Briefly reviews International Conference on Weblogs and Social Media (ICWSM12) from my perspective.
The latter part written in Japanese, sorry for that.
□Author
Masaya Mori, Global Head of Rakuten Institute of Technology, Executive Officer, Rakuten Inc.
森正弥 楽天株式会社 執行役員 兼 楽天技術研究所代表
□Description
そもそもなぜ人工知能(AI)をビジネスで活用する必要があるのかの視点に基づいて、AI活用戦略について述べた講演の資料です。
Paper reading - Dropout as a Bayesian Approximation: Representing Model Uncer...Akisato Kimura
Introducing the paper "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning" presented in ICML2016 (in Japanese).
Updated version of https://www.slideshare.net/akisatokimura/paper-reading-dropout-as-a-bayesian-approximation-representing-model-uncertainty-in-deep-learning
Paper reading - Dropout as a Bayesian Approximation: Representing Model Uncer...Akisato Kimura
A stale version, please check https://www.slideshare.net/akisatokimura/paper-reading-dropout-as-a-bayesian-approximation-representing-model-uncertainty-in-deep-learning-166237519 for a new version.
Introducing the paper "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning" presented in ICML2016 (in Japanese).
□Author
Masaya Mori, Global Head of Rakuten Institute of Technology, Executive Officer, Rakuten Inc.
森正弥 楽天株式会社 執行役員 兼 楽天技術研究所代表
□Description
そもそもなぜ人工知能(AI)をビジネスで活用する必要があるのかの視点に基づいて、AI活用戦略について述べた講演の資料です。
Paper reading - Dropout as a Bayesian Approximation: Representing Model Uncer...Akisato Kimura
Introducing the paper "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning" presented in ICML2016 (in Japanese).
Updated version of https://www.slideshare.net/akisatokimura/paper-reading-dropout-as-a-bayesian-approximation-representing-model-uncertainty-in-deep-learning
Paper reading - Dropout as a Bayesian Approximation: Representing Model Uncer...Akisato Kimura
A stale version, please check https://www.slideshare.net/akisatokimura/paper-reading-dropout-as-a-bayesian-approximation-representing-model-uncertainty-in-deep-learning-166237519 for a new version.
Introducing the paper "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning" presented in ICML2016 (in Japanese).
Brief description of the paper "Large-scale visual sentiment ontology and detectors using adjective noun pairs" presented in ACM Multimedia 2013 as a full paper.
4. What’s ICWSM?
International AAAI Conference on Weblogs
and Social Media
Annual conference, 6th for this year.
Seems to be a conference on Twitter & other
social media, few papers as to weblogs.
A lot of participants from companies and labs
about SNS, mass media, ads, and marketing.
A major cluster = sociologists,
a unique conference hosted by AAAI.
5. Symbolic panel discussions
I Want to (Net)work With You, But I Don't
Know What/Where/Who You Are
Panelists from Cisco, IBM, LinkedIn & Datahug
News Generation and Consumption Through
Social Media
Panelists from Storyful, Newswhip, Irish Times,
C-SPAN & Guardian
Machine learning accounts for a small portion.
6. Basic statistics
Only single track
Not high quality
as the rate indicates
Our presentation (can’t see any other JPN pres.)
Attendees: over 330 in advanced registration (x3 of papers),
half of them from USA, only 5 from Japan.
7. General overview
Computer science << sociology
Data collecting, analyses & discussions
> results > performance > technical novelty
Most oral presentations with high quality
Especially in terms of analysis and discussions.
Don’t mind theoretical soundness and novelty.
2 giants: Twitter & Facebook
But, we should not rely only on the giants.
The direction includes cross platform analysis.
8. Interesting events & efforts
Town hall meeting
Discussing future directions of the conference
with all the participants, not only PC members.
Industrial panel
With powerful debaters from various industries
Dataset sharing service
Provides new datasets used by papers.
All datasets released as openly available
community resources. http://icwsm.cs.mcgill.ca
9. Resources
All the papers presented in the main
conference can be freely accessible from
http://www.aaai.org/Library/ICWSM/icwsm12contents.php
All the workshop papers are also free :
http://www.aaai.org/Library/Workshops/workshops-library.php
I gathered most tweets as to ICWSM 12,
freely accessible from
http://togetter.com/id/_akisato
10. Our presentation
Creating Stories : Social Curation of Twitter
Messages
Curated lists = supervised corpora for analyzing
microblog messages
http://www.brl.ntt.co.jp/people/akisato/socialweb1.html
11. 面白かった発表 1
The Livehoods Project: Utilizing Social Media
to Understand the Dynamics of a City
Won the Best Paper Award
Twitterタイムラインから取れる
位置情報(tweets with geotags, 4sq etc.)から,
かなり局所的な地域の特性の変化が掴める.
URL: http://livehoods.org
Twitter ID: @livehoods
20. 面白かった発表 その他羅列1
Crossing Media Streams with Sentiment:
Domain Adaptation in Blogs, Reviews and
Twitter
Sentiment analysisをTwitterだけでやるの
無理だから,reviewやblogを教師に使う.
Exploring Social-Historical Ties on Location-
Based Social Networks
Foursquareもの.トピックと位置,両方使う.
階層Pitman-Yor過程によるモデル化
21. 面白かった発表 その他羅列2
The Emergence of Conventions in Online
Social Networks
Won the Best Paper Award
Twitterにおける「文法」らしきものは,基本
的にボトムアップにできあがってきたもの.
それを網羅的に検証.