• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.395-404
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• 2007

Feature-based modeling and history-based modeling are the two main paradigms that are used in most of current CAD systems. Although these modeling paradigms make it easier for designers to create solid model, it may pose dependency constraints on features that are interacting one with another. When editing such features, these constraints often cause unpredictable and unacceptable results. For example, when a parent feature is deleted, the child features of the parent feature are also deleted. This entails re-generations of the deleted features, which requires additional modeling time. In order to complement this situation, we propose a method to delete only the features of interest by disconnecting the dependency constraints. This method can provide designers with more efficient way of model modification.

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

• MALSORI
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• no.27_28
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• pp.27-56
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• 1994

Processes involving the change of vowel height are natural enough to be found in many languages. It is essential to have a better feature specification for vowel height to grasp these processes properly, Standard Phonology adopts the binary feature system, and vowel height is represented by the two features, i.e., [\pm high] and [\pm low]. This has its own merits. But it is defective because it is misleading when we count the number of features used in a rule to compare the naturalness of rules. This feature system also cannot represent more than three degrees of height, We wi31 discard the binary features for vowel height. We consider to adopt the multivalued feature [n high] for the property of height. However, this feature cannot avoid the arbitrariness resulting from the number values denoting vowel height. It is not easy to expect whether the number in question is the largest or not It also is impossible to decide whether a larger number denotes a higher vowel or a lower vowel. Furthermore this feature specification requires an ad hoc condition such as n > 3 or n \geq 2, whenever we want to refer to a natural class including more than one degree of height The altelnative might be Particle Phonology, or Dependency Phonology. These might be apt for multivalued vowel height systems, as their supporters argue. However, the feature specification of Particle Phonology will be discarded because it does not observe strictly the assumption that the number of the particle a is decisive in representing the height. One a in a representation can denote variant degrees of height such as [e], [I], [a], [a ] and [e ]. This also means that we cannot represent natural classes in terms of the number of the particle a, Dependency Phonology also has problems in specifying a degree of vowel height by the dependency relations between the elements. There is no unique element to represent vowel height since every property has to be defined in terms of the dependency relations between two or more elements, As a result it is difficult to formulate a rule for vowel height change, especially when the phenomenon involves a chain of vowel shifts. Therefore, we suggest a new feature specification for vowel height (see Chapter 3). This specification resorts to a single feature H and a few >'s which refer exclusively to the degree of the tongue height when a vowel is pronounced. It can cope with more than three degrees of height because it is fundamentally a multivalued scalar feature. This feature also obviates the ad hoc condition for a natural class while the [n high] type of multivalued feature suffers from it. Also this feature specification conforms to our expection that the notation should become simpler as the generality of the class increases, in that the fewer angled brackets are used, the more vowels are included, Incidentally, it has also to be noted that, by adopting a single feature for vowel height, it is possible to formulate a simpler version of rules involving the changes of vowel height especially when they involve vowel shifts found in many languages.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1254-1271
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• 2018

Keyphrase extraction is one of fundamental natural language processing (NLP) tools to improve many text-mining applications such as document summarization and clustering. In this paper, we propose to use two novel techniques on the top of the state-of-the-art keyphrase extraction methods. First is the anti-patterns that aim to recognize non-keyphrase candidates. The state-of-the-art methods often used the rich feature set to identify keyphrases while those rich feature set cover only some of all keyphrases because keyphrases share very few similar patterns and stylistic features while non-keyphrase candidates often share many similar patterns and stylistic features. Second one is to use the dependency graph instead of the word co-occurrence graph that could not connect two words that are syntactically related and placed far from each other in a sentence while the dependency graph can do so. In experiments, we have compared the performances with different settings of the graphs (co-occurrence and dependency), and with the existing method results. Finally, we discovered that the combination method of dependency graph and anti-patterns outperform the state-of-the-art performances.

• Language and Information
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• v.18 no.2
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• pp.59-79
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• 2014

This paper aims at exploring the processing mechanism of filler-gap dependency resolution and feature checking in Korean wh-constructions. Based on their findings on Japanese sentence processing, Aoshima et al. (2004) have argued that the parser posits a gap in the embedded clause in head-final languages, unlike in head-initial languages, where the parser posits a gap in the matrix clause. In order to verify their findings in the Korean context, and to further explore the mechanisms involved in processing Korean wh-constructions, the present study replicated the study done by Aoshima et al., with some modifications of problematic areas in their original design. Sixty-four Korean native speakers were presented Korean sentences containing a wh-phrase in four conditions, with word order and complementizer type as the two main factors. The participants read sentences segment-by-segment, and the reading times at each segment were measured. The reading time analysis showed that there was no such slowdown at the embedded verb in the scrambled conditions as observed in Aoshima et al. Instead, there was a clear indication of the wh-feature checking process in terms of a major slowdown at the relevant region.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1281-1288
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• 2015

Nongroup Cellular Automata(CA) having two trees in the state transition diagram of a CA is suitable for pattern classifier which divides pattern set into two classes. Maji et al. [1] classified patterns by using multiple attractor cellular automata as a pattern classifier with dependency vector. In this paper we propose a method of generation of a pattern classifier using feature vector which is the extension of dependency vector. In addition, we propose methods for finding nonreachable states in the 0-tree of the state transition diagram of TPMACA corresponding to the given feature vector for the analysis of the state transition behavior of the generated pattern classifier.

• Earthquakes and Structures
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• v.4 no.2
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• pp.181-202
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• 2013

It is well known that the properties of the soil deposits, especially the damping, depend on both frequency and strain amplitude. Therefore it is important to consider both dependencies to calculate the soil response against earthquakes in order to estimate input motions to buildings. However, it has been difficult to calculate the seismic response of the soil considering both dependencies directly. The author has studied the time domain evaluation of the frequency dependent dynamic stiffness, and proposed a simple hysteretic damping model that satisfies the causality condition. In this paper, this model was applied to nonlinear analyses considering the effects of the strain amplitude dependency of the soil. The basic characteristics of the proposed method were studied using a two layered soil model. The response behavior was compared with the conventional model e.g. the Ramberg-Osgood model and the SHAKE model. The characteristics of the proposed model were studied with regard to the effects of element divisions and the frequency dependency that is a key feature of the model. The efficiency of the model was confirmed by these studies.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.234-240
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• 2007

This paper argues that various kinds of displaced structures in English should be licensed by a more explicitly formulated type of rule schema in order to deal with what is called weak connectivity in English. This paper claims that the filler and the gap site cannot maintain the total identity of features but a partial overlap since the two positions need to obey the structural forces that come from occupying respective positions. One such case is the missing object construction where the subject fillers and the object gaps are to observe requirements that are imposed on the respective positions. Others include passive constructions and topicalized structures. In this paper, it is argued that the feature discrepancy comes from the different syntactic positions in which the fillers are assumed to be located before and after displacement. In order to capture this type of mismatch, syntactically relevant features are handled separately from the semantically motivated features in order to deal with the syntactically imposed requirements.

• Sleep Medicine and Psychophysiology
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• v.9 no.2
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• pp.100-105
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• 2002

Personality traits in insomniac patients have been a subject of many studies. A number of these studies have used the MMPI and have demonstrated elevated scores on several clinical scales reflecting somatic concerns, somatization, depression, anxiety, worry and social alienation. And it was suggested that insomnia was due to a process of internalization of psychological distress. Another hypothesis about psychological mechanisms has focused upon worry. Excessive and uncontrollable cognitive activity seem to be a characteristic feature of many insomniacs. One author emphasized the role of the dependency need and found a characteristic pattern among insomniacs. The central feature of this pattern is frustration of dependency need. The purpose of this paper was to review possible personality variable that may be predisposing causal factors of insomnia. Several factors are suggested by many studies, but in order to explore their causal importance other experimental and longitudinal studies are needed.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.993-997
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• 2009

Clustering is well known method and that can be used in statistical machine translation. In this paper we propose a corpus clustering method using syntactic structure and POS information of dependency grammar. And using this cluster language model as additional feature to phrased-based statistical machine translation system to improve translation Quality.