilizes an internet access to the CAD system.

• Journal of KIISE
• /
• v.41 no.12
• /
• pp.1099-1109
• /
• 2014

Web-accessibility evaluation tools can be used to determine whether or not a website meets accessibility guidelines. As such, many such tools have been developed for web accessibility, but most of them dynamically fetch and analyze pages and as a result, some pages maybe omitted due to the lack of access authorization or environment information. In this paper, we propose a static method that analyzes web accessibility via abstract parsing. Our abstract parsing technique understands syntactic and semantic program structures that dynamically generate web pages according to external inputs and parameters. The static method performs its analysis without omitting any pages because it covers all execution paths. We performed an experiment with a PHP-based website to demonstrate how our tool discovers more accessibility errors than a dynamic page accessibility analysis tool.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.10 no.6
• /
• pp.552-557
• /
• 2017

Wire, wireless digital broadcasting has sharply expanded with the birth of high definition TV since 2010, the use of duplex contents as well as simplex contents has rapidly increased. Currently, our satellite communications system adopted DVB by European digital broadcasting standardization organization as a standard of domestic data broadcasting, the method how to use selective contents has been studied variously according to the development of IPTV. Digital broadcasting utilizes the method using Transport Stream Packet(TSP) by the way of multiplexing of information in order to send multimedia information such as video, audio and data of MPEG-2, this streams include detail information on TV guide and program as well as video and audio information. In order to understand these data broadcasting system, this study realized TS analyzer that divides transport stream (TS) by packet in Linux environment, analyzes and prints by function, it can help the understanding of TS, the enhancement of stream parsing ability.

• The Magazine of the IEIE
• /
• v.28 no.2
• /
• pp.117-117
• /
• 2001