DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kil, Rhee-Man | - |
dc.contributor.advisor | 길이만 | - |
dc.contributor.author | Harvey Jezlid, Rosas Quintero | - |
dc.contributor.author | 하비, 로사스 | - |
dc.date.accessioned | 2011-12-14T04:55:41Z | - |
dc.date.available | 2011-12-14T04:55:41Z | - |
dc.date.issued | 2006 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=260051&flag=dissertation | - |
dc.identifier.uri | http://hdl.handle.net/10203/42146 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 응용수학전공, 2006.8, [ vi, 37 p. ] | - |
dc.description.abstract | Large scale databases are more common in many application areas of data mining. Most of them contains an incredible amount of information in text format, thus as the volume of electronic information grows, so does its complexity to analyze it and understand it. In this thesis, various types of statistical feature extraction and classification methods are introduced, and the performances of text classification for the benchmark data set Reuters-21578 are compared. It is also suggested the possible improvements of text mining methods through the analysis of simulation results. | eng |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Machine Learning | - |
dc.subject | Classification | - |
dc.subject | Feature Extraction | - |
dc.subject | Text Mining | - |
dc.subject | Data Mining | - |
dc.subject | 데이터 마이닝 | - |
dc.subject | 기계학습 | - |
dc.subject | 분류 | - |
dc.subject | 특징 추출 | - |
dc.subject | 텍스트 마이닝 | - |
dc.title | Statistical feature extraction for machine learning-based text mining | - |
dc.title.alternative | 기계학습 기반 텍스트 마이닝을 위한 통계적 특징 추출 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 260051/325007 | - |
dc.description.department | 한국과학기술원 : 응용수학전공, | - |
dc.identifier.uid | 020044326 | - |
dc.contributor.localauthor | Kil, Rhee-Man | - |
dc.contributor.localauthor | 길이만 | - |
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