Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Patrick Pantel"'
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 32
Emails in the workplace are often intentional calls to action for its recipients. We propose to annotate these emails for what action its recipient will take. We argue that our approach of action-based annotation is more scalable and theory-agnostic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4728c7ac8eff463d7d73b575f3c9e3d
https://doi.org/10.1609/aaai.v32i1.11931
https://doi.org/10.1609/aaai.v32i1.11931
Autor:
Madian Khabsa, Michael Gamon, Yu Su, Mark J. Encarnación, Ahmed Hassan Awadallah, Patrick Pantel
Publikováno v:
CIKM
As the Web evolves towards a service-oriented architecture, application program interfaces (APIs) are becoming an increasingly important way to provide access to data, services, and devices. We study the problem of natural language interface to APIs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25efcb1e708d447754050a2534e2781e
https://doi.org/10.1145/3132847.3133009
https://doi.org/10.1145/3132847.3133009
Publikováno v:
HLT-NAACL
We introduce a latent activity model for workplace emails, positing that communication at work is purposeful and organized by activities. We pose the problem as probabilistic inference in graphical models that jointly capture the interplay between la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f278f042851e87eb31e0aaeca1311451
https://doi.org/10.18653/v1/n16-1171
https://doi.org/10.18653/v1/n16-1171
Autor:
Pallavi Choudhury, Kristina Toutanova, Danqi Chen, Michael Gamon, Patrick Pantel, Hoifung Poon
Publikováno v:
EMNLP
Models that learn to represent textual and knowledge base relations in the same continuous latent space are able to perform joint inferences among the two kinds of relations and obtain high accuracy on knowledge base completion (Riedel et al., 2013).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a514069816411cd37a43dcf13ee2c053
https://doi.org/10.18653/v1/d15-1174
https://doi.org/10.18653/v1/d15-1174
Publikováno v:
Computer. 38:43-50
A general-purpose solution to the problem of matching entities within or across heterogeneous data sources can't depend on the presence or reliability of auxiliary data such as structural information or metadata. Instead, it must leverage the availab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be11fa1dedd0cb479b8a09554d27ba1b
https://doi.org/10.1109/mc.2005.406
https://doi.org/10.1109/mc.2005.406
Publikováno v:
CIKM
We present methods to automatically identify and recommend sub-tasks to help people explore and accomplish complex search tasks. Although Web searchers often exhibit directed search behaviors such as navigating to a particular Website or locating a p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3e26748b02986023f54853811d50476
https://doi.org/10.1145/2661829.2661912
https://doi.org/10.1145/2661829.2661912
Autor:
Bo Zhao, Patrick Pantel, Pradeep Chilakamarri, Dhyanesh Narayanan, David Hamilton, Evangelos E. Papalexakis, Bernhard Kohlmeier, Yuanhua Lv, Ashok K. Chandra, Michael Gamon, Ariel Fuxman
Publikováno v:
23rd International World Wide Web Conference, WWW '14, Seoul, Republic of Korea, April 7-11, 2014, Companion Volume
In today's productivity environment, users are constantly researching topics while consuming or authoring content in applications such as e-readers, word processors, presentation programs, or social networks. However, none of these applications suffi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f54a94a82ae4deadfb1e0854c04f39be
https://doi.org/10.1145/2567948.2577280
https://doi.org/10.1145/2567948.2577280
Publikováno v:
EMNLP
An "Interestingness Modeler" uses deep neural networks to learn deep semantic models (DSM) of "interestingness." The DSM, consisting of two branches of deep neural networks or their convolutional versions, identifies and predicts target documents tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75405b330a0ba079bccd35bb25e1439c
https://doi.org/10.3115/v1/d14-1002
https://doi.org/10.3115/v1/d14-1002
Publikováno v:
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
Natural touch interfaces, common now in devices such as tablets and smartphones, make it cumbersome for users to select text. There is a need for a new text selection paradigm that goes beyond the high acuity selection-by-mouse that we have relied on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c2702f14c4bb3a2c9a32eea9e7e2ae0
https://doi.org/10.3115/v1/p14-1143
https://doi.org/10.3115/v1/p14-1143
Autor:
Dekang Lin, Patrick Pantel
Publikováno v:
Natural Language Engineering. 7:343-360
One of the main challenges in question-answering is the potential mismatch between the expressions in questions and the expressions in texts. While humans appear to use inference rules such as ‘X writes Y’ implies ‘X is the author of Y’ in an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc7817a9a2516d5a32c7d46fff7eb754
https://doi.org/10.1017/s1351324901002765
https://doi.org/10.1017/s1351324901002765