ウォンテッドリー株式会社 / データサイエンティスト
ウォンテッドリー株式会社 / データサイエンティスト
ウォンテッドリー株式会社 / データサイエンティスト
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In the future
In the future
Visitに関わる全ての人により良い体験をして頂けるよう、プロダクトに対して効果的な施策を立案・実装し続けていきたいです。 また、モデリングスキルだけでなく、より広範囲のエンジニアリングスキルを身につけていき、自分の取り組める仕事の範囲を広げていきたいと思っています。
Mar 2021
Mar 2021
This paper describes the 6th place approach to Booking.com WSDM WebTour 2021 Challenge, which is a challenge with a task of predicting travellers’ next destination. We, in the team "hakubishin3 & u++ & yu-y4", trained four types of Long short-term memory (LSTM) models, and achieved the final score: 0.5399 by weighted averaging of these predictions. There are some differences in these models in feature engineering, multi-task learning, and data augmentation. Our experiments showed that the diversity of the models boosted the final result. Our codes are available at https://github. com/hakubishin3/booking-challenge-2021 and https://github.com/ upura/booking-challenge-2021.
Mar 2021
Mar 2021
Oct 2020
Oct 2020
Sept 2020
Sept 2020
The RecSys Challenge 2020 is a competition with a task of predicting four types of user engagements on Twitter: Like, Reply, Retweet and Retweet with comment. In this paper, we describe Team Wantedly’s approach to this challenge, which won the third place. We found that the targets are highly correlated and it is important to use every engagement to predict the other engagements. Therefore, we choose to stack LightGBM models to use this co-occurrences effectively in the large dataset. Our final scores are as follows: 1.5266 (Retweet PR-AUC), 30.06 (Retweet RCE), 0.1918 (Reply PR-AUC), 20.44 (Reply RCE), 0.7716 (Like PR-AUC), 24.76 (Like RCE), 0.0724 (Retweet with comment PR-AUC), 14.86 (Reply RCE). Our code is available at https://github.com/wantedly/recsys2020-challenge. Shuhei Goda, Naomichi Agata, and Yuya Matsumura. 2020. A Stacking Ensemble Model for Prediction of Multi-Type Tweet Engagements. In Proceedings of the Recommender Systems Challenge 2020. 6-10.
Sept 2020
Sept 2020
June 2020
June 2020
Feb 2020
Feb 2020
Dec 2019
Dec 2019
Dec 2019
Dec 2019
Nov 2019
Nov 2019
Oct 2019
Oct 2019
Oct 2019
Oct 2019
Apr 2020
Apr 2020
Apr 2016 - Aug 2019
統計・機械学習を使ってクライアントのビジネス課題の解決に取り組んできました。一部の案件では分析チームのリードを担当しました。
Aug 2019
Aug 2019
Feb 2018
Feb 2018
Mar 2016
惑星観測用補償光学装置の開発
Mar 2014
惑星観測用補償光学装置の開発
Mar 2021
Mar 2021
Oct 2020
Sept 2020
Sept 2020
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June 2020
Feb 2020
Dec 2019
Nov 2019
Oct 2019
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Japanese - Native