• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.173-182
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• 2013

Typographical mistakes made in the writing process of drafts of electronic documents are more common than any other type of errors. The majority of these errors caused by mistyping are regarded as consequently still typo-errors, but a considerable number of them are developed into the grammatical errors and the semantic errors. Pseudo semantic errors among these errors due to typographical errors have more noticeable peculiarities than pure semantic errors between senses of surrounding context words within a sentence. These semantic errors can be detected and corrected by simple algorithm based on the co-occurrence frequency because of their prominent contextual discrepancy. I propose a method for detection and correction based on the co-occurrence frequency in order to detect semantic errors due to typo-errors. The co-occurrence frequency in proposed method is counted for only words with immediate dependency relation, and the cosine similarity measure is used in order to detect pseudo semantic errors. From the presented experimental results, the proposed method is expected to help improve the detecting rate of overall proofreading system by about 2~3%.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.71-76
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• 2022

The purpose of this research is to investigate the types of semantic errors made by MT in translating EFL college students' original drafts written in Korean into English. Specifically, this study attempts to find out 1) what types of semantic errors are most frequently committed by MT? and 2) how students feel about the quality of the MT-produced output? The findings from this study indicated that MT produced the errors related to accuracy (47%) the most, followed by the errors related to fluency and ambiguity (14.6% respectively). Students were well aware of the errors with accuracy and fluency but had limited ability to check the errors with ambiguity. Based on the findings, this study suggests pedagogical implications which can be implemented in L2 writing classrooms.

• Journal of Information Technology Services
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• v.10 no.3
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• pp.189-201
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• 2011

Feature models are widely used to model commonalities and variabilities among products during software product line development. Feature configurations are generated by selecting the features to be included in individual products. Automated tools to identify errors or inconsistencies in the feature models and configurations are essential to successful software product line engineering. This paper proposes a verification technique and tool based on semantic web technologies such as OWL, SWRL and Protege API. This approach checks the feature model and configuration based on predefined rules and provides information on existence of errors as well as the kinds of those errors. This approach is extensible due to ease of rule modification and may be easily applied to other environments because semantic web technologies can be easily integrated with other programming environments. This paper demonstrates how various semantic web-related technologies can support automatic verification of one kind of software development artifact, the feature model.

• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.1-25
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• 2008

Spoken dialog tasks incur many errors including speech recognition errors, understanding errors, and even dialog management errors. These errors create a big gap between the user's intention and the system's understanding, which eventually results in a misinterpretation. To fill in the gap, people in human-to-human dialogs try to clarify the major causes of the misunderstanding to selectively correct them. This paper presents a method of clarification techniques to human-to-machine spoken dialog systems. We viewed the clarification dialog as a two-step problem-Belief confirmation and Clarification strategy establishment. To confirm the belief, we organized the clarification process into three systematic phases. In the belief confirmation phase, we consider the overall dialog system's processes including speech recognition, language understanding and semantic slot and value pairs for clarification dialog management. A clarification expert is developed for establishing clarification dialog strategy. In addition, we proposed a new design of plugging clarification dialog module in a given expert based dialog system. The experiment results demonstrate that the error verifiers effectively catch the word and utterance-level semantic errors and the clarification experts actually increase the dialog success rate and the dialog efficiency.

• Language and Information
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• v.14 no.1
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• pp.165-196
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• 2010

The primary goal of this paper is to propose methods of enriching two heterogeneous ontologies: Sejong Semantic Classes (SJSC) and KorLexNoun 1.5 (KLN). In order to achieve this goal, this study introduces the pros and cons of two ontologies, and analyzes the error patterns found during the fine-grained manual mapping processes between them. Error patterns can be classified into four types: (1) structural defectives involved in node branching, (2) errors in assigning the semantic classes, (3) deficiency in providing linguistic information, and (4) lack of the lexical units representing specific concepts. According to these error patterns, we propose different solutions in order to correct the node branching defectives and the semantic class assignment, to complement the deficiency of linguistic information, and to increase the number of lexical units suitably allotted to their corresponding concepts. Using the results of this study, we can obtain more enriched ontologies by correcting the defects and errors in each ontology, which will lead to the enhancement of practicality for syntactic and semantic analysis.

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.213-219
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• 2020

The purpose of this study was to investigate the characteristics of error types in naming task for 8 questionable demeatia groups, 9 definite dementia groups, and 10 normal groups. The items of naming error analysis were classified into visual perception errors, semantic association errors, semantic non-correlation errors, phoneme errors, Don't Know, and No Response. For the analysis, descriptive statistics analysis, analysis of variance, and multivariate analysis of variance were conducted using SPSS 21.0. As a result, there was a significant difference in the error rate between groups according to the error type. The errors that showed significant differences between the normal group and the other two groups were visual perception errors and semantic non-related errors. The error of non-response was different from the dementia confirmation group, but there was no significant difference from the dementia suspicion group. These results showed that Alzheimer's patients had a defect in confrontation naming ability. Also, it was found that it is appropriate to provid other clues when the defects caused by the degeneration of a specific step during the information processing process become severe.

• Journal of the Ergonomics Society of Korea
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• v.23 no.4
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• pp.9-21
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• 2004

As menu structure of household appliance is complicated, user's cognitive workload frequently occurs errors. In existing studies, errors didn't present that interpretation for cognitive factors and alternatives, but are only considered as statistical frequency. Therefore, error classification and analysis in tasks is inevitable in usability evaluation. This study classified human error throughout information process model and navigation behavior. Human error is defined as incorrect decision and behavior reducing performance. And navigation is defined as unrelated behavior with target item searching. We searched and analyzed human errors and its causes as a case study, using mobile phone which could control appliances in near future. In this study, semantic problems in menu structure were elicited by SAT. Scenarios were constructed by those. Error analysis tests were performed twice to search and analyze errors. In 1st prototype test, we searched errors occurred in process of each scenario. Menu structure was revised to be based on results of error analysis. Henceforth, 2nd Prototype test was performed to compare with 1st. Error analysis method could detect not only mistakes, problems occurred by semantic structure, but also slips by physical structure. These results can be applied to analyze cognitive causes of human errors and to solve their problems in menu structure of electronic products.

• Journal of Information Technology Services
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• v.7 no.3
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• pp.271-286
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• 2008

The core of the semantic web is ontology, which supports interoperability among semantic web applications and enables developer to reuse and share domain knowledge. It used a variety of fields such as Information Retrieval, E-commerce, Software Engineering, Artificial Intelligence and Bio-informatics. However, the reality is that various errors might be included in conceptual hierarchy when developing ontologies. Therefore, methodologies and supporting tools are essential to help the developer construct suitable ontologies for the given purposes and to detect and analyze errors in order to verify the inconsistency in the ontologies. In this paper we propose a new approach for ontology error detection based on the Concept Lattices of Formal Concept Analysis. By using the tool that we developed in this research, we can extract core elements from the source code of Ontology and then detect some structural errors based on the concept lattices. The results of this research can be helpful for ontology engineers to support error detection and construction of "well-defined" and "good" ontologies.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.504-512
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• 2019

This study aims to investigate language society cultural aspects in a community, examining and comparing linguistic errors of English signboards (ES) at home and abroad. The data comprised the ES in 5 cities, Korea and in Paris, France. The findings showed that the errors of the ES in Korea reached to 39.2%, whereas those in Paris contained 24.7%. In Korea, ES and errors were the most in Myeong-dong area. In Paris, the most ES were in the area of Eiffel Tower, but the most linguistic errors appeared at the 3, 4 districts of Marais. Those errors belonged to most in the business of drink, food, and clothes in turn in Korea, while this was the case in the field of clothes, food, and culture in Paris. The frequent errors were classified into semantic, morphologic, and syntactic aspects in turn. The regulations on signboards of foreign languages existed but were not abided by in the both countries. Thus, more practical and reasonable devices and policies are required to establish a more harmonious atmosphere of the ES.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.389-394
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• 1996

The product-user interface for consumer electronic products became complex due to the increased variety of functions corresponding to consumer needs. In this study, three types fo design improvement of the menu interface for a video cassette recorder is studied. Three modifications to an existing menu interface was designed using the semantic, the syntactic and the lexical design factors. A series of the validation experiments was performed to test the effect of the three types of task modifications. The results showed that performance time, number of errors and learning effect were improved for all task modification. It also showed that the performance improvement effect of the semantic factors was 8.8%, that of the syntactic factors was 5.9% and that of the lexical factors was 5.6% respectively. It was found out that the performance improvement effect of the semantic design factors were relatively more significant than the syntactic and the lexical design factors.