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09 API Interactions III.
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LiLa'16
March 20, 2016
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09 API Interactions III.
LiLa'16
March 20, 2016
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01 Introduction
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02 Online Evaluation
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03 LL4IR Architecture
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04 Use-Cases
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05 API Interactions I.
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06 Models for Use-Cases
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07 API Interactions II.
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08 Interpreting Feedback
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10 Simulations
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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)