Publications
1341.
Hori, Takaaki; Watanabe, Shinji; Zhang, Yu; Chan, William
Advances in Joint CTC-Attention based End-to-End Speech Recognition with a Deep CNN Encoder and RNN-LM Inproceedings
In: Proc. Interspeech 2017, pp. 949–953 year=2017, 0000.
@inproceedings{hori2017advances,
title = {Advances in Joint CTC-Attention based End-to-End Speech Recognition with a Deep CNN Encoder and RNN-LM},
author = {Takaaki Hori and Shinji Watanabe and Yu Zhang and William Chan},
booktitle = {Proc. Interspeech 2017},
pages = {949--953 year=2017},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
1342.
Wang, Dingquan; Eisner, Jason
Surface Statistics of an Unknown Language Indicate How to Parse It Journal Article
In: Transactions of the Association for Computational Linguistics (TACL), 0000, ISSN: 2307-387X.
@article{wang-eisner-2018-tacl,
title = {Surface Statistics of an Unknown Language Indicate How
to Parse It},
author = {Dingquan Wang and Jason Eisner},
url = {http://cs.jhu.edu/~jason/papers/#wang-eisner-2018-tacl},
issn = {2307-387X},
journal = {Transactions of the Association for Computational
Linguistics (TACL)},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
1343.
Paul, Michael J; Chisolm, Margaret S; Johnson, Matthew W; Vandrey, Ryan G; Dredze, Mark
Assessing the validity of online drug forums as a source for estimating demographic and temporal trends in drug use Journal Article
In: Journal of Addiction Medicine, 10 (5), pp. 324–330, 0000.
@article{Michael-J.-Paul:2016fpc,
title = {Assessing the validity of online drug forums as a source for estimating demographic and temporal trends in drug use},
author = {Michael J Paul and Margaret S Chisolm and Matthew W Johnson and Ryan G Vandrey and Mark Dredze},
journal = {Journal of Addiction Medicine},
volume = {10},
number = {5},
pages = {324--330},
abstract = {Objectives: Addiction researchers have begun monitoring online forums to uncover self-reported details about use and effects of emerging drugs. The use of such online data sources has not been validated against data from large epidemiological surveys. This study aimed to characterize and compare the demographic and temporal trends associated with drug use as reported in online forums and in a large epidemiological survey. Methods: Data were collected from the website, drugs-forum.com, from January 2007 through August 2012 (143,416 messages posted by 8,087 members) and from the United States National Survey on Drug Use and Health (NSDUH) from 2007-2012. Measures of forum participation levels were compared with and validated against two measures from the NSDUH survey data: percentage of people using the drug in last 30 days and percentage using the drug more than 100 times in the past year. Results: For established drugs (e.g., cannabis), significant correlations were found across demographic groups between drugs-forum.com and the NSDUH survey data, while weaker, non-significant correlations were found with temporal trends. Emerging drugs (e.g., Salvia divinorum) were strongly associated with male users in the forum, in agreement with survey-derived data, and had temporal patterns that increased in synchrony with poison control reports. Conclusions: These results offer the first assessment of online drug forums as a valid source for estimating demographic and temporal trends in drug use. The analyses suggest that online forums are a reliable source for estimation of demographic associations and early identification of emerging drugs, but a less reliable source for measurement of long-term temporal trends.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Objectives: Addiction researchers have begun monitoring online forums to uncover self-reported details about use and effects of emerging drugs. The use of such online data sources has not been validated against data from large epidemiological surveys. This study aimed to characterize and compare the demographic and temporal trends associated with drug use as reported in online forums and in a large epidemiological survey. Methods: Data were collected from the website, drugs-forum.com, from January 2007 through August 2012 (143,416 messages posted by 8,087 members) and from the United States National Survey on Drug Use and Health (NSDUH) from 2007-2012. Measures of forum participation levels were compared with and validated against two measures from the NSDUH survey data: percentage of people using the drug in last 30 days and percentage using the drug more than 100 times in the past year. Results: For established drugs (e.g., cannabis), significant correlations were found across demographic groups between drugs-forum.com and the NSDUH survey data, while weaker, non-significant correlations were found with temporal trends. Emerging drugs (e.g., Salvia divinorum) were strongly associated with male users in the forum, in agreement with survey-derived data, and had temporal patterns that increased in synchrony with poison control reports. Conclusions: These results offer the first assessment of online drug forums as a valid source for estimating demographic and temporal trends in drug use. The analyses suggest that online forums are a reliable source for estimation of demographic associations and early identification of emerging drugs, but a less reliable source for measurement of long-term temporal trends.
1344.
Dredze, Mark; Schilit, Bill
Facet suggestion for search query augmentation Patent
0000, (US Patent 8,433,705).
@patent{dredze2013facetd,
title = {Facet suggestion for search query augmentation},
author = {Mark Dredze and Bill Schilit},
publisher = {Google Patents},
note = {US Patent 8,433,705},
keywords = {},
pubstate = {published},
tppubtype = {patent}
}
1345.
Knowles, Rebecca; Koehn, Philipp
Context and Copying in Neural Machine Translation Inproceedings
In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 3034–3041, Association for Computational Linguistics, Brussels, Belgium, 0000.
@inproceedings{knowles-koehn:2018:EMNLP,
title = {Context and Copying in Neural Machine Translation},
author = {Rebecca Knowles and Philipp Koehn},
url = {http://www.aclweb.org/anthology/D18-1339},
booktitle = {Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing},
pages = {3034--3041},
publisher = {Association for Computational Linguistics},
address = {Brussels, Belgium},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
