All papers, subject order.
Subject headings: general-audience papers | sentiment analysis | IR | generation | similarity-based
methods | segmentation
| CFL's |
reviews and pedagogy
General audience
Sentiment analysis
- Get out the vote: Determining support or opposition from
Congressional floor-debate transcripts.
Matt Thomas, Bo Pang, and Lillian Lee.
Proceedings of EMNLP, pp. 327–335, 2006.
- Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales.
Bo Pang and Lillian Lee.
Proceedings of the ACL, pp. 115–124, 2005.
- A
sentimental education: Sentiment analysis using subjectivity
summarization based on minimum cuts.
Bo Pang and Lillian Lee.
Proceedings of the 42nd ACL, pp. 271–278, 2004.
- Thumbs up? Sentiment classification using machine learning techniques.
Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan.
Proceedings of EMNLP 2002, pp. 79–86.
Information retrieval
- IDF revisited: A simple new derivation within the Robertson-Spärck
Jones probabilistic model.
Lillian Lee.
Procedings of
SIGIR, pp. 751–752, 2007. (poster)
- Respect my authority! HITS without hyperlinks, utilizing
cluster-based language models.
Oren Kurland and Lillian Lee.
Proceedings of SIGIR, pp. 83–90, 2006.
- PageRank
without hyperlinks: Structural re-ranking using links induced by language models.
Oren Kurland and Lillian Lee.
Proceedings of SIGIR, pp. 306–313, 2005.
- Better than the real thing? Iterative pseudo-query processing using cluster-based language models.
Oren Kurland, Lillian Lee, and Carmel Domshlak.
Proceedings of SIGIR, pp. 19–26, 2005.
- Corpus
structure, language models, and ad hoc information
retrieval.
Oren Kurland and Lillian Lee.
Proceedings of SIGIR, pp. 194–201, 2004.
- Iterative residual rescaling: An analysis and generalization of LSI.
Rie Kubota Ando and Lillian Lee.
Proceedings of the 24th SIGIR, pp. 154–162, 2001.
Generation
Distributional similarity
- On the effectiveness of the skew divergence for statistical language analysis.
Lillian Lee.
Artificial Intelligence and Statistics 2001, pp 65–72, 2001.
- Measures of Distributional Similarity.
Lillian Lee.
Proceedings of the 37th ACL, pp 25–32, 1999.
- Distributional similarity models: Clustering vs. nearest neighbors.
Lillian Lee and Fernando Pereira.
Proceedings of the 37th ACL, pp 33–40, 1999.
- Similarity-based models of word cooccurrence probabilities (pre-publication version).
Ido Dagan, Lillian Lee, and Fernando Pereira.
Machine Learning 34(1-3), special issue on natural language
learning, pp 43–69, 1999.
- Similarity-Based Methods for Word Sense Disambiguation.
Ido Dagan, Lillian Lee, and Fernando Pereira.
Proceedings of the 35th ACL/8th EACL, pp 56–63, 1997.
- Similarity-Based Approaches to Natural Language Processing.
Lillian Lee.
Ph.D. thesis.
Harvard University Technical Report TR-11-97.
- Similarity-Based Estimation of Word Cooccurrence Probabilities.
Ido Dagan, Fernando Pereira, and Lillian Lee.
Proceedings of the 32nd ACL, pp 272–278, 1994.
- Distributional clustering of English words.
Fernando Pereira, Naftali Tishby, and Lillian Lee.
Proceedings of the 31st ACL, pp 183–190, 1993.
Of related interest: Baker and McCallum's SIGIR '98 paper, Distributional
Clustering of Words for Text Classification, favorably compares [PTL
93] to LSI and other algorithms.
Segmentation
Context-free languages
Reviews and pedagogy
- A new start: Innovative introductory AI-centered courses at
Cornell.
Eric Breck, David Easley, K-Y Daisy
Fan, Jon Kleinberg,
Lillian Lee, Jennifer Wofford, and
Ramin
Zabih.
AAAI Spring Symposium on Using AI to Motivate Greater Participation in
Computer Science, 2008.
- A non-programming introduction to computer science via NLP, IR, and AI.
Lillian Lee.
ACL Workshop on Effective Tools and Methodologies for Teaching Natural Language Processing and Computational Linguistics, pp 32–37, 2002.
- Foundations of Statistical Natural Language Processing by Christopher D. Manning and Hinrich Schütze [review] (prepublication version).
Lillian Lee.
Computational Linguistics 26(2), pp 277–279, 2000.
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