Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Girish Keshav Palshikar"'
Publikováno v:
Data Science and Engineering, Vol 3, Iss 3, Pp 232-247 (2018)
Abstract Continuous training is crucial for creating and maintaining the right skill-profile for the industrial organization’s workforce. There is a tremendous variety in the available trainings within an organization: technical, project management
Externí odkaz:
https://doaj.org/article/6f2e62ee57534d37b9e27f6c83e622f0
Publikováno v:
BMC Bioinformatics, Vol 19, Iss S8, Pp 1-7 (2018)
Abstract Background Social media is a useful platform to share health-related information due to its vast reach. This makes it a good candidate for public-health monitoring tasks, specifically for pharmacovigilance. We study the problem of extraction
Externí odkaz:
https://doaj.org/article/4b8413c0f1d1466487d5c01188e4fe7b
Publikováno v:
Studies in Computational Intelligence ISBN: 9789811953903
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f47e80f2421fc967327fdb0df5e2acf3
https://doi.org/10.1007/978-981-19-5391-0
https://doi.org/10.1007/978-981-19-5391-0
Publikováno v:
Investigations in Entity Relationship Extraction ISBN: 9789811953903
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a480b050d52783690b9eb97c45d5d8ba
https://doi.org/10.1007/978-981-19-5391-0_2
https://doi.org/10.1007/978-981-19-5391-0_2
Publikováno v:
Investigations in Entity Relationship Extraction ISBN: 9789811953903
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9c5b565c5e86d25359dc8fcddd6770e
https://doi.org/10.1007/978-981-19-5391-0_6
https://doi.org/10.1007/978-981-19-5391-0_6
Publikováno v:
Investigations in Entity Relationship Extraction ISBN: 9789811953903
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87c44411c36b3e3ec5196becf378ed45
https://doi.org/10.1007/978-981-19-5391-0_3
https://doi.org/10.1007/978-981-19-5391-0_3
Publikováno v:
Investigations in Entity Relationship Extraction ISBN: 9789811953903
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8cb483a673755b972b089a86c2251dfb
https://doi.org/10.1007/978-981-19-5391-0_1
https://doi.org/10.1007/978-981-19-5391-0_1
Publikováno v:
Investigations in Entity Relationship Extraction ISBN: 9789811953903
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::868a7edd6a0c882b737ea5e1bd867821
https://doi.org/10.1007/978-981-19-5391-0_7
https://doi.org/10.1007/978-981-19-5391-0_7
Publikováno v:
Transactions of the Indian Institute of Metals. 72:2209-2217
Given the explosion in availability of scientific documents (books and research papers), automatically extracting cause–effect (CE) relation mentions, along with other arguments such as polarity, uncertainty and evidence, is becoming crucial for cr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24ca25855e807f3812fe70365b59dc8e
https://doi.org/10.1007/s12666-019-01679-z
https://doi.org/10.1007/s12666-019-01679-z
Publikováno v:
International Journal of Data Science and Analytics.
Many complex and important real-life applications, such as surveillance, monitoring and fraud detection, need to identify entire time-series, from a given collection, as anomalous. In this paper, we formulate and propose a solution for this inter-tim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31430d78c4d4cb8e11b4611c05b36f5f
https://doi.org/10.1007/s41060-021-00248-2
https://doi.org/10.1007/s41060-021-00248-2