• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.829-836
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• 2003

In this paper, we propose a stochastic model for sentence speech understanding using dictionary and thesaurus. The proposed model extracts words from an input speech or text into a sentence. A computer is sellected category of dictionary database compared the word extracting from the input sentence calculating a probability value to the compare results from stochastic model. At this time, computer read out upper dictionary information from the upper dictionary searching and extracting word compared input sentence caluclating value to the compare results from stochastic model. We compare adding the first and second probability value from the dictionary searching and the upper dictionary searching with threshold probability that we measure the sentence understanding rate. We evaluated the performance of the sentence speech understanding system by applying twenty questions game. As the experiment results, we got sentence speech understanding accuracy of 79.8%. In this case, probability ($\alpha$) of high level word is 0.9 and threshold probability ($\beta$) is 0.38.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.124-135
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• 2021

Object detection is a fundamental yet challenging task in computer vision that plays an important role in object recognition, tracking, scene analysis and understanding. This paper aims to propose a multiproperty fusion algorithm for moving object detection. First, we build a scale-invariant feature transform (SIFT) vector field and analyze vectors in the SIFT vector field to divide vectors in the SIFT vector field into different classes. Second, the distance of each class is calculated by dispersion analysis. Next, the target and contour can be extracted, and then we segment the different images, reversal process and carry on morphological processing, the moving objects can be detected. The experimental results have good stability, accuracy and efficiency.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.113-124
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• 2022

News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.308-310
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• 2022

With the rise of the Al wave, task-oriented dialogue systems have become one of the popular research directions in academia and industry. Currently, task-oriented dialogue systems mainly adopt pipelined form, which mainly includes natural language understanding, dialogue state decision making, dialogue state tracking and natural language generation. However, pipelining is prone to error propagation, so many task-oriented dialogue systems in the market are only for single-round dialogues. Usually single- domain dialogues have relatively accurate semantic understanding, while they tend to perform poorly on multi-domain, multi-round dialogue datasets. To solve these issues, we developed a paddle-based multi-domain task-oriented Chinese dialogue system. It is based on NEZHA-base pre-training model and CrossWOZ dataset, and uses intention recognition module, dichotomous slot recognition module and NER recognition module to do DST and generate replies based on rules. Experiments show that the dialogue system not only makes good use of the context, but also effectively addresses long-term dependencies. In our approach, the DST of dialogue tracking state is improved, and our DST can identify multiple slotted key-value pairs involved in the discourse, which eliminates the need for manual tagging and thus greatly saves manpower.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1519-1530
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• 1997

Object-oriented software, reusability enables to specialize the software techniques by leading the user friendly thought and meets the user's need only concentrating on convenience of development environment. Reuse effect can be maximized through retrieval system. In this paper, we development the MT-Views(Multiple-Template Views) to realize the reuse effect as integrated reuse system including retrieval, understanding and rebuilding tools based on class library. We used the hybrid retrieval model for easy and efficient retrieval of similar software components. With using these tools, users can retrieve the reusable components and reuse the components for constructing therir own applications. Also, we can acquire many informations about retrieved components, so can rebuild components conforming our original intend.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.397-400
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• 2021

To solve the problem that existing computing methods cannot adequately represent the semantic features of sentences, Siamese TRAT, a semantic feature extraction model based on Transformer encoder is proposed. The transformer model is used to fully extract the semantic information within sentences and carry out deep semantic coding for sentences. In addition, the interactive attention mechanism is introduced to extract the similar features of the association between two sentences, which makes the model better at capturing the important semantic information inside the sentence. As a result, it improves the semantic understanding and generalization ability of the model. The experimental results show that the proposed model can improve the accuracy significantly for the semantic similarity calculation task of English and Chinese, and is more effective than the existing methods.

• Journal of Conservation Science
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• v.36 no.4
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• pp.244-254
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• 2020

This study investigates prehistoric human subsistence and pottery use on the Korean peninsula through the organic residue analysis of archaeological potsherds. Ancient human subsistence is one of the core topics in Korean archaeology. However, due to the high acidity of sediments, which prevents the long-term preservation of organic remains, archaeologists have been short of critical information on how these early prehistoric dwellers lived. Ceramic vessels can contain well-preserved lipids originating from past culinary practices. For a better understanding of human subsistence on the prehistoric Korean peninsula, food-processing behaviors were reconstructed by analyzing ancient lipids extracted from a pottery matrix. The potsherd samples used in the analysis in this paper were collected from major prehistoric habitation sites. The results show that subsistence strategies differed according to both location and time period and reveal how organic residue analysis can contribute to a better understanding of prehistoric human subsistence strategies.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.207-214
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• 2004

This study focused on providing a methodology to utilize temporal information obtained from remotely sensed data for monitoring a wide variety of targets on the earth's surface. Generally, a methodology in understanding of global changes is composed of mapping, quantifying, and monitoring changes in the physical characteristics of land cover. The selected processing and analysis technique affects the quality of the obtained information. In this research, feature extraction methodology is proposed based on segmentation. It requires a series of processing of multitempotal images: preprocessing of geometric and radiometric correction, image subtraction/thresholding technique, and segmentation/thresholding. It results in the mapping of the change-detected areas. Here, the appropriate methods are studied for each step and especially, in segmentation process, a method to delineate the exact boundaries of features is investigated in multiresolution framework to reduce computational complexity for multitemporal images of large size.

• Korean Journal of Remote Sensing
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• v.3 no.2
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• pp.121-141
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• 1987

Many techniques of image processing have been developed to analyse more precisely geological information obtained from satellites. SPOT, which is a recent project in France, will furnish stereoscopic image, with good resolution of surfaces(20m $\times$ 20m or 10m $\times$ 10m), and give altitudes(DEM) which can be restored automatically. One of the researches for the exploitation of this data, intends to recognize and distinguish automatically the geomorphological forms, containing important geological information from DEM. Along which the information obtained obtained from image processing, it will play an important role in the understanding of the surface of the terrain. This study was carried out in collaboration with University of Paris-6 and Ecole National des Sciences G$\'{e}$ographiques(Institute G$\'{e}$ographique National of France: IGN).

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.728-730
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• 2017

The proposed application design for emergency medical system includes the functions that help securing the window of opportunity for the patients in an emergency situation and efficiently link rescue agency, emergency medical treatment center and patients together. First, the treatment time can be saved at the emergency room by understanding the patient's condition by entering his/her health information such as anamnesis, family history, social history and blood type together with an identification number. Also, if the siren function which signals whereabouts of patients to the rescue crew is used, it will be much easier to find the location of the patient in need. The design allows rescue crew to call the patient to check whether he/she is conscious or not. Just by receiving the call, he/she will be deemed conscious.