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논문검색

정보 소득율 기반의 변수 선택을 통한 영화 관객 수 예측

원문정보

Predicting the Number of Movie Audiences Through Variable Selection Based on Information Gain Measure

박현목, 최상현

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

In this study, we propose a methodology for predicting the movie audience based on movie information that can be easily acquired before opening and effectively distinguishing qualitative variables. In addition, we constructed a model to estimate the number of movie audiences at the time of data acquisition through the configured variables. Another purpose of this study is to provide a criterion for categorizing success of movies with qualitative characteristics. As an evaluation criterion, we used information gain ratio which is the node selection criterion of C4.5 algorithm. Through the procedure we have selected 416 movie data features. As a result of the multiple linear regression model, the performance of the regression model using the variables selection method based on the information gain ratio was excellent.

목차

Abstract
1. 서론
2. 영화 관객 수 예측 선행연구
3. 분석대상 영화에 대한 기초통계 분석
4. 데이터 분할 및 전처리
4.1 데이터 분할
4.2 데이터 전처리
5. 데이터마이닝 모델 적용결과 분석
6. 결론
References

저자정보

  • 박현목 Hyeon-Mock Park. Department of Bigdata, Chungbuk National University
  • 최상현 Sang Hyun Choi. Professor, Department of MIS, Chungbuk National University

참고문헌

자료제공 : 네이버학술정보

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