Papers

    2015

  • Vered Shwartz, Omer Levy, Ido Dagan, and Jacob Goldberger. Learning to Exploit Structured Resources for Lexical Inference. CoNLL, 2015. [pdf] [supplementary]
  • Tae-Gil Noh, Sebastian Pado, Vered Shwartz, Ido Dagan, Vivi Nastase, Kathrin Eichler, Lili Kotlerman and Meni Adler. Multi-Level Alignments as an Extensible Representation Basis for Textual Entailment Algorithms. Proceedings of *SEM (short paper), 2015. [pdf]
  • Roy Bar-Haim, Ido Dagan and Jonathan Berant. Knowledge-Based Textual Inference via Parse-Tree Transformations. Journal of Artificial Intelligence Research. 2015.
  • Lili Kotlerman, Ido Dagan, Bernardo Magnini, and Luisa Bentivogly. Textual Entailment Graphs. Natural Language Engineering. 2015.
  • Chaya Liebeskind, Lili Kotlerman, and Ido Dagan. . Text categorization from category name in an industry-motivated scenario. Language Resources and Evaluation, 49(2):227–261. 2015.
  • Jonathan Berant, Noga Alon, Ido Dagan, Jacob Goldberger. Efficient Global Learning of Entailment Graphs Long paper in The Journal of Computational Linguistics 41(2) (2015).
  • Oren Melamud, Omer Levy, Ido Dagan. A Simple Word Embedding Model for Lexical Substitution. Workshop on Vector Space Modeling for NLP (VSM), 2015. [pdf]
  • Oren Melamud, Ido Dagan, Jacob Goldberger. Modeling Word Meaning in Context with Substitute Vectors. NAACL, 2015. [pdf]
  • Omer Levy, Steffen Remus, Chris Biemann, and Ido Dagan. Do Supervised Distributional Methods Really Learn Lexical Inference Relations? NAACL, 2015. [pdf]
  • Omer Levy, Yoav Goldberg, and Ido Dagan. Improving Distributional Similarity with Lessons Learned from Word Embeddings. TACL, 2015. [pdf]
  • 2014

  • Omer Levy and Yoav Goldberg. Neural Word Embeddings as Implicit Matrix Factorization. NIPS, 2014. [pdf]
  • Roee Aharoni, Moshe Koppel and Yoav Goldberg. Automatic Detection of Machine Translated Text and Translation Quality Estimation. In Proceedings of ACL (short papers), June 2014. [pdf]
  • Asher Stern and Ido Dagan. Recognizing Implied Predicate-Argument Relationships in Textual Inference. In Proceedings of ACL (short papers), June 2014. [pdf]
  • Gabriel Stanovsky, Jessica Ficler, Ido Dagan and Yoav Goldberg. Intermediary Semantic Representation Through Proposition Structures. In proceedings of ACL Semantic Parsing Workshop, June 2014. [pdf]
  • Bernardo Magnini, Roberto Zanoli, Ido Dagan, Kathrin Eichler, Gunter Neumann, Tae-Gil Noh, Sebastian Pado, Asher Stern, and Omer Levy. The Excitement Open Platform for Textual Inferences. In proceedings of ACL demo session, June 2014. [pdf]
  • Omer Levy, Ido Dagan, and Jacob Goldberger. Focused Entailment Graphs for Open IE Propositions. In proceedings of CoNLL, June 2014.  [pdf]
  • Oren Melamud, Ido Dagan, Jacob Goldberger, Idan Szpektor and Deniz Yuret. Probabilistic Modeling of Joint-context in Distributional Similarity. In proceedings of CoNLL, June 2014. Best paper runner-up. [pdf]
  • Torsten Zesch and Oren Melamud. Automatic Generation of Challenging Distractors Using Context-Sensitive Inference Rules. Workshop on Innovative Use of NLP for Building Educational Applications (BEA), June 2014. [pdf]
  • Omer Levy and Yoav Goldberg. Linguistic Regularities in Sparse and Explicit Word Representations. In proceedings of CoNLL, June 2014. Best paper. [pdf]
  • Omer Levy and Yoav Goldberg. Dependency-Based Word Embeddings. In Proceedings of ACL (short papers), June 2014. [pdf]
  •  

    2013

  • Torsten Zesch, Omer Levy, Iryna Gurevych, and Ido Dagan. UKP-BIU: Similarity and Entailment Metrics for Student Response Analysis. Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), pages 285-289, Atlanta, Georgia, USA, June, 2013. [pdf]
  • Hadas Zohar, Chaya Liebeskind, Jonathan Schler and Ido Dagan. Automatic thesaurus construction for cross generation corpus. Journal on Computing and Cultural Heritage (JOCCH), Volume 6 Issue 1, pp. 4:1-4:19, March 2013.
  • Idan Szpektor, Hristo Tanev, Ido Dagan, Bonaventura Coppola and Milen Kouylekov. Unsupervised Acquisition of Entailment Relations from the Web. Natural Language Engineering. 45 pages, 2013.
  • Asher Stern and Ido Dagan. The BIUTEE Research Platform for Transformation-based Textual Entailment Recognition. Linguistics Issues in Language Technology (LiLT). 26 pages, to appear, 2013.
  • Amnon Lotan, Asher Stern, Ido Dagan. TruthTeller: Annotating Predicate Truth. Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), short paper, pages 752-757, Atlanta, Georgia, June 2013. [pdf]
  • Oren Melamud, Jonathan Berant, Ido Dagan, Jacob Goldberger, and Idan Szpektor. A Two Level Model for Context Sensitive Inference Rules. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL, Volume 1: Long Papers), pages 1331-1340, Sofia, Bulgaria, August 2013. Best paper runner-up. [pdf]
  • Oren Melamud, Ido Dagan, Jacob Goldberger, Idan Szpektor. Using Lexical Expansion to Learn Inference Rules from Sparse Data. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL, Volume 2: Short Papers), pages 283-288, Sofia, Bulgaria, August 2013. [pdf]
  • Omer Levy, Torsten Zesch, Ido Dagan, Iryna Gurevych. Recognizing Partial Textual Entailment. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL, Volume 2: Short Papers), pages 451-455, Sofia, Bulgaria, August 2013. [pdf]
  • Eyal Shnarch, Erel Segal Halevi, Jacob Goldberger, Ido Dagan. PLIS: a Probabilistic Lexical Inference System. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL): System Demonstrations, pages 97-102, Sofia, Bulgaria, August 2013. [pdf]
  • Chaya Liebeskind; Ido Dagan; Jonathan Schler. Semi-automatic Construction of Cross-period Thesaurus. Proceedings of the 7th Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, pages 29-35, Sofia, Bulgaria, August 2013. [pdf]
  •  

    2012

  • Jonathan Berant, Ido Dagan, and Jacob Goldberger. Learning entailment relations by global graph structure optimization. Computational Linguistics, 38(1), pp. 73-111, March 2012.
  • Amnon Lotan MA thesis. A Syntax-based Rule-base for Textual Entailment and a Semantic Truth Value Annotator. Tel Aviv University 2012. [pdf]
  • Zeichner, Naomi and Berant, Jonathan and Dagan, Ido. Crowdsourcing Inference-Rule Evaluation. Short paper in Proceedings of the ACL, 2012. [pdf]
  • Asher Stern, Roni Stern, Ido Dagan and Ariel Felner. Efficient Search for Transformation-based Inference. In Proceedings of the ACL, 2012. [pdf]
  • Asher Stern and Ido Dagan. BIUTEE: A Modular Open-Source System for Recognizing Textual Entailment. In Proceedings of the ACL Demo Session, 2012. [pdf]
  • Jonathan Berant, Ido Dagan, Meni Adler and Jacob Goldberger. Efficient Tree-based Approximation for Entailment Graph Learning. In Proceedings of the ACL, 2012. [pdf]
  • Meni Adler, Jonathan Berant and Ido Dagan, Entailment-based Text Exploration with Application to the Health-care Domain. In Proceedings of the ACL Demo Session, 2012. [pdf]
  • Weisman, Hila and Jonathan Berant and Idan Szpektor and Ido Dagan. 2012. Learning Verb Inference Rules from Linguistically-Motivated Evidence. In Proceedings of EMNLP 2012. [pdf]
  • Chaya Liebeskind, Ido Dagan and Jonathan Schler. Statistical Thesaurus Construction for a Morphologically Rich Language. In Proceedings of the First Joint Conference on Lexical and Computational Semantics (*SEM), short paper, pages 59–64, Montreal, Canada, June 7-8, 2012. [pdf]
  • Eyal Shnarch, Ido Dagan and Jacob Goldberger. 2012. A Probabilistic Lexical Model for Ranking Textual Inferences. In Proceedings of *SEM: The First Joint Conference on Lexical and Computational Semantics, 2012. [pdf]
  • Lili Kotlerman, Ido Dagan, Maya Gorodetsky and Ezra Daya. Sentence Clustering via Projection over Term Clusters. In Proceedings of the First Joint Conference on Lexical and Computational Semantics (*SEM), short paper, pages 38–43, Montreal, Canada, June 7-8, 2012. [pdf]
  •  

    2011

  • Eyal Shnarch, Jacob Goldberger, Ido Dagan. Towards a Probabilistic Model for Lexical Entailment. TextInfer, 2011. [pdf]
  • Eyal Shnarch, Jacob Goldberger, Ido Dagan. A Probabilistic Modeling Framework for Lexical Entailment. ACL, 2011. [pdf]
  • Jonathan Berant, Ido Dagan, Jacob Goldberger. Global Learning of Typed Entailment Rules. Best student paper. ACL, 2011. [pdf]
  • Shachar Mirkin, Ido Dagan, Lili Kotlerman and Idan Szpektor. Classification-based Contextual Preferences. TextInfer 2011. [pdf]
  • Asher Stern and Ido Dagan. A confidence model for syntactically-motivated entailment proofs. In Proceedings of RANLP, 2011. [pdf]
  •  

    2010

  • Jonathan Berant, Ido Dagan and Jacob Goldberger. Global Learning of Focused Entailment Graphs. Long paper in the proceedings of ACL, 2010. [pdf]
  • Lili Kotlerman, Ido Dagan, Idan Szpektor and Maayan Zhitomirsky-Geffet. Directional Distributional Similarity for Lexical Inference. Special Issue of Natural Language Engineering on Distributional Lexical Semantics. Cambridge University Press, 2010.
  • Shachar Mirkin, Jonathan Berant, Ido Dagan and Eyal Shnarch. 2010. Recognising Entailment within Discourse. COLING. [pdf]
  • Roni Ben Aharon, Idan Szpektor and Ido Dagan. 2010. Generating Entailment Rules from FrameNet. ACL. [pdf]
  • Shachar Mirkin, Ido Dagan and Sebastian Pad?. 2010. Assessing the Role of Discourse References in Entailment Inference. ACL. [pdf]
  • Wilker Aziz, Marc Dymetmany, Shachar Mirkin, Lucia Specia, Nicola Cancedda and Ido Dagan. 2010.
    Learning an Expert from Human Annotations in Statistical Machine Translation: the Case of Out-of-Vocabulary Words. EAMT. [pdf]
  • Azad Abad, Luisa Bentivogli, Ido Dagan, Danilo Giampiccolo, Shachar Mirkin, Emanuele Pianta and Asher Stern. 2010. A Resource for Investigating the Impact of Anaphora and Coreference on Inference.LREC. [pdf]

 

    2009

  • Libby Barak, Ido Dagan, Eyal Shnarch. Text Categorization from Category Name via Lexical Reference. In Proceedings of North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT), 2009. [pdf]
  • Eyal Shnarch, Libby Barak, Ido Dagan. Extracting Lexical Reference Rules from Wikipedia. In Proceedings of ACL, 2009. [pdf]
  • Roy Bar-Haim, Jonathan Berant and Ido Dagan. 2009. A Compact Forest for Scalable Inference over Entailment and Paraphrase Rules. Proceedings of EMNLP 2009. [pdf]
  • Lili Kotlerman, Ido Dagan, Idan Szpektor and Maayan Zhitomirsky-Geffet. 2009. Directional Distributional Similarity for Lexical Expansion. ACL 2009. [pdf]
  • Idan Szpektor and Ido Dagan. 2009. Augmenting WordNet-based Inference with Argument Mapping. TextInfer 2009.
  • Shachar Mirkin, Lucia Specia, Nicola Cancedda, Ido Dagan, Marc Dymetman and Idan Szpektor. 2009.
    Source-Language Entailment Modeling for Translating Unknown Terms. ACL. [pdf]
  • Roy Bar-Haim, Jonathan Berant, Ido Dagan, Iddo Greental, Shachar Mirkin, Eyal Shnarch and Idan Szpektor. Efficient Semantic Deduction and Approximate Matching over Compact Parse Forests. In Proceedings of Text Analysis Conference (TAC), 2009. [pdf]
  • Shachar Mirkin, Ido Dagan, Eyal Shnarch. Evaluating the Inferential Utility of Lexical-Semantic Resources. 2009. EACL. Athens, Greece. [pdf]

    2008

  • Roy Bar-Haim, Jonathan Berant, Ido Dagan, Iddo Greental, Shachar Mirkin, Eyal Shnarch and Idan Szpektor. 2008. Efficient Semantic Deduction and Approximate Matching over Compact Parse Forests. In Proceedings of Text Analysis Conference (TAC) 2008.
  • Ido Dagan, Roy Bar-Haim, Idan Szpektor, Iddo Greental, and Eyal Shnarch. 2008. Natural Language as the Basis for Meaning Representation and Inference. In Proceedings of CICLING 2008.
  • Ido Dagan, Roy Bar-Haim, Idan Szpektor, Iddo Greental and Eyal Shnarch. Natural Language as the Basis for Meaning Representation and Inference. In: A. Gelbukh (Ed.) Computational Linguistics and Intelligent Text Processing, Lecture Notes in Computer Science 4919: 151-170, Springer, 2008. [pdf]
  • Idan Szpektor, Ido Dagan, Roy Bar-Haim and Jacob Goldberger. 2008. Contextual Preferences. In Proceedings of ACL 2008. [pdf]
  • Idan Szpektor and Ido Dagan. 2008. Learning Entailment Rules for Unary Templates. COLING 2008 as a full oral paper. [pdf]

    2007

  • Danilo Giampiccolo; Bernardo Magnini; Ido Dagan; Bill Dolan. The Third PASCAL Recognizing Textual Entailment Challenge. Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, June 2007, Prague, Czech Republic. [pdf]
  • Roy Bar-Haim, Ido Dagan, Iddo Greental and Eyal Shnarch. Semantic Inference at the Lexical-Syntactic Level. Proceedings of the 22nd National Conference on Artificial Intelligence (AAAI), July 2007, Vancouver, Canada. [pdf]
  • Idan Szpektor, Ido Dagan, Alon Lavie, Danny Shacham and and Shuly Wintner. Cross Lingual and Semantic Retrieval for Cultural Heritage Appreciation. Proceedings of the ACL Workshop on Language Technology for Cultural Heritage Data (LaTeCH), June 2007, Prague, Czech Republic. [pdf]
  • Idan Szpektor, Eyal Shnarch and Ido Dagan. Instance-based Evaluation of Entailment Rule Acquisition. Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL), June 2007, Prague, Czech Republic. [pdf]
  • Roy Bar-Haim, Ido Dagan, Iddo Greental, Idan Szpektor and Moshe Friedman. Semantic Inference at the Lexical-Syntactic Level for Textual Entailment Rocognition. Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, June 2007, Prague, Czech Republic. [pdf]
  • Idan Szpektor and Ido Dagan. Learning Canonical Forms of Entailment Rules. Proceedings of the International Conference Recent Advantages in Natural Language Processing (RANLP), September 2007, Bulgaria. [pdf]

    2006

  • Qui?onero-Candela, J.; Dagan, I.; Magnini, B.; d’Alch?-Buc, F.
    (Eds.) Machine Learning Challenges. Lecture Notes in Computer Science, Vol.
    3944, 462 p. Springer, 2006.
  • A Gliozzo, C Strapparava, I Dagan, (2005), Unsupervised and Supervised Exploitation of Semantic Domains in Lexical Disambiguation, Computer Speech and Language, Vol. 18, Issue 3, July 2004, pp. 275-299. [pdf]
  • Ido Dagan, Oren Glickman and Bernardo Magnini. The PASCAL
    Recognising Textual Entailment Challenge. In Qui?onero-Candela, J.; Dagan, I.; Magnini, B.; d’Alch?-Buc, F. (Eds.) Machine Learning Challenges. Lecture Notes in Computer Science , Vol. 3944, pp. 177-190, Springer, 2006. [pdf]
  • Oren Glickman, Ido Dagan and Moshe Koppel. A lexical alignment model
    for probabilistic textual entailment. In Quinonero-Candela, J.; Dagan, I.; Magnini, B.; d’Alch?-Buc, F. (Eds.) Machine Learning Challenges. Lecture Notes in Computer Science , Vol. 3944, pp. 287-298, Springer, 2006. [pdf]
  • Roy Bar Haim, Ido Dagan, Bill Dolan, Lisa Ferro, Danilo Giampiccolo, Bernardo Magnini and Idan Szpektor. The Second PASCAL Recognising Textual Entailment Challenge. Proceedings of The Second PASCAL Recognising Textual Entailment Challenge, 10 April 2006, Venice, Italy. [pdf]
  • Ido Dagan, Oren Glickman, Alfio Gliozzo, Efrat Marmorshtein and Carlo Strapparava. Direct Word Sense Matching for Lexical Substitution. Proceedings of COLING-ACL 2006, 17-21 Jul 2006, Sydney, Australia. [pdf]
  • Shachar Mirkin, Ido Dagan and Maayan Geffet. Integrating Pattern-based and Distributional Similarity Methods for Lexical Entailment Acquisition. Proceedings of COLING-ACL 2006, 17-21 Jul 2006, Sydney, Australia. [pdf]
  • Lorenza Romano, Milen Kouylekov, Idan Szpektor, Ido Dagan and Alberto Lavelli. Investigating a Generic Paraphrase-based Approach for Relation Extraction. Proceedings of EACL 2006, 5-7 April 2006, Trento, Italy. [pdf]
  • Oren Glickman, Ido Dagan, Mikaela Keller, Samy Bengio and Walter Daelemans. Investigating Lexical Substitution Scoring for Subtitle Generation. Proceedings of CoNLL-X, 8-9 Jun 2006, New York City, USA. [pdf]
  • Oren Glickman, Ido Dagan and Eyal Shnarch. Lexical Reference: a Semantic Matching Subtask. Proceedings of EMNLP 2006, 22-23 Jul 2006, Sydney, Australia. [pdf]

    2005

  • Roy Bar-Haim, Idan Szpektor and Oren Glickman. 2005. Definition and Analysis of Intermediate Entailment Levels. ACL 2005 Workshop on Empirical Modeling of Semantic Equivalence and Entailment. [pdf]
  • Zhitomirsky-Geffet, Maayan and Ido Dagan. Bootstrapping Distributional Feature Vector Quality, Computational Linguistics. [pdf]
  • Maayan Geffet and Ido Dagan. The Distributional Inclusion Hypotheses and Lexical Entailment. Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), 2005. [pdf]
  • Oren Glickman and Ido Dagan. A Probabilistic Setting and Lexical Cooccurrence Model for Textual Entailment. Proceedings of ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment, 2005. [pdf]
  • Oren Glickman, Ido Dagan and Moshe Koppel. A Probabilistic Classification Approach for Lexical Textual Entailment. Proceedings of the 20th National Conference on Artificial Intelligence (AAAI), 2005. [pdf]
  • Oren Glickman, Ido Dagan and Moshe Koppel. A Probabilistic Lexical Approach to Textual Entailment. Proceedings of the International Joint Conferences on Artificial Intelligence (IJCAI), 2005. [pdf]
  • Alfio Gliozzo, Carlo Strapparava, and Ido Dagan. Investigating Unsupervised Learning for Text Categorization Bootstrapping. Proceedings of the joint Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), 2005. [pdf]
  • Zvika Marx, Ido Dagan and Eli Shamir. A Generalized Framework for Revealing Analogous Themes across Related Topics. Proceedings of the joint Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), 2005. [pdf]
  • M. Koppel, N. Akiva and I. Dagan, (2005), Feature Instability as a Criterion for Selecting Potential Style Markers, Journal of the American Society for Information Science and Technology (JASIST), Volume 57, Number 11, September 2006, pp. 1519-1525. [ps]

    2004

  • Glickman Oren, Ido Dagan. Acquiring lexical paraphrases from a single corpus, in N. Nicolov, K. Bontcheva, G. Angelova and R. Mitkov (editors). Recent Advances in Natural Language Processing III, John Benjamins Publ. Co., Amsterdam, 2004, pp. 81-90. [pdf]
  • Marx Z., Dagan I. and Shamir E. (2004). Identifying structure across pre-partitioned data. In Thrun S., Saul L., and Scho”lkopf B. (eds.), Advances in Neural Information Processing Systems 16 (NIPS 2003), December 8-13, Vancouver, Canada. [pdf]
  • Ido Dagan and Oren Glickman. 2004. Probabilistic textual entailment: Generic applied modeling of language variability. In PASCAL Workshop on Learning Methods for Text Understanding and Mining, Grenoble. [pdf]
  • Idan Szpektor, Hristo Tanev, Ido Dagan and Bonaventura Coppola. Scaling Web-based Acquisition of Entailment Relations. Proceedings of Empirical Methods in Natural Language Processing (EMNLP), 2004. [pdf]
  • Maayan Geffet and Ido Dagan. Feature Vector Quality and Distributional Similarity. Proceedings of The 20th International Conference on Computational Linguistics (COLING), 2004. [pdf]

    2003

  • Koppel, Moshe, Navot Akiva and Ido Dagan. A Corpus-Independent Feature Set for Style Based Text Categorization, in Proceedings of IJCAI’03 Workshop on Computational Approaches to Style Analysis and Synthesis, Acapulco, Mexico, 2003. [pdf]
  • Glickman, Oren and Ido Dagan. Identifying Lexical Paraphrases from a Single Corpus: A Case Study for Verbs, in Proceedings of Recent Advantages in Natural Language Processing (RANLP ’03), 2003. [pdf]

    2002

  • Marx, Zvika, Ido Dagan, Joachim M. Buhmann and Eli Shamir. Coupled clustering: a method for detecting structural correspondence, Journal of Machine Learning Research, 2002, Vol. 3(Dec), pp. 747-780. [pdf]
  • Dagan, Ido and Yuval Krymolowski. Compositional memory-based partial parsing, in R. Bod, R. Scha and K. Sima’an (Eds.), Data-Oriented Parsing, CSLI Publications, 2002, forthcoming (20 pages). [pdf]
  • Marx, Zvika, Ido Dagan and Eli Shamir. Cross-component clustering for template induction, in Proceedings of the ICML Workshop on Text Learning (TextML), 2002, pp. 66-75. [pdf]
  • Dagan, Ido, Zvika Marx and Eli Shamir. Cross-dataset clustering: revealing corresponding Themes Across Multiple Corpora, in Proceedings of the Sixth Conference on Natural Language Learning (CoNLL), 2002, pp. 15-21. [doc]

    2001

  • Marx, Zvika, Ido Dagan, Joachim M. Buhmann. Coupled Clustering: a method for detecting structural correspondence, in Proceedings of the Eighteenth International Conference on Machine Learning (ICML), 2001, pp.353–360. [pdf]
  • Marx, Zvika and Ido Dagan. Conceptual mapping through keyword coupled clustering. Mind and Society: a Special Issue on Commonsense and Scientific Reasoning, 4(2), pp. 59-85, 2001. [ps]

    2000

  • Dagan, Ido. Contextual Word Similarity, in Rob Dale, Hermann Moisl and Harold Somers (Eds.), Handbook of Natural Language Processing, Marcel Dekker Inc, 2000, Chapter 19, pp. 459-476. [doc]
  • Choueka, Yaacov, Ehud S. Conley and Ido Dagan. A comprehensive bilingual word alignment system: application to disparate languages – Hebrew and English, in J. Veronis (Ed.), Parallel Text Processing, Kluwer Academic Publishers, 2000, pp. 69–96. [doc]
  • Krymolowski, Yuval and Ido Dagan. Compositional Memory-Based Partial Parsing, in Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2000, pp. 45-52.

    1999

  • Dagan, Ido, Lillian Lee and Fernando Pereira. Similarity-based models of cooccurrence probabilities, Machine Learning, 1999, Vol. 34(1-3) special issue on Natural Language Learning, pp. 43-69. [pdf]
  • Argamon, Shlomo, Ido Dagan and Yuval Krymolowski. A memory based approach to learning shallow natural language patterns, Journal of Experimental and Theoretical AI (JETAI), 1999, Vol. 11, pp. 369-390. [pdf]
  • Argamon-Engleson, Shlomo and Ido Dagan. Committee-Based Sample Selection for Probabilistic Classifiers, Journal of Artificial Intelligence Research (JAIR), 1999, Vol. 11, pp. 335-360. [ps]
  • Dagan, Ido, Kenneth Church and William Gale. Robust bilingual word alignment for machine aided translation, in S. Armstrong, K. Church, P. Isabelle, S. Manzi, E. Tzoukermann and D. Yarowsky (Eds.), Natural Language Processing Using Very Large Corpora, Kluwer Academic Publishers, 1999, pp. 209-224.
  • Marx, Zvi, Ido Dagan and Eli Shamir. Detecting Sub-Topic Correspondence through Bipartite Term Clustering, in Proceedings of the ACL-1999 Workshop on Unsupervised Learning in Natural Language Processing, 1999, pp. 45-51. [ps]

    1998

  • Argamon, Shlomo, Ido Dagan and Yuval Krymolowsky. Memory-based learning of shallow natural language patterns, in Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 1998. [ps]
  • Feldman, Ronen, Ido Dagan and Haym Hirsh. Mining text using keyword distributions, Journal of Intelligent Information Systems, 1998, Vol. 10(3), pp. 281-300. [pdf]

    1997

  • Dagan, Ido, Lillian Lee and Fernando Pereira. Similarity-based methods for word sense disambiguation, in Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 1997, pp 56-63. [ps]
  • Dagan, Ido, Yael Karov and Dan Roth. Mistake-driven learning in text categorization, in Proceedings of Second Conference on Empirical Methods in Natural Language Processing (EMNLP-2), 1997.
  • Yamazaki, Takefumi and Ido Dagan. Mistake-driven learning with thesaurus for text categorization, in Proceedings of the Natural Language Pacific Rim Symposium (NLPRS-97), 1997.
  • Dagan, Ido and Kenneth Church. Termight: Coordinating man and machine in bilingual terminology acquisition, Machine Translation, 1997, Vol. 12(1-2), pp. 89-107. [ps]

 

    1996

  • Engelson, Sean and Ido Dagan. Sample selection in natural language learning, in S. Wermter, E. Riloff and G. Scheler (Eds.), Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing, Springer, 1996, pp. 230-245.
  • Engelson, Sean and Ido Dagan. Minimizing Manual Annotation Cost in Supervised Training from Corpora, in Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 1996, pp. 319-326. [pdf]
  • Dagan, Ido, Ronen Feldman and Haym Hirsh. Keyword-Based Browsing and Analysis of Large Document Sets, in Proceedings of The Fifth Annual Symposium on Document Analysis and Information Retrieval (SDAIR), 1996, pp. 191-208. [pdf]
  • Feldman, Ronen, Ido Dagan and Willi Kloesgen. Efficient algorithms for mining and manipulating associations in texts, in Proceedings of the Thirteenth European Meeting on Cybernetics and Systems Research (EMCSR), 1996.

    1995

  • Dagan, Ido, John Justeson, Shalom Lappin, Herbert Leass and Amnon Ribak. Syntax and lexical statistics in anaphora resolution, Applied Artificial Intelligence, 1995, Vol. 9, pp. 633-644.
  • Dagan, Ido, Shaul Marcus and Shaul Markovitch. Contextual word similarity and estimation from sparse data, Computer, Speech and Language, 1995, Vol. 9, pp. 123-152.
  • Dagan, Ido and Sean Engelson. Committee-based sampling for training probabilistic classifiers, in Proceedings of the Twelfth International Conference on Machine Learning (ICML), 1995.
  • Dagan, Ido and Sean Engelson. Selective sampling in natural language learning, in Proceedings of the IJCAI Workshop on New Approaches to Learning for Natural Language Processing, 1995, pp. 41-48.
  • Feldman, Ronen and Ido Dagan. KDT – Knowledge Discovery in Texts, in Proceedings of the First International Conference on Knowledge Discovery (KDD), 1995, pp. 112-117. [ps]
  • Feldman, Ronen and Ido Dagan. Knowledge Discovery in Textual Databases, in Proceedings of the ECML Workshop in Knowledge Discovery, 1995.