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| Deletions are marked like this. | Additions are marked like this. |
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| || np151 || 0.68 || 0.48 || 0.47 || b=0.1, k=1 || Weighted number of ratings logarithmically || | || np151 || 0.65 || 0.51 || 0.49 || b=0.1, k=1 || Removed common words and weighted number of ratings logarithmically || |
| Line 14: | Line 14: |
| || ab1561 || 0.62 || 0.43 || 0.43 || b = 0.1, k =1 ||Filtered out common filler words and general nonvalue added words|| |
Results for Exercise Sheet 2 (Ranking)
These results should be based on the file movies-benchmark.test.tsv. Click "Edit" in the upper bar of this page and add your row to the table below, following the examples already there. Please write down all values with exactly two digits of precision. In the first column, write your account name.
Name |
MP@3 |
MP@R |
MAP |
BM25 Parameters |
Refinements |
np151 |
0.65 |
0.51 |
0.49 |
b=0.1, k=1 |
Removed common words and weighted number of ratings logarithmically |
sw1169 |
0.62 |
0.43 |
0.43 |
b=0.1, k=0.75 |
None (baseline) |
pw194 |
0.70 |
0.50 |
0.47 |
b=0.1, k=0.75 |
Weighted in popularity through use of combining imdb_score and imdb_ratings as a single bonus score factor |
os141 |
0.56 |
0.33 |
0.32 |
b=0.75, k=1.75 |
Weighted by IMDB popularity |
le123 |
0.63 |
0.44 |
0.44 |
b=0.1 k=0.6 |
removed the most common english words from the queries |
jk867 |
0.58 |
0.44 |
0.42 |
b=0.01 k=0.8 |
removed most frequent words from the queries |
br124 |
0.62 |
0.43 |
0.44 |
b=0, k=1 |
removed some common words, adjusted evaluation based on other provided metrics |
ts669 |
0.62 |
0.42 |
0.43 |
b=0, k=0.9 |
Documents including all words of a query are boosted |
lk249 |
0.58 |
0.44 |
0.40 |
b=0.1, k=0.75 |
some small words like "with" or "an" are not considered |
ab1561 |
0.62 |
0.43 |
0.43 |
b = 0.1, k =1 |
Filtered out common filler words and general nonvalue added words |