Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
09 API Interactions III.
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
LiLa'16
March 20, 2016
Research
62
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
09 API Interactions III.
LiLa'16
March 20, 2016
More Decks by LiLa'16
See All by LiLa'16
01 Introduction
lila16ecir
0
91
02 Online Evaluation
lila16ecir
0
95
03 LL4IR Architecture
lila16ecir
0
78
04 Use-Cases
lila16ecir
0
79
05 API Interactions I.
lila16ecir
0
69
06 Models for Use-Cases
lila16ecir
0
65
07 API Interactions II.
lila16ecir
0
63
08 Interpreting Feedback
lila16ecir
0
120
10 Simulations
lila16ecir
0
88
Other Decks in Research
See All in Research
L’albédo:levier d’atténuation du changement climatique dans les systèmes fourragers
institutdelelevage
PRO
0
140
[最先端NLP勉強会2026] Checklists Are Better Than Reward Models For Aligning Language Models
nzw0301
1
330
Cross-Media Human-Information Interaction
signer
PRO
0
280
医療LLMの現在地〜最新研究から社会実装までを考える〜
kento1109
1
1.8k
Visual SLAM未来予測 / Future Prediction in Visual SLAM
koide3
1
1.3k
論文読み会 SNLP2026 Tau2-Bench: Evaluating Conversational Agents in a Dual-Control Environment
s_mizuki_nlp
0
300
ICAITD 2026 Oral Presentation
rikkabotan7
0
110
Développer des solutions de réduction des émissions de méthane entérique : 1ers résultats Méthane 2030
institutdelelevage
PRO
0
250
TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis
satai
3
120
敵対生成プロンプト同時探索による内省型プロンプト最適化
kinoue_smarthr
0
440
ハードウェア研究で国際トップ会議を目指す!IROS 2027での論文採択を目指して
ayatokanada
7
4.1k
Santé et fertilité des sols : ce que nous disent les pratiques dans les systèmes de polyculture-élevage
institutdelelevage
PRO
0
120
Featured
See All Featured
Designing for Performance
lara
612
70k
The Mindset for Success: Future Career Progression
greggifford
PRO
0
540
Measuring Dark Social's Impact On Conversion and Attribution
stephenakadiri
2
310
Agile Actions for Facilitating Distributed Teams - ADO2019
mkilby
0
310
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
133
20k
Let's Do A Bunch of Simple Stuff to Make Websites Faster
chriscoyier
508
140k
The Curious Case for Waylosing
cassininazir
1
570
ラッコキーワード サービス紹介資料
rakko
1
5.3M
Easily Structure & Communicate Ideas using Wireframe
afnizarnur
194
17k
Navigating Team Friction
lara
192
16k
How Software Deployment tools have changed in the past 20 years
geshan
2
35k
More Than Pixels: Becoming A User Experience Designer
marktimemedia
3
560
Transcript
Anne Schuth (Blendle / University of Amsterdam, The Netherlands) Krisztian
Balog (University of Stavanger, Norway) Tutorial at ECIR 2016 in Padua, Italy API Interactions III.
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
Feedback endpoint • GET /api/participant/feedback/(key)/ (qid)[/(runid)] • Returns feedback for
this user on this query • runid is optional • qid can be “all”
Feedback endpoint { "feedback": [ {"qid": "S-q1", "runid": "baseline", "modified_time":
"Sun, 27 Apr 2014 13:46:00 -0000", "doclist": [ { "clicked": false, "docid": "R-d89", "team": "participant" }, { "clicked": false, "docid": "R-d87", "team": "site" }, { "clicked": true, "docid": "R-d88", "team": "site" }, ...
Outcome endpoint • GET /api/participant/outcome/(key)/ (qid) • Returns outcome for
this user on this query • Outcomes are aggregated per test period • qid can be “all”
Outcome endpoint { "outcomes": [ { "impressions": 661, "losses": 103,
"outcome": 0.4690721649484536, "qid": "all", "site_id": "R", "test_period": { "end": "Sat, 16 May 2015 00:00:00 -0000", "name": "CLEF LL4IR Round #1", "start": "Fri, 01 May 2015 00:00:00 -0000" }, "ties": 467, "type": "test", "wins": 91 }, ... ] }
Exercise • Complete 03_feedback.py to obtain feedback and outcome for
the queries from the run(s) you submitted in exercise #2
What to do with this feedback? • You figure it
out… • (That might be your next paper)