Slack_State_of_Work_2019.pdf
10.5 MB
The State of Work
A survey by Slack and GlobalWebIndex of 17,000 knowledge workers, managers and executives on the state of work today
A survey by Slack and GlobalWebIndex of 17,000 knowledge workers, managers and executives on the state of work today
Forwarded from Городские данные (Anna Barinova)
Как группы людей ведут себя в публичных пространствах: исследование и визуализация студии SWA Group. Каждому паттерну поведения придумано забавное название — например, «Эффект пончика»: https://www.theguardian.com/cities/gallery/2019/aug/01/lizarding-and-flex-allure-how-do-you-use-your-city-plaza-in-pictures-field-guide
the Guardian
From lizarding to lingering: how we really behave in public spaces
From the donut effect to ‘cockroaching’, the Field Guide to Urban Plazas looks at how people behave in public space
https://www.bloomsbury.com/us/facebook-and-conversation-analysis-9781350038288/
https://www.amazon.com/Facebook-Conversation-Analysis-Structure-Organization/dp/1350038288/ref=sr_1_1?keywords=Facebook+Conversation+Analysis+Structure+Organization&qid=1567955005&s=gateway&sr=8-1
https://www.amazon.com/Facebook-Conversation-Analysis-Structure-Organization/dp/1350038288/ref=sr_1_1?keywords=Facebook+Conversation+Analysis+Structure+Organization&qid=1567955005&s=gateway&sr=8-1
Bloomsbury
Facebook and Conversation Analysis
Facebook and Conversation Analysis investigates the structure and organization of comments on a major social media platform, Facebook, using applied conversatio…
CHANCELLOR-DISSERTATION-2019.pdf
944 KB
HUMAN-CENTERED ALGORITHMS AND ETHICAL PRACTICES TO UNDERSTAND DEVIANT MENTAL HEALTH BEHAVIORS IN ONLINE COMMUNITIES
Telegram опубликовал в открытом доступе тестовую версию своего блокчейна — TON. Ссылки на архивы с файлами и хранилище на Github размещены на тестовом сайте ton.org.
Подробнее:
https://tjournal.ru/115571
https://tonlabs.io/main
Подробнее:
https://tjournal.ru/115571
https://tonlabs.io/main
TJ
«Ведомости» рассказали о старте открытого тестирования блокчейна TON. Но связь сайта с Telegram не подтверждена
Платформу может загрузить любой желающий.
We present a method to produce abstractive summaries of long documents that exceed several thousand words via neural abstractive summarization. We perform a simple extractive step before generating a summary, which is then used to condition the transformer language model on relevant information before being tasked with generating a summary.
We show that this extractive step significantly improves summarization results. We also show that this approach produces more abstractive summaries compared to prior work that employs a copy mechanism while still achieving higher rouge scores. Note: The abstract above was not written by the authors, it was generated by one of the models presented in this paper
https://arxiv.org/abs/1909.03186
We show that this extractive step significantly improves summarization results. We also show that this approach produces more abstractive summaries compared to prior work that employs a copy mechanism while still achieving higher rouge scores. Note: The abstract above was not written by the authors, it was generated by one of the models presented in this paper
https://arxiv.org/abs/1909.03186
arXiv.org
On Extractive and Abstractive Neural Document Summarization with...
We present a method to produce abstractive summaries of long documents that exceed several thousand words via neural abstractive summarization. We perform a simple extractive step before...