Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Vishrawas Gopalakrishnan"'
Autor:
Vishrawas Gopalakrishnan, Sayali Pethe, Sarah Kefayati, Raman Srinivasan, Paul Hake, Ajay Deshpande, Xuan Liu, Etter Hoang, Marbelly Davila, Simone Bianco, James H. Kaufman
Publikováno v:
Epidemics, Vol 37, Iss , Pp 100510- (2021)
Importance:: Assumption of a well-mixed population during modeling is often erroneously made without due analysis of its validity. Ignoring the importance of the geo-spatial granularity at which the data is collected could have significant implicatio
Externí odkaz:
https://doaj.org/article/dabc773d12c84cf889bcd0a0257096ca
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 13:1-21
Recent advances in unsupervised language processing methods have created an opportunity to exploit massive text corpora for developing high-quality vector space representation (also known as word embeddings) of words. Towards this direction, practiti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::074efd33b4ebf0cf54d9d2d07adae2af
https://doi.org/10.1145/3310254
https://doi.org/10.1145/3310254
Autor:
Fred Roberts, Prithwish Chakraborty, Sayali Pethe, Xuan Liu, Raman Srinivasan, Ajay A. Deshpande, Hu Huang, Vishrawas Gopalakrishnan, Gretchen Purcell Jackson, Piyush Madan, Sarah Kefayati, Jianying Hu
Epidemiological models have provided valuable information for the outlook of COVID-19 pandemic and relative impact of different mitigation scenarios. However, more accurate forecasts are often needed at near term for planning and staffing. We present
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24a3ee703c9d60c2e1c0fe24a730b8da
https://doi.org/10.1101/2020.09.11.20180521
https://doi.org/10.1101/2020.09.11.20180521
Autor:
Etter Hoang, Simone Bianco, Marbelly Davila, Ajay A. Deshpande, Vishrawas Gopalakrishnan, Xuan Liu, Sarah Kefayati, Paul Hake, Sayali Pethe, Raman Srinivasan, James H. Kaufman
Publikováno v:
Epidemics, Vol 37, Iss, Pp 100510-(2021)
Epidemics
Epidemics
Importance: Assumption of a well-mixed population during modeling is often erroneously made without due analysis of its validity. Ignoring the importance of the geo-spatial granularity at which the data is collected could have significant implication
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5ff8b2411bb66103152c48789db637d
https://doi.org/10.1016/j.epidem.2021.100510
https://doi.org/10.1016/j.epidem.2021.100510
Publikováno v:
Bioinformatics. 34:2103-2115
Motivation The overwhelming amount of research articles in the domain of bio-medicine might cause important connections to remain unnoticed. Literature Based Discovery is a sub-field within biomedical text mining that peruses these articles to formul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::acecd090b1f071acf98201e456bfe645
https://doi.org/10.1093/bioinformatics/btx837
https://doi.org/10.1093/bioinformatics/btx837
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 29:38-56
Learning semantics based on context information has been researched in many research areas for decades. Context information can not only be directly used as the input data, but also sometimes used as auxiliary knowledge to improve existing models. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c2af6c965b7cade47667dea021b2ba1
https://doi.org/10.1109/tkde.2016.2614508
https://doi.org/10.1109/tkde.2016.2614508
Publikováno v:
KDD
Given two topics of interest (A, C) that are otherwise disconnected - for instance two concepts: a disease ("Migraine") and a therapeutic substance ("Magnesium") - this paper attempts to find the conceptual bridges (e.g., serotonin (B)) that connects
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a20d6c883b6606d15a4536c33d583ad
https://doi.org/10.1145/3219819.3220071
https://doi.org/10.1145/3219819.3220071
Publikováno v:
ICDM
Literature based discovery (LBD) is a task that aims to uncover hidden associations between non-interacting scientific concepts by rationally connecting independent nuggets of information. Broadly, prior approaches to LBD include use of: a) distribut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::add6136b8b71599b94a615ba1dc726ac
https://doi.org/10.1109/icdm.2017.63
https://doi.org/10.1109/icdm.2017.63
Publikováno v:
Proceedings of the VLDB Endowment. 7:1167-1178
Title matching refers roughly to the following problem. We are given two strings of text obtained from different data sources. The texts refer to some underlying physical entities and the problem is to report whether the two strings refer to the same
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e6a6fdc5fa4dd406c71faff0fc7fcf95
https://doi.org/10.14778/2732977.2732990
https://doi.org/10.14778/2732977.2732990
Publikováno v:
ICDM
Discovering topics in short texts, such as news titles and tweets, has become an important task for many content analysis applications. However, due to the lack of rich context information in short texts, the performance of conventional topic models
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ced7b8294a6eef5e87b7fc24137ba2b
https://doi.org/10.1109/icdm.2016.0176
https://doi.org/10.1109/icdm.2016.0176