• Journal of the Korean Association of Oral and Maxillofacial Surgeons
• /
• v.49 no.4
• /
• pp.192-197
• /
• 2023

Objectives: Surgical extraction of maxillary third molars is routine in departments devoted to oral and maxillofacial surgery. Because maxillary third molars are anatomically adjacent to the maxillary sinus, complications such as oroantral fistula and maxillary sinusitis can occur. Here we explore the factors that can cause radiographic postoperative swelling of the maxillary sinus mucosa after surgical extraction. Materials and Methods: This retrospective study reviewed the clinical records and radiographs of patients who underwent maxillary third-molar extraction. Preoperative panoramas, Waters views, and cone-beam computed tomography were performed for all patients. The patients were divided into two groups; those with and those without swelling of the sinus mucosa swelling or air-fluid level in a postoperative Waters view. We analyzed the age and sex of patients, vertical position, angulation, number of roots, and relation to the maxillary sinus between groups. Statistical analysis used logistic regression and P<0.05 was considered statistically significant. Results: A total of 91 patients with 153 maxillary third molars were enrolled in the study. Variables significantly related to swelling of the maxillary sinus mucosa after surgical extraction were the age and the distance between the palatal cementoenamel junction (CEJ) and the maxillary sinus floor (P<0.05). Results of the analysis show that the relationship between the CEJ and sinus floor was likely to affect postoperative swelling of the maxillary sinus mucosa. Conclusion: Maxillary third molars are anatomically adjacent to the maxillary sinus and require careful handling when the maxillary sinus is pneumatized to the CEJ of teeth.

• Korean Journal of Cognitive Science
• /
• v.19 no.2
• /
• pp.143-161
• /
• 2008

The goal of this paper is to extract the hyponymy relation between words in the corpus. Adopting the basic algorithm of Hearst (1992), I propose a method of pattern-based extraction of semantic relations from the corpus. To this end, I set up a list of hypernym-hyponym pairs from Sejong Electronic Dictionary. This list is supplemented with the superordinate-subordinate terms of CoroNet. Then, I extracted all the sentences from the corpus that include hypemym-hyponym pairs of the list. From these extracted sentences, I collected all the sentences that contain meaningful constructions that occur systematically in the corpus. As a result, we could obtain 21 generalized patterns. Using the PERL program, we collected sentences of each of the 21 patterns. 57% of the sentences are turned out to have hyponymy relation. The proposed method in this paper is simpler and more advanced than that in Cederberg and Widdows (2003), in that using a word net or an electronic dictionary is generally considered to be efficient for information retrieval. The patterns extracted by this method are helpful when we look fer appropriate documents during information retrieval, and they are used to expand the concept networks like ontologies or thesauruses. However, the word order of Korean is relatively free and it is difficult to capture various expressions of a fired pattern. In the future, we should investigate more semantic relations than hyponymy, so that we can extract various patterns from the corpus.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.9
• /
• pp.763-770
• /
• 2004

The important issue of emotion recognition from speech is a feature extracting and pattern classification. Features should involve essential information for classifying the emotions. Feature selection is needed to decompose the components of speech and analyze the relation between features and emotions. Specially, a pitch of speech components includes much information for emotion. Accordingly, this paper searches the relation of emotion to features such as the sound loudness, pitch, etc. and classifies the emotions by using the statistic of the collecting data. This paper deals with the method of recognizing emotion from the sound. The most important emotional component of sound is a tone. Also, the inference ability of a brain takes part in the emotion recognition. This paper finds empirically the emotional components from the speech and experiment on the emotion recognition. This paper also proposes the recognition method using these emotional components and the transition probability.

• Annual Conference on Human and Language Technology
• /
• 2015.10a
• /
• pp.90-95
• /
• 2015

기계적 학습을 위해서는 일반적으로 많은 양의 수동 주석데이터(Manually Labeled Data)가 요구된다. 원격지도(Distant Supervision)는 현실적으로 부족한 주석데이터(Labeled Data)를 대신해 자동적으로 주석데이터를 수집하여 학습하는 접근 방식으로 관계 추출(Relation Extracion) 문제에 널리 활용되고 있다. 이때 필연적으로 많은 노이즈(Noise)가 발생되는데, 적합성 검증(Relevance Verification)을 통해 수집된 학습데이터를 정제함으로써 노이즈로 인한 변동성을 줄이고 결과적으로 향상된 성능을 보여주는 관계 추출 방법을 제시한다.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.12a
• /
• pp.45-48
• /
• 2000

A typical map image is consisted of number, symbols and lines that represent contour lines, geographical bounaries, roads, rivers and etc. This paper describe the separation. The separation algorithm is based on structural relation. The separation of proposed method is better than method using only a size of connected component. This proposed method will be used in GIS input system efficiently.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2004.05b
• /
• pp.354-357
• /
• 2004

Data warehouse is subject-oriented, integrated, non-volatiled data, and it used for OLAP(On-Line Analytical Processing) the extraction of information from making decision processing. In the present, lots of study have been devoted to multidimensional modeling between OLAP operator and star schema. In this paper, the design of using the snowflake schema for object-oriented conceptual relation is more extended than using drill-across operator. The object-oriented relation schema which was not applicable has been improved through the design.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2018.05a
• /
• pp.285-288
• /
• 2018

데이터 정형화기술은 자연어 처리 및 인공지능분야, 데이터베이스 등 다양한 분야에서 중요한 핵심적인 기술 중 하나이다. 최근 정형화 문제를 푸는 많은 신경망 기반 알고리즘들이 제안되었으나, 기존의 모든 알고리즘이 키워드의 후보가 입력으로 주어진다고 가정하고 있으며, 알고리즘 대부분은 두 개의 속성(attribute)을 가지는 이진 관계(binary relation)만 처리할 수 있다는 한계가 있다. 본 논문에서는 컨볼루션 신경망을 이용한 N항 관계 정형화 방업을 제안하고, 이를 이용한 구인 광고 정형화 시스템을 개발하고 성능을 평가한다.

• International Journal of Advanced Culture Technology
• /
• v.6 no.4
• /
• pp.317-322
• /
• 2018

We use edge detection technique for the input image to extract the entire edges of the object in the image and then select only the edges that construct the outline of the object. By examining the positional relation between these pixels composing the outline, a simplified version of the outline of the object in the input image is generated by removing unnecessary pixels while maintaining the condition of connection of the outline. For each pixel constituting the outline, its direction is calculated by examining the positional relation with the next pixel. Then, we group the consecutive pixels with same direction into one and then change them to a line segment instead of a point. Among those line segments composing the outline of the object, a line segment whose length is smaller than a predefined minimum length of acceptable line segment is removed by merging it into one of the adjacent line segments. As a result, an outline composed of line segments of over a certain length is obtained through this process.

• Journal of Information Management
• /
• v.40 no.4
• /
• pp.1-22
• /
• 2009

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In this study, we define scientific as a set of 10 types of named entities and technical terminologies in a biomedical domain. in order to automatically extract these entities from scientific documents at once, we develop a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer, co-reference resolver and terminology extractor. Each module of the integrated system has been evaluated with various corpus as well as KEEC 2009. The system will be utilized for various information service areas such as information retrieval, question-answering(Q&A), document indexing, dictionary construction, and so on.

• Journal of Korean Medical classics
• /
• v.25 no.4
• /
• pp.105-113
• /
• 2012

Objectives : Acquiring information from symptoms is one of the important method to gain clinically available information in korean medicine. Therefore, up to now, study of symptom terms was frequently implemented in promotion of various information project. In data extraction methods using symptom information from DB, information search using synonym and method using ontology is studied and utilized. However, considering concept of symptom has essential information of appeared body area and phenomenon we think that extending synonym and ontology relationship in symptom terms can be useful for search and set to this study. Methods : We collect terms relevant to human body area and structure described in Donguibogam. Synonymous relationship between collected terms is organized. Relationship between collected terms is build to human-body-knowledge table which has form of Concept+Relation+Concept. Type of relationship is limited on a range of expressing content about parts of human body. Result & Conclusion : Search condition is generated automatically using relationship of the upper area in knowledge table contents. Information of next and previous acupuncture point, upper and lower acupuncture point, left and right acupuncture point can be searched using information of acupuncture point location, order, relative position in area, direction in knowledge table contents.