緩やかな死は嫌だ。

Wantedly RecSys 2020 参加レポート④ - 推薦システムにおける「Similarity / 類似性」とは ~ Netflix における事例 ~

Oct 2020

WANTEDLY TECH BOOK 9：Wantedly執筆部

Sept 2020

RecSys Challenge 2020 Workshop: A Stacking Ensemble Model for Prediction of Multi-type Tweet Engagements

Sept 2020

Wantedly RecSys 2020 参加レポート① - Wantedly Data チームで RecSys 2020 にオンライン参加しました

Sept 2020

A Stacking Ensemble Model for Prediction of Multi-type Tweet Engagements

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

「Team Wantedly」 が RecSys Challenge 2020 で３位に入賞しました

June 2020

WWW2020 論文紹介

Apr 2020

会社訪問アプリ「Wantedly Visit」における相互推薦システムの応用事例

Mar 2020

社内での円滑なデータ分析のために

Nov 2019