• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.446-454
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• 2010

According to the original chart parsing algorithm, a sentence is parsed in a strict left-to-right order. The modified chart parsing algorithm proposed in this paper breaks the strictness. With the proposed algorithm, a sentence is parsed in a random order. Conventional left-to-right parsing is also possible, since left-to-right parsing is a special case of random-order parsing. The proposed parsing algorithm is an extension of chart parsing algorithm and its control structure is very simple, so that it is easy to implement the algorithm.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.9-17
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• 1994

The incremental parsing techniques are essential part of language-based environment which allow incremental construction of programs, as reparsing of modified part of the program alone enhances the system performance. A number of methods and algorithms have been proposed for incremental parsing and for the construction of incremental parsers. The purpose of this paper is to review the earlier incremental parsing algorithms which are too expensive in both time and space, and to present an efficient incremental LR parsing algorithm which is more efficient than the previous ones. In this paper, we generate automatically an extended LR parsing tables which allow the nonterminal symbols as well as terminal symbols for the input, and apply them to our efficient incremental LR parsing algorithm. Using these extended LR parsing tables. we suggest several methods to reduce its memory spaces and parsing steps as well. The algorithms described here were implemented in C language and YACC on a SUN UNIX OS, and were tested with several grammars and strings.

• Journal of KIISE
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• v.42 no.3
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• pp.361-366
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• 2015

Gap parsing is an algorithm for parsing incomplete input strings which include some gaps. Gap parsing is different from conventional parsing, and as known results, one-gap parsing algorithms for arbitrary context-free grammar and LL(1) grammar have $O(n^3)$ and $O(n^2)$ time complexity, respectively. This paper presents a one-gap parsing algorithm for extended PLR(1) grammars. Extended PLR(1) grammars are the class of grammars smaller than LR(1) but much larger than LL(1). The one-gap parsing algorithm of the grammar class is shown to have the time complexity of $O(n^2)$, which is equal to the complexity of one-gap parsing algorithms for LL(1) grammars.

• Journal of KIISE:Software and Applications
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• v.41 no.7
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• pp.518-522
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• 2014

A single state parsing automaton has the characteristics of the decision of actions which do not depend on the history of the parsing paths but on the current state. The single state parsing automaton hence has the advantage of the reduced parsing time and a small memory requirement compared to those of the conventional LR automaton. However, currently, the grammar classes generating single state parsing automata have not been known. This paper deals with the grammar classes generating single state parsing automata; in addition, this paper gives the generating method of single state parsing automata of the grammar classes.

• Korean Journal of Cognitive Science
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• v.6 no.3
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• pp.41-63
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• 1995

We present a LR,bottom-up parsing algorithms for TAG. We will introduce the adjoining rules system to handle the formal properties of TAG and to describe the parsing process more effectively. We will consider the context-free behavior of TAG at the adjoining instant. Then we will present the LR bottom up parsing algorithm for TAG by using this property. The basic idea behind a LR bottom up parsing algorithm can be applied to parsing TAG with other conventional algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.97-98
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• 2018

최근 딥러닝 기술의 발전으로 영상 분류 및 영상 내 객체 검출뿐만 아니라 CNN 기반의 segmentation 기술도 개발되어 다른 요소까지 포함한 직사각형 영역의 검출 영역이 아닌 경계까지 고려한 분리가 가능하게 되었다. 더불어 사람 영역을 신체부위나 의류 부분과 같은 세부 영역으로 나누어 분리하는 human parsing 기술까지 연구되고 있다. Human parsing은 의류스타일 분석 및 검색, 사람의 행동 인식 및 추적과 같은 분야에도 응용될 수 있다. 본 논문에서는 Spatial pyramid pooling layer를 이용하여 영상 전체에 대한 공간적 분포 및 특성 정보를 고려한 human parsing 기법을 제안한다. Look into person(LIP) dataset을 이용하여 기존의 다른 segmentation 및 human parsing 기법과 제안하는 기법을 비교하여 제안하는 기법의 human parsing 결과가 보다 정교한 분리가 가능한 것을 확인하였다.

• Journal of KIISE
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• v.44 no.3
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• pp.239-245
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• 2017

Probabilistic grammar is used in natural language processing, and the parse result of the grammar has to preserve the probability of the original grammar. As for the representative parsing method, LL parsing and LR parsing, the former preserves the probability information of the original grammar, but the latter does not. A characteristic of a probabilistic parsing automaton has been studied; but, currently, the generating model of probabilistic parsing automata has not been known. The paper provides a model of probabilistic parsing automata based on the single state parsing automata. The generated automaton preserves the probability of the original grammar, so it is not necessary to test whether or not the automaton is probabilistic parsing automaton; defining a probability function for the automaton is not required. Additionally, an efficient automaton can be constructed by choosing an appropriate parameter.

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.510-515
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• 2017

It is important to speed up the loading time of web applications. Parsing is a loading process that contributes to an increased loading time. To address this issue, the optimization called Concurrent Parsing has been proposed which handles the parsing process in parallel by using additional threads. However, Concurrent Parsing has a limitation that it does not consider the priority order of parsing. In this paper, we propose heuristics that exploit priorities of parsing to improve the Concurrent Parsing. For parsing priority, we empirically investigate the sequence of function calls, classify functions into 3 categories, and extract function call probabilities. If a function has high call probability, we give a high priority and if a function has low probability, we give a low priority. We evaluate this priority heuristics on real web applications and get the 2.6% decrease of loading time on average.

• Journal of KIISE
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• v.43 no.10
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• pp.1079-1084
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• 2016

Single-state parsing automata have a characteristic such that the decision of an action depends only on the current state but not on the parsing history. The memory space and the parsing time of single-state parsing automata are less than the memory space and the parsing time of LR automata. However, the applicable grammar class of single-state parsing automata is less than that of LR automata. This paper provides extended single-state parsing automata, which are applicable to LR grammars. In the prior work, the special state, referred to as the cyclic state was not treated in the construction of single-state parsing automata, and hence, the applicable grammar class was less than LR grammars. The paper solves the problem of cyclic states by processing dynamic information depending on an input string. The proposed method expands the application of grammar class of single-state parsing automata to LR grammars.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.91-99
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• 2006

The incremental parsing technique plays an important role in language-based environment which allows the incremental construction of a program. It improves the performance of a system by reanalyzing only the changed part of a program. The conventional incremental parsing uses the stack data structure in order to store the parsing information. In this paper, we suggest a threaded tree construction algorithm which parse by adding the threaded node address instead of using a stack data structure. We also suggest an incremental threaded tree construction which has incremental parsing process of five steps using the constructed threaded tree.