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golf_system_0: using word embedding to construct document vector and calculate similarity by four features including cosine sim and euclidean distance.
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golf_system_1: introducing TF-IDF cosine similarits (tweet VS vclaim_content, tweet VS vclaim_title) and BM25 scores (tweet VS vclaim_content, tweet VS vclaim_title) as features, Linear SVC as model
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golf_system_2: introducing TF-IDF cosine similarits (tweet VS vclaim_content, tweet VS vclaim_title) and BM25 scores (tweet VS vclaim_content, tweet VS vclaim_title) as features, Logistic Regression as model
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golf_system_3: introducing TF-IDF cosine similarits (tweet VS vclaim_content, tweet VS vclaim_title) and BM25 scores (tweet VS vclaim_content, tweet VS vclaim_title) as features, Linear Regression as model
BaseLine:
| metric | @depth | score |
|---|---|---|
| map | 1 | 0.470 |
| map | 3 | 0.601 |
| map | 5 | 0.609 |
| map | 10 | 0.615 |
| map | 20 | 0.617 |
| map | all | 0.619 |
| precision | 1 | 0.472 |
| precision | 3 | 0.249 |
| precision | 5 | 0.156 |
| precision | 10 | 0.082 |
| precision | 20 | 0.043 |
| precision | all | 0.000 |
| reciprocal_rank | 1 | 0.472 |
| reciprocal_rank | 3 | 0.603 |
| reciprocal_rank | 5 | 0.611 |
| reciprocal_rank | 10 | 0.616 |
| reciprocal_rank | 20 | 0.619 |
| reciprocal_rank | all | 0.621 |
System 1:
| metric | @depth | score |
|---|---|---|
| map | 1 | 0.622 |
| map | 3 | 0.622 |
| map | 5 | 0.622 |
| map | 10 | 0.622 |
| map | 20 | 0.622 |
| map | all | 0.622 |
| precision | 1 | 0.624 |
| precision | 3 | 0.208 |
| precision | 5 | 0.125 |
| precision | 10 | 0.062 |
| precision | 20 | 0.031 |
| precision | all | 0.000 |
| reciprocal_rank | 1 | 0.624 |
| reciprocal_rank | 3 | 0.624 |
| reciprocal_rank | 5 | 0.624 |
| reciprocal_rank | 10 | 0.624 |
| reciprocal_rank | 20 | 0.624 |
| reciprocal_rank | all | 0.624 |
System 2:
| metric | @depth | score |
|---|---|---|
| map | 1 | 0.612 |
| map | 3 | 0.612 |
| map | 5 | 0.612 |
| map | 10 | 0.612 |
| map | 20 | 0.612 |
| map | all | 0.612 |
| precision | 1 | 0.614 |
| precision | 3 | 0.205 |
| precision | 5 | 0.123 |
| precision | 10 | 0.061 |
| precision | 20 | 0.031 |
| precision | all | 0.000 |
| reciprocal_rank | 1 | 0.614 |
| reciprocal_rank | 3 | 0.614 |
| reciprocal_rank | 5 | 0.614 |
| reciprocal_rank | 10 | 0.614 |
| reciprocal_rank | 20 | 0.614 |
| reciprocal_rank | all | 0.614 |
System 3: map@5 0.586