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Semantic Software Lab
Concordia University
Montréal, Canada

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Monday May 20, 2019
Start: 2019-05-20

Language, Data and Knowledge (LDK) aims at bringing together researchers from across disciplines concerned with the acquisition, curation and use of language data in the context of data science and knowledge-based applications. With the advent of the Web and digital technologies, an ever increasing amount of language data is now available across application areas and industry sectors, including social media, digital archives, company records, etc. The efficient and meaningful exploitation of this data in scientific and commercial innovation is at the core of data science research, employing NLP and machine learning methods as well as semantic technologies based on knowledge graphs

Tuesday May 21, 2019

Language, Data and Knowledge (LDK) aims at bringing together researchers from across disciplines concerned with the acquisition, curation and use of language data in the context of data science and knowledge-based applications. With the advent of the Web and digital technologies, an ever increasing amount of language data is now available across application areas and industry sectors, including social media, digital archives, company records, etc. The efficient and meaningful exploitation of this data in scientific and commercial innovation is at the core of data science research, employing NLP and machine learning methods as well as semantic technologies based on knowledge graphs

Wednesday May 22, 2019
Start: 2019-05-20
End: 2019-05-22

Language, Data and Knowledge (LDK) aims at bringing together researchers from across disciplines concerned with the acquisition, curation and use of language data in the context of data science and knowledge-based applications. With the advent of the Web and digital technologies, an ever increasing amount of language data is now available across application areas and industry sectors, including social media, digital archives, company records, etc. The efficient and meaningful exploitation of this data in scientific and commercial innovation is at the core of data science research, employing NLP and machine learning methods as well as semantic technologies based on knowledge graphs

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