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| Deletions are marked like this. | Additions are marked like this. |
| Line 11: | Line 11: |
| ||aa278 + cn93||0.6 ||0.448 ||0.454 ||0.6 ||0.448 ||0.454 ||BM25 (b=0.75, k=1.75) + no normalization || | |
| Line 21: | Line 22: |
| ||jh642||0.467||0.31||0.27||0.467||0.31||0.28|| BM25 (b=0.72, k=1.75) + no normalization || | ||jh642||0.47||0.31||0.27||0.47||0.31||0.28|| BM25 (b=0.75, k=1.75) + no normalization || ||lc133+kt101||0.167||0.167||0.118||0.5||0.126||0.099|| BM25 (b=0.1, k=0.001) + row-wise L2 norm || ||ml360||0.6||0.24||0.23||0.6||0.456||0.455|| BM25 (b=0.15, k=0.8) + no normalization || |
Results for Exercise Sheet 8 (Vector Space Model)
Click "Edit (Text)" in the upper bar of this page and add your row to the table below, following the examples already there.
In the first column, write your account name, or name1+name2 if you work in a group.
In the columns 2-4, write down the values of MP@3, MP@R and MAP returned by your process_query() method from ES2.
In the columns 5-7, write down the values of your best result returned by your process_query_vsm() method from ES8.
In the 8th column, give a concise description of the score type and the normalization you have used to achieve the best result in process_query_vsm().
Please write down all values with exactly two digits of precision.
Name |
process_query() from ES2 |
process_query_vsm() from ES8 |
Used combination in process_query_vsm() |
||||
MP@3 |
MP@R |
MAP |
MP@3 |
MP@R |
MAP |
||
ck1028 |
0.60 |
0.45 |
0.45 |
x.xx |
x.xx |
x.xx |
? |
pm169 + tt93 |
0.47 |
0.31 |
0.27 |
0.47 |
0.31 |
0.27 |
BM25 (b=0.75, k=1.75) + no normalization |
ky18 + ll298 |
0.20 |
0.10 |
0.12 |
0.53 |
0.43 |
0.40 |
BM25 (b=0.01, k=0.01) + max - min over column ormalization |
aa278 + cn93 |
0.6 |
0.448 |
0.454 |
0.6 |
0.448 |
0.454 |
BM25 (b=0.75, k=1.75) + no normalization |
ak736 + lf124 |
0.53 |
0.39 |
0.41 |
0.53 |
0.39 |
0.42 |
BM25(b=0.3, k=1.3 ) + no normalization |
jt143 |
0.47 |
0.31 |
0.27 |
0.47 |
0.31 |
0.27 |
BM25 (b=0.75, k=1.75) + no normalization |
by19 + ms1512 |
0.43 |
0.43 |
0.16 |
0.6 |
0.45 |
0.45 |
BM25 (b=0.1, k=0.9) + no normalization |
ms946 |
0.47 |
0.36 |
0.35 |
0.63 |
0.45 |
0.45 |
BM25 (b=0.1, k=0.8) + no normalization + no refinements |
ad289 |
0.60 |
0.42 |
0.43 |
0.60 |
0.43 |
0.44 |
BM25 (b=0.2, k=0.5) + no normalization |
rs442 |
0.57 |
0.41 |
0.44 |
0.57 |
0.41 |
0.44 |
BM25 (b=0.2, k=1.0) + no normalization |
lp218 |
0.47 |
0.31 |
0.28 |
0.5 |
0.29 |
0.29 |
BM25 (b=0.75, k=1.75) + L3 norm, column normalization |
jh465+tk190 |
0.53 |
0.42 |
0.44 |
0.53 |
0.42 |
0.44 |
BM25 (b=0.1, k=1) + no normalization |
jd132+mr277 |
0.53 |
0.41 |
0.40 |
0.53 |
0.41 |
0.40 |
BM25 (b=0.1, k=1.75) + no normalization |
ne38 |
0.53 |
0.41 |
0.41 |
0.53 |
0.41 |
0.41 |
BM25 (b=0.1, k=1.75) + no normalization |
jh642 |
0.47 |
0.31 |
0.27 |
0.47 |
0.31 |
0.28 |
BM25 (b=0.75, k=1.75) + no normalization |
lc133+kt101 |
0.167 |
0.167 |
0.118 |
0.5 |
0.126 |
0.099 |
BM25 (b=0.1, k=0.001) + row-wise L2 norm |
ml360 |
0.6 |
0.24 |
0.23 |
0.6 |
0.456 |
0.455 |
BM25 (b=0.15, k=0.8) + no normalization |