10 Result(s)
within
Chapter
Yu-Seop Kim
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Chapter and Conference Paper
Looking for Better Combination of Biomarker Selection and Classification Algorithm for Early Screening of Ovarian Cancer
This paper demonstrates and evaluates the classification performance of the optimal biomarker combinations that can diagnose ovarian cancer under Luminex exposed environment. The optimal combinations were dete...
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Chapter and Conference Paper
Calibration of Urine Biomarkers for Ovarian Cancer Diagnosis
For the ovarian cancer diagnosis with biomarkers in urine samples, various calibration functions are selected and investigated to compensate the variability of their concentrations. The 15 biomarkers tested in...
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Chapter and Conference Paper
A Multi-phase Semi-supersense Tagging of Korean Unknown Nouns
Supersense tagging is a problem of finding a corresponding semantic super tag (eg. Phenomenon, Act) based on syntactic information and annotated corpora. However, we employ semantic information rather than syn...
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Chapter and Conference Paper
KOST: Korean Semantic Tagger ver. 1.0
Despite that the semantic annotated corpus data is necessary in semantic role labeling of natural language processing, the data set is not quite enough in Korean language. Semantic role labeling is to tag a se...
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Chapter and Conference Paper
Sentence Difficulty Analysis with Local Feature Space and Global Distributional Difference
In this paper, we consider the problem of sentence difficulty analysis from various angles. Past works have endeavored to design deterministic scoring algorithms depending only on semantic and syntactic inform...
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Chapter and Conference Paper
Construction of Korean Semantic Annotated Corpus
Semantic role labeling is to determine semantic relationships between a predicate and its arguments in a sentence. Although semantic annotated corpus should be necessary to do the labeling, unfortunately, Kore...
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Chapter and Conference Paper
An Intelligent Grading System for Descriptive Examination Papers Based on Probabilistic Latent Semantic Analysis
In this paper, we developed an intelligent grading system, which scores descriptive examination papers automatically, based on Probabilistic Latent Semantic Analysis (PLSA). For grading, we estimated semantic ...
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Chapter and Conference Paper
An Intelligent Grading System Using Heterogeneous Linguistic Resources
In this paper, we propose an intelligent grading system using heterogeneous linguistic resources. We used latent semantic kernel as one resource in former research and found that a deficit of indexed terms gav...
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Chapter and Conference Paper
An Empirical Study on Dimensionality Optimization in Text Mining for Linguistic Knowledge Acquisition
In this paper, we try to find empirically the optimal dimensionality in data-driven models, Latent Semantic Analysis (LSA) model and Probabilistic Latent Semantic Analysis (PLSA) model. These models are used f...
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Chapter and Conference Paper
Machine Translation Systems: E-K, K-E, J-K, K-J
We present four kinds of machine translation system in this description: E-K (English to Korean), K-E (Korean to English), J-K (Japanese to Korean), K-J (Korean to Japanese). Among these, E-K and K-J translati...
