Get our free extension to see links to code for papers anywhere online!

Add to Chrome

Add to Firefox

Picture for Lillian Lee

Lillian Lee

Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization

May 12, 2004
Regina Barzilay, Lillian Lee

Figure 1 for Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization

Figure 2 for Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization

Figure 3 for Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization

Figure 4 for Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization

* HLT-NAACL 2004: Proceedings of the Main Conference, pp. 113--120
* Best paper award

Access Paper or Ask Questions

"I'm sorry Dave, I'm afraid I can't do that": Linguistics, Statistics, and Natural Language Processing circa 2001

Apr 21, 2003
Lillian Lee

* In "Computer Science: Reflections on the Field, Reflections from the Field" (report of the National Academies' Study on the Fundamentals of Computer Science), pp. 111--118, 2004
* To appear, National Research Council study on the Fundamentals of Computer Science. 7 pages

Access Paper or Ask Questions

Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment

Apr 02, 2003
Regina Barzilay, Lillian Lee

Figure 1 for Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment

Figure 2 for Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment

Figure 3 for Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment

Figure 4 for Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment

* Proceedings of HLT-NAACL 2003 (Human Language Technology Conference)

Access Paper or Ask Questions

Thumbs up? Sentiment Classification using Machine Learning Techniques

May 28, 2002
Bo Pang, Lillian Lee, Shivakumar Vaithyanathan

Figure 1 for Thumbs up? Sentiment Classification using Machine Learning Techniques

Figure 2 for Thumbs up? Sentiment Classification using Machine Learning Techniques

Figure 3 for Thumbs up? Sentiment Classification using Machine Learning Techniques

* To appear in EMNLP-2002

Access Paper or Ask Questions

Bootstrapping Lexical Choice via Multiple-Sequence Alignment

May 25, 2002
Regina Barzilay, Lillian Lee

Figure 1 for Bootstrapping Lexical Choice via Multiple-Sequence Alignment

Figure 2 for Bootstrapping Lexical Choice via Multiple-Sequence Alignment

Figure 3 for Bootstrapping Lexical Choice via Multiple-Sequence Alignment

Figure 4 for Bootstrapping Lexical Choice via Multiple-Sequence Alignment

* 8 pages; to appear in the proceedings of EMNLP-2002

Access Paper or Ask Questions

Mostly-Unsupervised Statistical Segmentation of Japanese Kanji Sequences

May 10, 2002
Rie Kubota Ando, Lillian Lee

Figure 1 for Mostly-Unsupervised Statistical Segmentation of Japanese Kanji Sequences

Figure 2 for Mostly-Unsupervised Statistical Segmentation of Japanese Kanji Sequences

Figure 3 for Mostly-Unsupervised Statistical Segmentation of Japanese Kanji Sequences

Figure 4 for Mostly-Unsupervised Statistical Segmentation of Japanese Kanji Sequences

* Natural Language Engineering 9 (2), pp. 127--149, 2003
* 22 pages. To appear in Natural Language Engineering

Access Paper or Ask Questions

Fast Context-Free Grammar Parsing Requires Fast Boolean Matrix Multiplication

Dec 15, 2001
Lillian Lee

Figure 1 for Fast Context-Free Grammar Parsing Requires Fast Boolean Matrix Multiplication

Figure 2 for Fast Context-Free Grammar Parsing Requires Fast Boolean Matrix Multiplication

Figure 3 for Fast Context-Free Grammar Parsing Requires Fast Boolean Matrix Multiplication

Figure 4 for Fast Context-Free Grammar Parsing Requires Fast Boolean Matrix Multiplication

* Journal of the ACM 49(1), pp. 1--15, January 2002
* To appear in Journal of the ACM

Access Paper or Ask Questions

Iterative Residual Rescaling: An Analysis and Generalization of LSI

Jun 17, 2001
Rie Kubota Ando, Lillian Lee

* Proceedings of the 24th SIGIR, pp. 154--162, 2001.
* To appear in the proceedings of SIGIR 2001. 11 pages

Access Paper or Ask Questions

Measures of Distributional Similarity

Jan 18, 2000
Lillian Lee

Figure 1 for Measures of Distributional Similarity

Figure 2 for Measures of Distributional Similarity

Figure 3 for Measures of Distributional Similarity

Figure 4 for Measures of Distributional Similarity

* 37th Annual Meeting of the ACL, 1999, pp. 25-32
* 9 pages, 3 figures

Access Paper or Ask Questions

Similarity-Based Models of Word Cooccurrence Probabilities

Sep 27, 1998
Ido Dagan, Lillian Lee, Fernando C. N. Pereira

Figure 1 for Similarity-Based Models of Word Cooccurrence Probabilities

Figure 2 for Similarity-Based Models of Word Cooccurrence Probabilities

Figure 3 for Similarity-Based Models of Word Cooccurrence Probabilities

Figure 4 for Similarity-Based Models of Word Cooccurrence Probabilities

* Machine Learning, 34, 43-69 (1999)
* 26 pages, 5 figures

Access Paper or Ask Questions