IWoTM 2019 : 2019 International Workshop on Text Mining (IWoTM 2019)
Call For Papers
●2019 International Workshop on Text Mining (IWoTM 2019)-- Ei Compendex & Scopus—Call for papers
｜August 23-25, 2019｜Vancouver, Canada｜Website: http://www.iwotm.org/
●Venue: Τhe University of British Columbia,Vancouver, Canada
The University of British Columbia (UBC) is a public research university with campuses in Vancouver and Kelowna, British Columbia. Established in 1908, UBC is British Columbia's oldest university. The university is ranked among the top 20 public universities worldwide and among the top three in Canada.
●IWoTM 2019 welcomes researchers, engineers, scientists and industry professionals to an open forum where advances in the field of Text Mining can be shared and examined. The conference is an ideal platform for keeping up with advances and changes to a consistently morphing field.
●Publication and Indexing
All accepted papers will be published in the digital conference proceedings which will send to be indexed by all major citation databases such as Ei Compendex, Scopus, Google Scholar, Cambridge Scientific Abstracts (CSA), Inspec, SCImago Journal & Country Rank (SJR), EBSCO, CrossRef, Thomson Reuters (WoS), etc.
A selection of papers will be recommended to be published in journals.
Prof.Shikharesh Majumdar, Carleton University, Canada
Dr.Ziad Kobti, University of Windsor, Canada
●Program Preview/ Program at a glance
August 23, 2019: Registration + Icebreaker Reception
August 24, 2019: Opening Ceremony+ KN Speech+ Technical Sessions
August 25, 2019: Technical Sessions+ Half day tour/Lab tours
1. PDF version submit via CMT: https://cmt3.research.microsoft.com/IWOTM2019
2. Submit Via email directly to: firstname.lastname@example.org
Ms.Tiya T. Deng
Call for papers(http://www.iwotm.org/cfp.html):
Auto-categorization & auto-metadata generation
Deep learning & machine learning
Document processing and visualization techniques
Entity/noun phrase extraction
Sentiment and social analysis
Text analytics techniques of all kinds
Text mining and knowledge management
User aspects and relations to official statistics