Advanced Search
DSpace@MIT

Browsing MIT Open Access Articles by Author "Barzilay, Regina"

Research and Teaching Output of the MIT Community

Browsing MIT Open Access Articles by Author "Barzilay, Regina"

Sort by: Order: Results:

  • Snyder, Benjamin; Naseem, Tahira; Eisenstein, Jacob; Barzilay, Regina (Association for Computational Linguistics, 2009-06)
    We investigate the problem of unsupervised part-of-speech tagging when raw parallel data is available in a large number of languages. Patterns of ambiguity vary greatly across languages and therefore even unannotated ...
  • Sauper, Christina; Barzilay, Regina (Association for the Advancement of Artificial Intelligence, 2013-01)
    We present a model for aggregation of product review snippets by joint aspect identification and sentiment analysis. Our model simultaneously identifies an underlying set of ratable aspects presented in the reviews of a ...
  • Sauper, Christina Joan; Barzilay, Regina (Association for Computational Linguistics, 2009-08)
    In this paper, we investigate an approach for creating a comprehensive textual overview of a subject composed of information drawn from the Internet. We use the high-level structure of human-authored texts to automatically ...
  • Snyder, Benjamin; Barzilay, Regina (Omnipress, 2010-06)
    For centuries, scholars have explored the deep links among human languages. In this paper, we present a class of probabilistic models that use these links as a form of naturally occurring supervision. These models ...
  • Chen, Harr; Branavan, Satchuthanan R.; Barzilay, Regina; Karger, David R. (AI Access Foundation, 2009-10)
    We present a novel Bayesian topic model for learning discourse-level document structure. Our model leverages insights from discourse theory to constrain latent topic assignments in a way that reflects the underlying ...
  • Sauper, Christina Joan; Haghighi, Aria; Barzilay, Regina (Association for Computational Linguistics, 2011-06)
    We present a probabilistic topic model for jointly identifying properties and attributes of social media review snippets. Our model simultaneously learns a set of properties of a product and captures aggregate user sentiments ...
  • Benson, Edward Oscar; Haghighi, Aria; Barzilay, Regina (Association for Computational Linguistics, 2011-06)
    We present a novel method for record extraction from social streams such as Twitter. Unlike typical extraction setups, these environments are characterized by short, one sentence messages with heavily colloquial speech. ...
  • Lei, Tao; Long, Fan; Barzilay, Regina; Rinard, Martin C. (Association for Computational Linguistics (ACL), 2013-08)
    We present a method for automatically generating input parsers from English specifications of input file formats. We use a Bayesian generative model to capture relevant natural language phenomena and translate the English ...
  • Chen, Harr; Branavan, Satchuthanan R.; Barzilay, Regina; Karger, David R. (Association for Computational Linguistics, 2009-06)
    We present a novel Bayesian topic model for learning discourse-level document structure. Our model leverages insights from discourse theory to constrain latent topic assignments in a way that reflects the underlying ...
  • Polifroni, Joseph; Seneff, Stephanie; Branavan, Satchuthanan R.; Wang, Chao; Barzilay, Regina (Institute of Electrical and Electronics Engineers (IEEE), 2010-12)
    In this paper, we introduce a new envisioned application for speech which allows users to enter restaurant reviews orally via their mobile device, and, at a later time, update a shared and growing database of consumer-provided ...
  • Sauper, Christina Joan; Haghighi, Aria; Barzilay, Regina (Association for Computational Linguistics, 2010-10)
    Information about the content structure of a document is largely ignored by current text analysis applications such as information extraction and sentiment analysis. This stands in contrast to the linguistic intuition ...
  • Chen, Harr; Benson, Edward Oscar; Naseem, Tahira; Barzilay, Regina (Association for Computing Machinery, 2011-06)
    We present a novel approach to discovering relations and their instantiations from a collection of documents in a single domain. Our approach learns relation types by exploiting meta-constraints that characterize the general ...
  • Branavan, Satchuthanan R.; Chen, Harr; Eisenstein, Jacob; Barzilay, Regina (AI Access Foundation, 2009-04)
    This paper presents a new method for inferring the semantic properties of documents by leveraging free-text keyphrase annotations. Such annotations are becoming increasingly abundant due to the recent dramatic growth in ...
  • Branavan, S. R. K.; Kushman, Nathaniel A.; Lei, Tao; Barzilay, Regina (The Association for Computational Linguistics, 2012-07)
    Comprehending action preconditions and effects is an essential step in modeling the dynamics of the world. In this paper, we express the semantics of precondition relations extracted from text in terms of planning operations. ...
  • Branavan, Satchuthanan R.; Silver, David; Barzilay, Regina (Association for Computing Machinery, 2011-06)
    This paper presents a novel approach for leveraging automatically extracted textual knowledge to improve the performance of control applications such as games. Our ultimate goal is to enrich a stochastic player with ...
  • Yoong Keok, Lee; Haghighi, Aria; Barzilay, Regina (Association for Computing Machinery, 2011-06)
    The connection between part-of-speech (POS) categories and morphological properties is well-documented in linguistics but underutilized in text processing systems. This paper proposes a novel model for morphological ...
  • Naseem, Tahira; Snyder, Benjamin; Eisenstein, Jacob; Barzilay, Regina (AI Access Foundation, 2009-11)
    We demonstrate the effectiveness of multilingual learning for unsupervised part-of-speech tagging. The central assumption of our work is that by combining cues from multiple languages, the structure of each becomes more ...
  • Branavan, Satchuthanan R.; Silver, David; Barzilay, Regina (AAAI Press/International Joint Conferences on Artificial Intelligence, 2011-07)
    This paper presents a new Monte-Carlo search algorithm for very large sequential decision-making problems. Our approach builds on the recent success of Monte-Carlo tree search algorithms, which estimate the value of states ...
  • Barzilay, Regina (Springer-Verlag, 2010-08)
    Since the early days of generation research, it has been acknowledged that modeling the global structure of a document is crucial for producing coherent, readable output. However, traditional knowledge-intensive approaches ...
  • Branavan, Satchuthanan R.; Zettlemoyer, Luke S.; Barzilay, Regina (Association for Computational Linguistics, 2010-07)
    In this paper, we address the task of mapping high-level instructions to commands in an external environment. Processing these instructions is challenging—they posit goals to be achieved without specifying the steps required ...
Open Access