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🔷از سری جلسات آزمایشگاه علوم داده دانشکده ریاضی
🔻کتابخانه Numpy
🗓 دوشنبه ۲۸ بهمن ساعت 17
📌 کلاس 311 دانشکده ریاضی
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🔻کتابخانه Numpy
🗓 دوشنبه ۲۸ بهمن ساعت 17
📌 کلاس 311 دانشکده ریاضی
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DataScienceLab
🔷از سری جلسات آزمایشگاه علوم داده دانشکده ریاضی 🔻کتابخانه Numpy 🗓 دوشنبه ۲۸ بهمن ساعت 17 📌 کلاس 311 دانشکده ریاضی ‼️برای شرکت حتما فرم زیر را تکمیل کنید‼️ ثبت نام
دوستان توجه داشته باشید که زمان برگزاری این جلسه هفته بعد است.
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🗓 دوشنبه 5 اسفند ساعت 17
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جلسه این هفته به دلیل حفظ سلامت شما دوستان برگزار نخواهد شد. اگر شرایط به همین روال ادامه یابد به احتمال زیاد باقی جلسات تا پایان سال به صورت مجازی برگزار میشوند.
🔷از سری جلسات آزمایشگاه علوم داده دانشکده ریاضی
🔻کتابخانه Pandas
🗓 دوشنبه 12 اسفند ساعت 17
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🔷از سری جلسات آزمایشگاه علوم داده دانشکده ریاضی
🔻کتابخانه Pandas
🗓 دوشنبه 19 اسفند ساعت 17
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🔷از سری جلسات آزمایشگاه علوم داده دانشکده ریاضی 🔻کتابخانه Pandas 🗓 دوشنبه 19 اسفند ساعت 17 📌به دلیل تعطیلی دانشگاه این جلسه آنلاین در پلتفرم freeconferencecall.com برگزار خواهد شد. ‼️برای شرکت حتما فرم زیر را تکمیل کنید‼️ ثبت نام
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Call for participation at the RecSys Challenge 2020
About the Challenge
The RecSys Challenge 2020 is organized by Politecnico di Bari, Free University of Bozen-Bolzano, TU Wien, University of Colorado, Boulder, and Universidade Federal de Campina Grande, and sponsored by Twitter.
On Twitter, users post and engage with (in the form of Likes, Replies, Retweets and Retweets with comments) content known as “Tweets”. This challenge aims to evaluate novel algorithms for predicting different engagement rates at a large scale, and to push the state-of-the-art in recommender systems. Following the success and advancements in the domain of top-K recommendations, the development of new approaches is encouraged by releasing the largest real-world dataset to predict user engagements. The dataset comprises of roughly 160 million public engagements, along with user and engagement features, that span a period of 2 weeks and contain public interactions (Like, Reply, Retweet and Retweet with comment), as well as roughly 100 million pseudo negatives which are randomly sampled from the public follow graph. While sampling the latter pool of Tweets, a special care is taken about preserving user privacy.
The submitted results will be evaluated on a held-out test set generated from more recent Tweets on the platform. The evaluation metrics will include precision-recall area under curve (PR-AUC) and cross-entropy loss. Participants will also be provided with a validation set, for which the engagement information will be missing. Paying special attention to the users’ privacy, the dataset will be updated daily to ensure GDPR-compliance and the corresponding metrics will be updated on the leaderboard.
Prizes
The best three teams will be rewarded with the following prizes:
Winner: $15,000
Second team: $10,000
Third team: $5,000
Dataset Denoscription
Each data entry will be characterized by the engagement features, user features (for both engaging and authoring users, at the time of data extraction), and tweet features. In total, three datasets will be released:
A training set, obtained by subsampling positive interaction within ~2 weeks
A test set (10% of train), sampled from 24 hours of data
A validation set (10% of train), sampled from 24 hours of data
Participation
In order for participants to gain access to this dataset, and to participate in the challenge, each individual needs to register for a developer account through the following link. It is advised to do so as early as possible, as access to the data cannot be granted without prior authorisation.
As part of the RecSys Challenge, you may access Twitter Content (as defined in Twitter Developer Agreement and Policy). Your access to and use of the Twitter Content is governed by the Twitter Developer Agreement and Policy). Your access to the Twitter Content is limited to the purposes of the RecSys Challenge and those approved via the application process. The Twitter Developer Agreement and Policy do not expand the license to the Twitter Content.
In addition to the restrictions set out in the Twitter Developer Agreement and Policy, isolating individual Tweets or users for purposes other than participation in this challenge is strictly forbidden. Other restricted uses of the dataset can be found here.
In order to participate in the RecSys Challenge, individuals need to sign up here and here to agree to the Twitter Developer Agreement and Policy and RecSys Challenge's Terms & Conditions listed here. Twitter is only providing a data set solely as a sponsor of Recsys Challenge 2020. Twitter is not responsible for the RecSys Challenge, which shall be controlled and administered by RecSys as explained here and here. Following the RecSys Challenge, Twitter may make the dataset available for researchers to access subject to the Twitter Developer Agreement and Policy.
Important Dates
About the Challenge
The RecSys Challenge 2020 is organized by Politecnico di Bari, Free University of Bozen-Bolzano, TU Wien, University of Colorado, Boulder, and Universidade Federal de Campina Grande, and sponsored by Twitter.
On Twitter, users post and engage with (in the form of Likes, Replies, Retweets and Retweets with comments) content known as “Tweets”. This challenge aims to evaluate novel algorithms for predicting different engagement rates at a large scale, and to push the state-of-the-art in recommender systems. Following the success and advancements in the domain of top-K recommendations, the development of new approaches is encouraged by releasing the largest real-world dataset to predict user engagements. The dataset comprises of roughly 160 million public engagements, along with user and engagement features, that span a period of 2 weeks and contain public interactions (Like, Reply, Retweet and Retweet with comment), as well as roughly 100 million pseudo negatives which are randomly sampled from the public follow graph. While sampling the latter pool of Tweets, a special care is taken about preserving user privacy.
The submitted results will be evaluated on a held-out test set generated from more recent Tweets on the platform. The evaluation metrics will include precision-recall area under curve (PR-AUC) and cross-entropy loss. Participants will also be provided with a validation set, for which the engagement information will be missing. Paying special attention to the users’ privacy, the dataset will be updated daily to ensure GDPR-compliance and the corresponding metrics will be updated on the leaderboard.
Prizes
The best three teams will be rewarded with the following prizes:
Winner: $15,000
Second team: $10,000
Third team: $5,000
Dataset Denoscription
Each data entry will be characterized by the engagement features, user features (for both engaging and authoring users, at the time of data extraction), and tweet features. In total, three datasets will be released:
A training set, obtained by subsampling positive interaction within ~2 weeks
A test set (10% of train), sampled from 24 hours of data
A validation set (10% of train), sampled from 24 hours of data
Participation
In order for participants to gain access to this dataset, and to participate in the challenge, each individual needs to register for a developer account through the following link. It is advised to do so as early as possible, as access to the data cannot be granted without prior authorisation.
As part of the RecSys Challenge, you may access Twitter Content (as defined in Twitter Developer Agreement and Policy). Your access to and use of the Twitter Content is governed by the Twitter Developer Agreement and Policy). Your access to the Twitter Content is limited to the purposes of the RecSys Challenge and those approved via the application process. The Twitter Developer Agreement and Policy do not expand the license to the Twitter Content.
In addition to the restrictions set out in the Twitter Developer Agreement and Policy, isolating individual Tweets or users for purposes other than participation in this challenge is strictly forbidden. Other restricted uses of the dataset can be found here.
In order to participate in the RecSys Challenge, individuals need to sign up here and here to agree to the Twitter Developer Agreement and Policy and RecSys Challenge's Terms & Conditions listed here. Twitter is only providing a data set solely as a sponsor of Recsys Challenge 2020. Twitter is not responsible for the RecSys Challenge, which shall be controlled and administered by RecSys as explained here and here. Following the RecSys Challenge, Twitter may make the dataset available for researchers to access subject to the Twitter Developer Agreement and Policy.
Important Dates
March 4: Challenge goes live
June 1:
Validation server closes
Test set released
Test server opens
June 7: Challenge closes
June 15: Test results released
July 1: Paper Submission Due
August 1: Paper Acceptance Notifications
August 14: Deadline for camera-ready papers
September 22-26: Workshop taking place as part of the ACM RecSys conference in Rio de Janeiro, Brazil
For more details see here and here, and if you have any questions, feel free to post them here.
All the best,
RecSys Challenge 2020 Team
June 1:
Validation server closes
Test set released
Test server opens
June 7: Challenge closes
June 15: Test results released
July 1: Paper Submission Due
August 1: Paper Acceptance Notifications
August 14: Deadline for camera-ready papers
September 22-26: Workshop taking place as part of the ACM RecSys conference in Rio de Janeiro, Brazil
For more details see here and here, and if you have any questions, feel free to post them here.
All the best,
RecSys Challenge 2020 Team