Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
07 API Interactions II.
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
LiLa'16
March 20, 2016
Research
60
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
07 API Interactions II.
LiLa'16
March 20, 2016
More Decks by LiLa'16
See All by LiLa'16
01 Introduction
lila16ecir
0
87
02 Online Evaluation
lila16ecir
0
93
03 LL4IR Architecture
lila16ecir
0
72
04 Use-Cases
lila16ecir
0
78
05 API Interactions I.
lila16ecir
0
69
06 Models for Use-Cases
lila16ecir
0
64
08 Interpreting Feedback
lila16ecir
0
110
09 API Interactions III.
lila16ecir
0
60
10 Simulations
lila16ecir
0
84
Other Decks in Research
See All in Research
さくらインターネット研究所テックトーク2026春、研究開発Gr.25年度成果26年度方針
kikuzo
0
150
多様なデータを許容し学習し続ける模倣学習 / Advanced Imitation Learning for VLA
prinlab
0
220
明日から使える!研究効率化ツール入門
matsui_528
13
7.3k
英語教育 “研究” のあり方:学術知とアウトリーチの緊張関係
terasawat
1
990
typst の使い方:言語学を研究する学生のために
gitomochang
0
460
2026年1月の生成AI領域の重要リリース&トピック解説
kajikent
0
1k
セマンティック通信勉強会 6Gに向けたデバイス間効率的な通信の技術紹介・課題・今後展望
satai
3
160
The mathematics of transformers
gpeyre
0
320
Anthropic が提案する LLM の内部状態を自然言語で説明可能にした Natural Language Autoencoders / Natural Language Autoencoders Produce Unsupervised Explanations of LLM Activations
shunk031
0
130
LLM Compute Infrastructure Overview
karakurist
2
1.4k
LiDAR点群の地表面分類手法の比較・検証
vegapunkhiroshi79
0
120
第66回コンピュータビジョン勉強会@関東 Epona: Autoregressive Diffusion World Model for Autonomous Driving
kentosasaki
0
630
Featured
See All Featured
Building a Modern Day E-commerce SEO Strategy
aleyda
45
9.1k
How to Align SEO within the Product Triangle To Get Buy-In & Support - #RIMC
aleyda
2
1.5k
BBQ
matthewcrist
89
10k
ラッコキーワード サービス紹介資料
rakko
1
3.6M
Lightning talk: Run Django tests with GitHub Actions
sabderemane
0
200
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
55k
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
PRO
201
75k
How to optimise 3,500 product descriptions for ecommerce in one day using ChatGPT
katarinadahlin
PRO
1
3.6k
The Curious Case for Waylosing
cassininazir
1
390
Leo the Paperboy
mayatellez
7
1.8k
Navigating the Design Leadership Dip - Product Design Week Design Leaders+ Conference 2024
apolaine
1
350
Navigating Algorithm Shifts & AI Overviews - #SMXNext
aleyda
1
1.3k
Transcript
Anne Schuth (Blendle / University of Amsterdam, The Netherlands) Krisztian
Balog (University of Stavanger, Norway) Tutorial at ECIR 2016 in Padua, Italy API Interactions II.
Outline for API interactions • Obtaining an API key and
signing up for a site • Getting queries and candidate items • Generating and uploading rankings • Obtaining feedback and outcome
Uploading ranking Living Labs API Researcher ranking click Queries Documents
Run endpoint • PUT /api/participant/run/(key)/(qid) • Submit a ranking for
a specific query • A run is just a ranking of docids as shown to users • A run can be updated • Note: runs for test queries can only be updated before the test period starts
Example { 'doclist': [ {'docid': u'R-d70'}, {'docid': u'R-d72'}, {'docid': u'R-d74'},
{'docid': u'R-d75'}, {'docid': u'R-d1270'}, {'docid': u'R-d73'}, {'docid': u'R-d1271'}, {'docid': u'R-d71'}], 'qid': u'R-q2', 'runid': "LiLa’16" } R-q2 Q0 R-d70 1 0.9 LiLa16 R-q2 Q0 R-d72 2 0.8 LiLa16 R-q2 Q0 R-d74 3 0.7 LiLa16 R-q2 Q0 R-d75 4 0.6 LiLa16 R-q2 Q0 R-d1270 5 0.5 LiLa16 R-q2 Q0 R-d73 6 0.4 LiLa16 R-q2 Q0 R-d1271 7 0.3 LiLa16 R-q2 Q0 R-d71 8 0.2 LiLa16
Example { 'doclist': [ {'docid': u'R-d70'}, {'docid': u'R-d72'}, {'docid': u'R-d74'},
{'docid': u'R-d75'}, {'docid': u'R-d1270'}, {'docid': u'R-d73'}, {'docid': u'R-d1271'}, {'docid': u'R-d71'}], 'qid': u'R-q2', 'runid': "LiLa’16" } PUT http://api.living-labs.net/api/ participant/doclist/(key)/R-q2
Historical feedback • Go figure • http://doc.living-labs.net/en/latest/api- participant.html#historical-feedback
Exercise • Code for baseline (single field) retrieval and uploading
the ranking to the API is given in 02_ranker.py 1. Implement multi-field retrieval 2. Incorporate historical feedback into the ranking