Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Collaborative Topic Modeling for Recommending S...

Avatar for Shinichi Takayanagi Shinichi Takayanagi
May 30, 2016
Research
0
1.5k

Collaborative Topic Modeling for Recommending Scientific Articles

論文"Collaborative Topic Modeling for Recommending Scientific Articles"を読んだ際に使用したスライド

Avatar for Shinichi Takayanagi

Shinichi Takayanagi

May 30, 2016
Tweet

More Decks by Shinichi Takayanagi

See All by Shinichi Takayanagi
バイブコーディングの正体——AIエージェントはソフトウェア開発を変えるか？
Avatar for Shinichi Takayanagi stakaya
5
960
[NeurIPS 2023 論文読み会] Wasserstein Quantum Monte Carlo
Avatar for Shinichi Takayanagi stakaya
0
530
[KDD2021 論文読み会] ControlBurn: Feature Selection by Sparse Forests
Avatar for Shinichi Takayanagi stakaya
2
1.9k
[ICML2021 論文読み会] Mandoline: Model Evaluation under Distribution Shift
Avatar for Shinichi Takayanagi stakaya
0
2k
[情報検索/推薦 各社合同 論文読み祭 #1] KDD ‘20 "Embedding-based Retrieval in Facebook Search"
Avatar for Shinichi Takayanagi stakaya
2
610
【2020年新人研修資料】ナウでヤングなPython開発入門
Avatar for Shinichi Takayanagi stakaya
29
21k
論文読んだ「Simple and Deterministic Matrix Sketching」
Avatar for Shinichi Takayanagi stakaya
1
1.2k
Quick Introduction to Approximate Bayesian Computation (ABC) with R"
Avatar for Shinichi Takayanagi stakaya
3
340
The Road to Machine Learning Engineer from Data Scientist
Avatar for Shinichi Takayanagi stakaya
5
4.4k

Other Decks in Research

See All in Research
電通総研の生成AI・エージェントの取り組み エンジニアリング業務向けAI活用事例紹介
Avatar for AITC - DENTSU SOKEN isidaitc
1
860
Delta Airlines® Customer Care in the U.S.: How to Reach Them Now
Avatar for booking.comcustomerservice bookingcomcustomersupportusa
0
110
経済学と機械学習：因果推論と密度比推定を中心に
Avatar for MasaKat0 masakat0
0
130
[CV勉強会@関東 CVPR2025] VLM自動運転model S4-Driver
Avatar for Shin-kyoto shinkyoto
2
450
SSII2025 [TS1] 光学・物理原理に基づく深層画像生成
Avatar for 画像センシングシンポジウム ssii
PRO
4
4.1k
SSII2025 [SS1] レンズレスカメラ
Avatar for 画像センシングシンポジウム ssii
PRO
2
1k
EarthSynth: Generating Informative Earth Observation with Diffusion Models
Avatar for SatAI.challenge satai
3
170
近似動的計画入門
Avatar for MIKIO KUBO mickey_kubo
4
1k
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities
Avatar for SatAI.challenge satai
3
150
20250725-bet-ai-day
Avatar for cipepser cipepser
2
370
【緊急警告】日本の未来設計図 ～沈没か、再生か。国民と断行するラストチャンス～
Avatar for 高木祐介 yuutakasan
0
150
NLP2025参加報告会 LT資料
Avatar for Hayahide Yamagishi hargon24
1
350

Featured

See All Featured
Practical Orchestrator
Avatar for Shlomi Noach shlominoach
190
11k
GitHub's CSS Performance
Avatar for Jon Rohan jonrohan
1031
460k
Speed Design
Avatar for Sergey Chernyshev sergeychernyshev
32
1.1k
How To Stay Up To Date on Web Technology
Avatar for Chris Coyier chriscoyier
790
250k
Navigating Team Friction
Avatar for Lara Hogan lara
188
15k
Building a Scalable Design System with Sketch
Avatar for Laura Van Doore lauravandoore
462
33k
Easily Structure & Communicate Ideas using Wireframe
Avatar for Afnizar Nur Ghifari afnizarnur
194
16k
Building Flexible Design Systems
Avatar for Yesenia Perez-Cruz yeseniaperezcruz
328
39k
How to train your dragon (web standard)
Avatar for Monica Dinculescu notwaldorf
96
6.2k
JavaScript: Past, Present, and Future - NDC Porto 2020
Avatar for David Neal reverentgeek
50
5.5k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
Avatar for Kevin Liebholz kevinliebholz
34
6k
Building an army of robots
Avatar for Kyle Neath kneath
306
45k

Transcript

  1. RCO論文輪読会(2016/05/27) “Collaborative topic modeling for recommending scientific articles”(KDD2011) Chong Wang,

    David M. Blei 高柳慎一

  2. （C）Recruit Communications Co., Ltd. ABSTRACT 1

  3. （C）Recruit Communications Co., Ltd. 1. INTRODUCTION 2

  4. （C）Recruit Communications Co., Ltd. 1. INTRODUCTION 3

  5. （C）Recruit Communications Co., Ltd. 1. INTRODUCTION 4

  6. （C）Recruit Communications Co., Ltd. 2. BACKGROUND ＆ 2.1 Recommendation Tasks

    5

  7. （C）Recruit Communications Co., Ltd. 2.1 Recommendation Tasks 6

  8. （C）Recruit Communications Co., Ltd. 2.1 Recommendation Tasks 7

  9. （C）Recruit Communications Co., Ltd. 2.2 Recommendation by Matrix Factorization 8

  10. （C）Recruit Communications Co., Ltd. 2.2 Recommendation by Matrix Factorization 9

  11. （C）Recruit Communications Co., Ltd. 2.2 Recommendation by Matrix Factorization 10

  12. （C）Recruit Communications Co., Ltd. 2.2 Recommendation by Matrix Factorization 11

  13. （C）Recruit Communications Co., Ltd. 2.3 Probabilistic Topic Models 12

  14. （C）Recruit Communications Co., Ltd. LDAの生成過程 13

  15. （C）Recruit Communications Co., Ltd. LDAの特徴 14

  16. （C）Recruit Communications Co., Ltd. 3. COLLABORATIVE TOPIC REGRESSION 15

  17. （C）Recruit Communications Co., Ltd. COLLABORATIVE TOPIC REGRESSION 16

  18. （C）Recruit Communications Co., Ltd. CTRの生成過程 17

  19. （C）Recruit Communications Co., Ltd. 3. COLLABORATIVE TOPIC REGRESSION 18

  20. （C）Recruit Communications Co., Ltd. CTRのモデルのRegressionたる所以 19

  21. （C）Recruit Communications Co., Ltd. 学習のさせ方 20

  22. （C）Recruit Communications Co., Ltd. 学習のさせ方 21

  23. （C）Recruit Communications Co., Ltd. 簡単な証明 by iPad手書き 22

  24. （C）Recruit Communications Co., Ltd. 学習のさせ方 23

  25. （C）Recruit Communications Co., Ltd. 予測 24

  26. （C）Recruit Communications Co., Ltd. 4. EMPIRICAL STUDY 25

  27. （C）Recruit Communications Co., Ltd. データの規模感 26

  28. （C）Recruit Communications Co., Ltd. 評価 27

  29. （C）Recruit Communications Co., Ltd. 結果 28

  30. （C）Recruit Communications Co., Ltd. 結果 (ライブラリ内の論文数(Fig 5)・ある論文をLikeした数(Fig 6) 依存性) 29

    数が増えると Recallが下がる (あまり有名な論文じゃ ないのを出すため) 数が増えると Recallが上がる (みんな見てる論文 だとCFがうまく動く)

  31. （C）Recruit Communications Co., Ltd. 結果(ある2ユーザの好んだトピックを抽出) 30 トピックの潜 在ベクトルの 重みをランキ ングして抽出

  32. （C）Recruit Communications Co., Ltd. 結果(オフセットの大きかった論文BEST 10) 31 ※内容よりもCFが効くケースに相当

  33. （C）Recruit Communications Co., Ltd. 結果(EMの論文がベイズ統計勢にもよく参照されている例) 32 ※内容よりもCFが効く ケースに相当

  34. （C）Recruit Communications Co., Ltd. 結果(逆にトピックが広がらない例) 33 ※内容が支配的なケー スに相当

  35. （C）Recruit Communications Co., Ltd. 5. CONCLUSIONS AND FUTURE WORK 34