Text Retrieval & Text Mining Journal Club
Place: B11 MacLean Hall
Goal: To study current papers from journals and conference proceedings in text retrieval and text mining. Examples of problems include topic models, web retrieval and web mining, ranking strategies, ambiguity resolution, knowledge discovery, web phenomenon including social networks, information extraction and text classification. The reading group is lead by Professor Padmini Srinivasan. Interested students (from beginning to advanced students) and faculty are invited to participate in the reading group. Participation format is informal with individuals taking turns to present an overview of the selected paper and lead the discussion. This forum has resulted in collaborative projects and published papers.
This semester we will combine this with students presenting on their research.
John Gikonyo: Feb 9
1. O. Farri, A. Rahman, K. A. Monsen, R. Zhang, S. V. Pakhomov, D. S. Pieczkiewicz, S. M. Speedie, and G. B. Melton, “Impact of a prototype visualization tool for new information in EHR clinical documents,” Appl. Clin. Inform., vol. 3, no. 4, pp. 404–418, 2012.
2. G. Hripcsak, D. K. Vawdrey, M. R. Fred, and S. B. Bostwick, “Use of electronic clinical documentation: time spent and team interactions,” J. Am. Med. Inform. Assoc. JAMIA, vol. 18, no. 2, pp. 112–117, Apr. 2011.
Yuanyang Lu: Feb 16
Meme Prediction paper
Xiaoxuan: Feb 23
Salles T, Rocha L, Pappa G L, et al. Temporally-aware algorithms for document classification[C]//Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval. ACM, 2010: 307-314.
Momina: March 2
NCBI at the 2014 BioASQ challenge task: large - scale biomedical semantic indexing and question answering. in Working Notes for CLEF 2014 Conference, vol-1180:1319-1327. Yuqing Mao, Chih - Hsuan Wei, Zhiyong Lu.
John: March 23
J., Ku, Y., & Chen, H. (2013.). Modeling the dynamics of medical information through web forums in medical industry. Technological Forecasting and Social Change. http://doi.org/10.1016/j.techfore.2013.12.006”
Momina: April 6
1. NCBI at the 2014 BioASQ challenge task: large-scale biomedical semantic indexing and question answering
2 - Automatic Classification of PubMed Abstracts with Latent Semantic Indexing
Xiaoxuan: April 13
Fung G P C, Yu J X, Lu H. Classifying text streams in the presence of concept drifts. Advances in Knowledge Discovery and Data Mining. Springer Berlin Heidelberg, 2004: 373-383.
April 20: John
Haustein, S., Larivière, V., Haustein, S., Peters, I., Sugimoto, C. R., Thelwall, M., & Larivière, V. (2014). Tweeting biomedicine: An analysis of tweets and citations in the biomedical literature. Journal of the Association for Information Science and Technology, 65(4), 656–669. http://doi.org/10.1002/asi.23101
Chao: May 4
Modeling User Attitude toward Controversial Topics in Online Social Media From ICWSM 2014