R
Raymond J. Mooney
Researcher at University of Texas at Austin
Publications - 320
Citations - 35237
Raymond J. Mooney is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Natural language & Parsing. The author has an hindex of 86, co-authored 308 publications receiving 32776 citations. Previous affiliations of Raymond J. Mooney include University of Illinois at Urbana–Champaign.
Papers
More filters
Proceedings ArticleDOI
Content-based book recommending using learning for text categorization
Raymond J. Mooney,Loriene Roy +1 more
TL;DR: This work describes a content-based book recommending system that utilizes information extraction and a machine-learning algorithm for text categorization and shows initial experimental results demonstrate that this approach can produce accurate recommendations.
Proceedings ArticleDOI
Sequence to Sequence -- Video to Text
Subhashini Venugopalan,Marcus Rohrbach,Jeff Donahue,Raymond J. Mooney,Trevor Darrell,Kate Saenko +5 more
TL;DR: In this article, an end-to-end sequence to sequence model was proposed to generate captions for videos, which can learn the temporal structure of the sequence of frames as well as the sequence model of the generated sentences, i.e. a language model.
Posted Content
Content-Based Book Recommending Using Learning for Text Categorization
Raymond J. Mooney,Loriene Roy +1 more
TL;DR: The authors proposed a content-based book recommendation system that utilizes information extraction and a machine-learning algorithm for text categorization, which has the advantage of being able to recommend previously unrated items to users with unique interests and to provide explanations for its recommendations.
Proceedings ArticleDOI
Adaptive duplicate detection using learnable string similarity measures
TL;DR: This paper proposes to employ learnable text distance functions for each database field, and shows that such measures are capable of adapting to the specific notion of similarity that is appropriate for the field's domain.
Proceedings ArticleDOI
A Shortest Path Dependency Kernel for Relation Extraction
Razvan Bunescu,Raymond J. Mooney +1 more
TL;DR: Experiments on extracting top-level relations from the ACE (Automated Content Extraction) newspaper corpus show that the new shortest path dependency kernel outperforms a recent approach based on dependency tree kernels.