Oren Melamud
Natural Language Processing Lab
Department of Computer Science, Bar Ilan University

[Contact | Short Bio | Publications]


Ido Dagan

Contact Information

Natural Language Processing Lab
Department of Computer Science
Bar Ilan University,
Ramat Gan, 52900, Israel

 

Email: melamuo located-at macs.biu.ac.il

As of August 2016, I am a Research Scientist at IBM Research, New York

 



I am a PhD student in the Department of Computer Science, Bar-Ilan University, under the supervision of Prof. Ido Dagan and Prof. Jacob Goldberger.
I am developing computational models that capture semantic properties of words or phrases and identify semantic inference relations between them.
In particular my research is focused on how different concrete contexts affect semantic meanings and inferences (e.g. as in "Joe _runs_ a business" versus "Joe _runs_ marathons").

I also enjoy collaborating with other researchers to develop educational NLP applications that utilize components of my semantic models.



Short Bio

Prior to starting my PhD in March 2012, I have been working for several years in the hi-tech industry as a software engineer and then system architect.
During this period I also earned an M.Sc. (Magna Cum Laude) in Computer Science from Bar-Ilan University, Israel.
Prior to that I received a B.Sc. in Math and Physics from the Hebrew University.



Publications

  • PhD Dissertation: Improving Lexical Inference using Context-sensitive Distributional Models with Rich Context Representations. BIU, 2016. PDF
  • Oren Melamud, Jacob Goldberger, Ido Dagan. context2vec: Learning Generic Context Embedding with Bidirectional LSTM. CoNLL, 2016. PDF
  • Michael Wojatzki, Oren Melamud, Torsten Zesch. Bundled Gap Filling: A New Paradigm for Unambiguous Cloze Exercises. Workshop on Innovative Use of NLP for Building Educational Applications (BEA), 2016. PDF
  • Oren Melamud, David McClosky, Siddharth Patwardhan, Mohit Bansal. The Role of Context Types and Dimensionality in Learning Word Embeddings. NAACL, 2016. PDF
  • Vasily Konovalov, Ron Artstein, Oren Melamud, Ido Dagan. The Negochat Corpus of Human-agent Negotiation Dialogues. LREC, 2016. PDF
  • 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
  • Oren Melamud, Ido Dagan, Jacob Goldberger, Idan Szpektor and Deniz Yuret. Probabilistic Modeling of Joint-context in Distributional Similarity. CoNLL, 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), 2014. PDF
  • Oren Melamud, Jonathan Berant, Ido Dagan, Jacob Goldberger and Idan Szpektor. A Two Level Model for Context Sensitive Inference Rules. ACL, 2013. Best paper runner-up. PDF
  • Oren Melamud, Ido Dagan, Jacob Goldberger and Idan Szpektor. Using Lexical Expansion to Learn Inference Rules from Sparse Data. ACL, short paper, 2013. PDF
  • Yonatan Aumann, Moshe Lewenstein, Oren Melamud, Ron Pinter, Zohar Yakhini. Dotted Interval Graphs. ACM Transactions on Algorithms (TALG) 8.2 (2012): 9


Talks

  • context2vec: Learning Generic Context Embedding with Bidirectional LSTM. CoNLL. August 2016. PDF
  • The Role of Context Types and Dimensionality in Learning Word Embeddings. NAACL. June 2016. PDF
  • Probabilistic Modeling of Joint-context in Distributional Similarity. CoNLL. June 2014. PDFPDF
  • A Two Level Model for Context Sensitive Inference Rules. ACL. August 2013. PDF

 

Software and Datasets