원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.9 No.9
2016.09
pp.139-148
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper presents a data-driven methodology to disambiguate a query by suggesting relevant subcategories within a specific domain. This is achieved by finding correlations between the user’s search history and the context of the current search keyword. We apply automatic categorization on each query to identify a list of categories which can describe the query given. To predict the categories of a user input query, we employed machine learning algorithms. We present the preliminary evaluation results and conclude with future work.
목차
Abstract
1. Introduction
2. Our Approach
2.1. Data Pre-processing
2.2. Categorization
2.3. Data Preparation
2.4. Categorization Learning
3. Evaluation
3.1. Results
3.2. Discussions
4. Conclusion
Acknowledgement
References
1. Introduction
2. Our Approach
2.1. Data Pre-processing
2.2. Categorization
2.3. Data Preparation
2.4. Categorization Learning
3. Evaluation
3.1. Results
3.2. Discussions
4. Conclusion
Acknowledgement
References
저자정보
참고문헌
자료제공 : 네이버학술정보