2019:Education/Wikipedia Word Analyzer
 | This is a Closed submission for Wikimania 2019. It has been reviewed and was not accepted. |
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Title[edit | edit source]
Outline of Wikipedia Word Analyzer
Session leader(s)[edit | edit source]
| Full Name* | Email address* | Wikimedia Username (if you have one) | Affiliation | Country | Role, website or any other details you'd like to share |
|---|---|---|---|---|---|
| Yutaka Kubota | qurataro@gmail.com | qurataro | Personal | Japan | https://www.qurataro.com/wikipedia/ |
Session type[edit | edit source]
Each Space at Wikimania 2019 will have specific format requests. The program design prioritises submissions which are future-oriented and directly engage the audience. The format of this submission is a:
- Lecture - 25 min (20 min + 5 min for questions)
Length of session[edit | edit source]
If it is possible, 25 minutes and 5 min question.
Description[edit | edit source]
Wikipedia have a useful rich information. However, we difficult to read long description. So I imaged if the system pick up proper noun and put them around the titles. We might easy to and quickly understand the word. I build the system Japanese version.
Supporting work[edit | edit source]
Optional:
Relationship to the theme[edit | edit source]
This session will address the conference theme — Wikimedia, Free Knowledge and the Sustainable Development Goals — in the following manner: One of the idea of more useful using Wikpedia, And we quickly and easy to lean the huge information using morphology system.
Session outcomes[edit | edit source]
At the end of the session, the following will have been achieved: If we combine rich information and morphology system, We quickly and easy to understand the detail of word.
Relation to other Spaces[edit | edit source]
presentations
Requirements[edit | edit source]
The session will work best with these conditions:
- Recording: