Question recommendation with constraints for massive open online courses

RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems

Volumn , Issue , 2014, Pages 49-56

  Yang, Diyi ^a   Adamson, David ^a   Rosé, Carolyn Penstein ^a  

^a Carnegie Mellon University ^*  (United States)

Author keywords

Constrained question recommendation; Expertise matching; Load balance; Massive open online courses

Indexed keywords

FACTORIZATION; RECOMMENDER SYSTEMS; STUDENTS;

BASELINE METHODS; CONSTRAINED QUESTION RECOMMENDATION; DISCUSSION FORUM; EXPERTISE MATCHING; LOAD BALANCE; MASSIVE OPEN ONLINE COURSE; MATRIX FACTORIZATIONS; TRADITIONAL PRODUCTS;

E-LEARNING;

EID: 84908895536     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2645710.2645748     Document Type: Conference Paper

References (25)

1. D. Agarwal and B.-C. Chen. Regression-based latent factor models. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '09, pages 19-28, New York, NY, USA, 2009. ACM.
2. R. K. Ahuja, T. L. Magnanti, and J. B. Orlin. Network flows: Theory, algorithms, and applications. Prentice hall, 1993.
3. M. S. Amin, B. Yan, S. Sriram, A. Bhasin, and C. Posse. Social referral: Leveraging network connections to deliver recommendations. In Proceedings of the Sixth ACM Conference on Recommender Systems, RecSys '12, pages 273-276, New York, NY, USA, 2012. ACM.
4. R. M. Carini, G. D. Kuh, and S. P. Klein. Student engagement and student learning: Testing the linkages. Research in Higher Education, 47(1):1-32, 2006.
5. K. Chen, T. Chen, G. Zheng, O. Jin, E. Yao, and Y. Yu. Collaborative personalized tweet recommendation. In Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval, SIGIR '12, pages 661-670, New York, NY, USA, 2012. ACM.
6. D. Hu, S. GU, S. Wang, L. Wenyin, and E. Chen. Question recommendation for user-interactive question answering systems. In Proceedings of the 2Nd International Conference on Ubiquitous Information Management and Communication, ICUIMC '08, pages 39-44, New York, NY, USA, 2008. ACM.
7. R. Junco. The relationship between frequency of facebook use, participation in facebook activities, and student engagement. ComputersEducation, 58(1):162-171, 2012.
8. Y. Kabutoya, T. Iwata, H. Shiohara, and K. Fujimura. Effective question recommendation based on multiple features for question answering communities. In ICWSM, 2010.
9. Y. Koren. Factorization meets the neighborhood: A multifaceted collaborative filtering model. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '08, pages 426-434, New York, NY, USA, 2008. ACM.
10. Y. Koren, R. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. Computer, 42(8):30-37, Aug. 2009.
11. J. Kunegis, G. Gröner, and T. Gottron. Online dating recommender systems: The split-complex number approach. In Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web, pages 37-44. ACM, 2012.
12. D.-R. Liu and Y.-Y. Shih. Hybrid approaches to product recommendation based on customer lifetime value and purchase preferences. Journal of Systems and Software, 77(2):181-191, 2005.
13. P. Lops, M. de Gemmis, and G. Semeraro. Content-based recommender systems: State of the art and trends. In Recommender Systems Handbook, pages 73-105. Springer, 2011.
14. Y.-J. Park and A. Tuzhilin. The long tail of recommender systems and how to leverage it. In Proceedings of the 2008 ACM conference on Recommender systems, pages 11-18. ACM, 2008.
15. L. Pizzato, T. Rej, T. Chung, I. Koprinska, K. Yacef, and J. Kay. Reciprocal recommender system for online dating. In Proceedings of the Fourth ACM Conference on Recommender Systems, RecSys '10, pages 353-354, New York, NY, USA, 2010. ACM.
16. M. Qu, G. Qiu, X. He, C. Zhang, H. Wu, J. Bu, and C. Chen. Probabilistic question recommendation for question answering communities. In Proceedings of the 18th international conference on World wide web, pages 1229-1230. ACM, 2009.
17. S. Rendle. Factorization machines. In Data Mining (ICDM), 2010 IEEE 10th International Conference on, pages 995-1000. IEEE, 2010.
18. I. Roll, V. Aleven, B. M. McLaren, and K. R. Koedinger. Improving students help-seeking skills using metacognitive feedback in an intelligent tutoring system. Learning and Instruction, 21(2):267-280, 2011.
19. Y. Shi, D. Ye, A. Goder, and S. Narayanan. A large scale machine learning system for recommending heterogeneous content in social networks. In Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, pages 1337-1338. ACM, 2011.
20. W. Tang, J. Tang, T. Lei, C. Tan, B. Gao, and T. Li. On optimization of expertise matching with various constraints. Neurocomputing, 76(1):71-83, 2012.
21. L. Terveen and D. W. McDonald. Social matching: A framework and research agenda. ACM Trans. Comput.-Hum. Interact., 12(3):401-434, Sept. 2005.
22. F. Xu, Z. Ji, and B. Wang. Dual role model for question recommendation in community question answering. In Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '12, pages 771-780, New York, NY, USA, 2012. ACM.
23. D. Yang, T. Chen, W. Zhang, Q. Lu, and Y. Yu. Local implicit feedback mining for music recommendation. In Proceedings of the Sixth ACM Conference on Recommender Systems, RecSys '12, pages 91-98, New York, NY, USA, 2012. ACM.
24. D. Yang, M. Piergallini, I. Howley, and C. Rose. Forum thread recommendation for massive open online courses. In Proceedings of 7th International Conference on Educational Data Mining, 2014.
25. D. Yang, T. Sinha, D. Adamson, and C. P. Rose. Turn on, tune in, drop out: Anticipating student dropouts in massive open online courses. In Workshop on Data Driven Education, Advances in Neural Information Processing Systems 2013, 2013.