상세 보기
Job recommendation in askstory: Experiences, methods, and evaluation
- Lee, Yeon-Chang;
- Hong, Jiwon;
- Kim, Sang-Wook
Citations
SCOPUS
6초록
AskStory is an e-recruitment site that maintains a large number of resumes and job openings. Job seekers in AskStory have difficulty in finding proper job openings that she/he is likely to be interested in. We discuss an approach to recommend job openings to jobs seekers. We identify the properties of the dataset used in job recommendation, discover the problems caused by the properties, and propose the methods for alleviating the problems. We evaluate our approach through extensive experiments. The results show that our approach is effective in alleviating the problems and provides recommendation accuracy satisfactory to job seekers.
키워드
E-recruitment sites; Job matching; Job recommendation; Job matching; Job recommendation; Job seekers; Job-openings; Recommendation accuracy; Computation theory
- 제목
- Job recommendation in askstory: Experiences, methods, and evaluation
- 저자
- Lee, Yeon-Chang; Hong, Jiwon; Kim, Sang-Wook
- 발행일
- 2016-04
- 유형
- Conference Paper
- 저널명
- Proceedings of the ACM Symposium on Applied Computing
- 권
- 04-08-April-2016
- 페이지
- 780 ~ 786