Row 90072

Row ID: 90072 | Dataset Entry | Axioma AXP Content Repository

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I guess that's what's confusing me. The relevance scores would be different for each query, considering that what would be a positive sample for one would be a negative for the other.

In terms of "ideal ranking" I would think that all we have to do is take the retrieved documents and check if the positive documents are in there, then calculate the nDCG based on their position in the retrieved list.

It seems to me like all we need to calculate nDCG is the retrieved list, no?

FieldValue
text I guess that's what's confusing me. The relevance scores would be different for each query, considering that what would be a positive sample for one would be a negative for the other. In terms of "ideal ranking" I would think that all we have to do is take the retrieved documents and check if the positive documents are in there, then calculate the nDCG based on their position in the retrieved list. It seems to me like all we need to calculate nDCG is the retrieved list, no?
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-25
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url_encoded Z0FBQUFBQm5Lak84aGRvcVJKcHZya1Iza2JUQjkwNGZTemVPbWVpR0MwWE43Qzl3UjI3eFZScll0eFBjXzRXbTcycDlnRmhOejZ6SzdJbEZMcnE4QTFVVTMtc1FoZU5BLU95TXJtamZPelVudDY0cFc4VDlDYlNnVWluNlh0bDJGZ0QzeTN4NFotc2QyTG5qMXhNYWhYSWdWOWlta1lKelUzb0Y5ejFfajZ6cGtoYUlXT2VaNW9vT3RNQ2dyN2poSFJTZlpiMHk4TGh1eDhMNU90bVZnRXoxMmhyYmJvdC0xZz09

Raw Record

{
  "text": "I guess that's what's confusing me. The relevance scores would be different for each query, considering that what would be a positive sample for one would be a negative for the other.\n\nIn terms of \"ideal ranking\" I would think that all we have to do is take the retrieved documents and check if the positive documents are in there, then calculate the nDCG based on their position in the retrieved list.\n\nIt seems to me like all we need to calculate nDCG is the retrieved list, no?",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-25",
  "username_encoded": "Z0FBQUFBQm5Lak1yVmlreWg2S3lGdjVENDJZRlhDelM0eU5Lc05pSjB6OXdjdjRUVnFVTDY5czBPNFkzZDNMUDBtbGxWclE5MFIycXphRFJrc2kwTzd6Z0dtc1pYa1JIcnc9PQ==",
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}
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