Difference between revisions of "2010:Query-by-Singing/Humming Results"
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===General Legend=== | ===General Legend=== | ||
− | ==== | + | == General Legend == |
− | + | {| border="1" cellspacing="0" style="text-align: left; width: 800px;" | |
− | + | |- style="background: yellow;" | |
− | + | ! width="80" | Sub code | |
− | " | + | ! width="200" | Submission name |
− | " | + | ! width="80" style="text-align: center;" | Abstract |
+ | ! width="440" | Contributors | ||
+ | |- | ||
+ | ! HAFR1 | ||
+ | | QBH Simbals || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2010/HAFR1.pdf PDF] || [http://dept-info.labri.fr/~hanna Pierre Hanna], [http://simbals.labri.fr Julien Allali], [http://simbals.labri.fr Pascal Ferraro], [http://simbals.labri.fr Matthias Robine] | ||
+ | |- | ||
+ | ! JY1 | ||
+ | | The programs of QBSH -beginning|| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2010/JY1.pdf PDF] || [http://www.tsinghua.edu.cn/eng/index.jsp Jingzhou Yang] | ||
+ | |- | ||
+ | ! JY2 | ||
+ | | The programs of QBSH -anywhere|| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2010/JY1.pdf PDF] || [http://www.tsinghua.edu.cn/eng/index.jsp Jingzhou Yang] | ||
+ | |- | ||
+ | ! YF1 | ||
+ | | Yeh, Fang -beginning|| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2010/YF1.pdf PDF] || [http://mirlab.org/users/kenshincs Tzu-chun Yeh], [http://mirlab.org/users/markfang Yi-fan Fang] | ||
+ | |- | ||
+ | ! YF2 | ||
+ | | Yeh, Fang -anywhere || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2010/YF1.pdf PDF] || [http://mirlab.org/users/kenshincs Tzu-chun Yeh], [http://mirlab.org/users/markfang Yi-fan Fang] | ||
+ | |} | ||
===Task 1 Results=== | ===Task 1 Results=== | ||
Line 29: | Line 46: | ||
=====Task 1a Friedman's Test for Significant Differences===== | =====Task 1a Friedman's Test for Significant Differences===== | ||
− | The Friedman test was run in MATLAB against the QBSH Task | + | The Friedman test was run in MATLAB against the QBSH Task 1a Simple/MRR data over the 48 ground truth song groups. |
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05); | Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05); | ||
Simple Hit/Miss Count: | Simple Hit/Miss Count: | ||
− | <csv>2010/qbsh/friedman/ | + | <csv>2010/qbsh/friedman/QbshTask1aSimpleByGroup.friedman.tukeyKramerHSD.csv</csv> |
− | [[Image: | + | [[Image:2010QbshTask1aSimpleByGroup.friedman.tukeyKramerHSD.png|500px]] |
MRR Method: | MRR Method: | ||
− | <csv>2010/qbsh/friedman/ | + | <csv>2010/qbsh/friedman/QbshTask1aMrrByGroup.friedman.tukeyKramerHSD.csv</csv> |
− | [[Image: | + | [[Image:2010QbshTask1aMrrByGroup.friedman.tukeyKramerHSD.png|500px]] |
=====Task 1a Summary Results by Query Group===== | =====Task 1a Summary Results by Query Group===== | ||
Line 62: | Line 79: | ||
=====Task 1b Friedman's Test for Significant Differences===== | =====Task 1b Friedman's Test for Significant Differences===== | ||
− | The Friedman test was run in MATLAB against the QBSH Task | + | The Friedman test was run in MATLAB against the QBSH Task 1b Simple/MRR data over the 106 ground truth song groups. |
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05); | Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05); | ||
Simple Hit/Miss Count: | Simple Hit/Miss Count: | ||
− | <csv>2010/qbsh/friedman/ | + | <csv>2010/qbsh/friedman/QbshTask1bSimpleByGroup.friedman.tukeyKramerHSD.csv</csv> |
− | [[Image: | + | [[Image:2010QbshTask1bSimpleByGroup.friedman.tukeyKramerHSD.png|500px]] |
MRR Method: | MRR Method: | ||
− | <csv>2010/qbsh/friedman/ | + | <csv>2010/qbsh/friedman/QbshTask1bMrrByGroup.friedman.tukeyKramerHSD.csv</csv> |
− | [[Image: | + | [[Image:2010QbshTask1bMrrByGroup.friedman.tukeyKramerHSD.png|500px]] |
=====Task 1b Summary Results by Query Group===== | =====Task 1b Summary Results by Query Group===== | ||
Simple Hit/Miss Count | Simple Hit/Miss Count | ||
Line 112: | Line 129: | ||
=====Task 2 Friedman's Test for Significant Differences===== | =====Task 2 Friedman's Test for Significant Differences===== | ||
− | The Friedman test was run in MATLAB against the QBSH Task | + | The Friedman test was run in MATLAB against the QBSH Task 2 data over the 48 ground truth song groups. |
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05); | Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05); | ||
− | <csv>2010/qbsh/friedman/ | + | <csv>2010/qbsh/friedman/QbshTask2Group.friedman.tukeyKramerHSD.csv</csv> |
− | [[Image: | + | [[Image:2010QbshTask2Group.friedman.tukeyKramerHSD.png|500px]] |
Line 128: | Line 145: | ||
===Runtime Results=== | ===Runtime Results=== | ||
− | <csv>2010/qbsh/ | + | <csv>2010/qbsh/QbshRunTime.csv</csv> |
[[Category: Results]] | [[Category: Results]] |
Latest revision as of 14:46, 3 August 2010
Contents
- 1 Introduction
- 2 General Legend
Introduction
These are the results for the 2008 running of the Query-by-Singing/Humming task. For background information about this task set please refer to the 2010:Query by Singing/Humming page.
Task Descriptions
Task 1 Goto Task 1 Results: The first subtask is the same as last year. In this subtask, submitted systems take a sung query as input and return a list of songs from the test database. Mean reciprocal rank (MRR) of the ground truth, as well as the simple hit(1)/miss(0) counting, is calculated over the top 10 returns. Two data sets are used:
- Jang's Dataset Results Roger Jang's MIR-QBSH corpus with 48 songs as ground truth + 2000 Essen Collection MIDI noise files. See ESAC Data Homepage for more information about the Essen Collection. The queries consists of 4431 humming. All queries are from the beginning of references
- ThinkIT's Dataset Results IOACAS corpus 1 data set with 106 songs as ground truth + 2000 Essen Collection MIDI noise files. See ESAC Data Homepage for more information about the Essen Collection. The queries consists of 355 humming. There are no "singing from beginning" gurantee.
- IOACAS's 2nd Dataset Results IOACAS corpus 2 data set with 192 songs as ground truth + 2000 Essen Collection MIDI noise files. See ESAC Data Homepage for more information about the Essen Collection. The queries consists of 404 humming. There are no "singing from beginning" gurantee.
Task 2 Goto Task 2 Results: The second subtask is the query against other humming. In the second subtask, Roger Jang's MIR-QBSH corpus has been divided into two groups (2040 as queries and 2391 as database). The query is performed against the other humming database and the top 10 closed are returned. The score is simple count of how many returns belong to the same ground truth song.
General Legend
General Legend
Sub code | Submission name | Abstract | Contributors |
---|---|---|---|
HAFR1 | QBH Simbals | Pierre Hanna, Julien Allali, Pascal Ferraro, Matthias Robine | |
JY1 | The programs of QBSH -beginning | Jingzhou Yang | |
JY2 | The programs of QBSH -anywhere | Jingzhou Yang | |
YF1 | Yeh, Fang -beginning | Tzu-chun Yeh, Yi-fan Fang | |
YF2 | Yeh, Fang -anywhere | Tzu-chun Yeh, Yi-fan Fang |
Task 1 Results
Task 1a, Jang's dataset Results
Task 1a Overall Results
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
Simple Count | 0.771 | 0.967 | 0.956 | 0.947 | 0.912 |
MRR | 0.665 | 0.947 | 0.926 | 0.915 | 0.871 |
Total Count | 4408 | 4431 | 4431 | 4431 | 4431 |
Task 1a Friedman's Test for Significant Differences
The Friedman test was run in MATLAB against the QBSH Task 1a Simple/MRR data over the 48 ground truth song groups. Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
Simple Hit/Miss Count:
TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
---|---|---|---|---|---|
JY1 | JY2 | -0.1065 | 0.7292 | 1.5649 | FALSE |
JY1 | YF1 | 0.1331 | 0.9688 | 1.8044 | TRUE |
JY1 | YF2 | 1.2060 | 2.0417 | 2.8774 | TRUE |
JY1 | HAFR1 | 2.2997 | 3.1354 | 3.9711 | TRUE |
JY2 | YF1 | -0.5961 | 0.2396 | 1.0753 | FALSE |
JY2 | YF2 | 0.4768 | 1.3125 | 2.1482 | TRUE |
JY2 | HAFR1 | 1.5706 | 2.4063 | 3.2419 | TRUE |
YF1 | YF2 | 0.2372 | 1.0729 | 1.9086 | TRUE |
YF1 | HAFR1 | 1.3310 | 2.1667 | 3.0024 | TRUE |
YF2 | HAFR1 | 0.2581 | 1.0938 | 1.9294 | TRUE |
MRR Method:
TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
---|---|---|---|---|---|
JY1 | JY2 | 0.2666 | 1.1354 | 2.0043 | TRUE |
JY1 | YF2 | 0.3916 | 1.2604 | 2.1293 | TRUE |
JY1 | YF1 | 1.5374 | 2.4063 | 3.2751 | TRUE |
JY1 | HAFR1 | 2.6624 | 3.5313 | 4.4001 | TRUE |
JY2 | YF2 | -0.7438 | 0.1250 | 0.9938 | FALSE |
JY2 | YF1 | 0.4020 | 1.2708 | 2.1397 | TRUE |
JY2 | HAFR1 | 1.5270 | 2.3958 | 3.2647 | TRUE |
YF2 | YF1 | 0.2770 | 1.1458 | 2.0147 | TRUE |
YF2 | HAFR1 | 1.4020 | 2.2708 | 3.1397 | TRUE |
YF1 | HAFR1 | 0.2562 | 1.1250 | 1.9938 | TRUE |
Task 1a Summary Results by Query Group
Simple Hit/Miss Count
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
1 | 0.947 | 0.947 | 0.947 | 0.947 | 0.895 |
2 | 0.357 | 0.786 | 0.786 | 0.714 | 0.643 |
3 | 0.636 | 0.727 | 0.636 | 0.636 | 0.636 |
4 | 0.733 | 0.867 | 0.800 | 0.800 | 0.800 |
5 | 0.867 | 0.933 | 0.933 | 0.933 | 0.800 |
6 | 0.750 | 0.917 | 0.917 | 0.833 | 0.833 |
7 | 0.533 | 0.933 | 0.867 | 0.867 | 0.867 |
8 | 0.667 | 0.933 | 0.933 | 0.867 | 0.933 |
9 | 0.750 | 0.917 | 0.917 | 0.917 | 0.917 |
10 | 0.895 | 0.895 | 0.842 | 0.684 | 0.842 |
11 | 0.802 | 0.969 | 0.938 | 0.948 | 0.906 |
12 | 0.915 | 0.968 | 0.961 | 0.968 | 0.961 |
13 | 0.881 | 0.981 | 0.975 | 0.981 | 0.938 |
14 | 0.918 | 0.975 | 0.975 | 0.987 | 0.956 |
15 | 0.741 | 0.963 | 0.963 | 0.963 | 0.926 |
16 | 0.930 | 0.981 | 0.969 | 0.950 | 0.925 |
17 | 0.728 | 0.987 | 0.974 | 0.974 | 0.882 |
18 | 0.750 | 0.982 | 0.994 | 0.976 | 0.951 |
19 | 0.892 | 0.975 | 0.968 | 0.975 | 0.943 |
20 | 0.467 | 0.988 | 0.976 | 1.000 | 0.982 |
21 | 0.318 | 0.879 | 0.848 | 0.848 | 0.788 |
22 | 0.953 | 0.994 | 0.983 | 0.977 | 0.954 |
23 | 0.852 | 1.000 | 0.984 | 0.984 | 0.984 |
24 | 0.583 | 0.884 | 0.843 | 0.851 | 0.810 |
25 | 0.574 | 0.935 | 0.813 | 0.740 | 0.569 |
26 | 0.654 | 0.981 | 0.962 | 0.962 | 0.962 |
27 | 0.765 | 0.988 | 0.953 | 0.953 | 0.965 |
28 | 0.495 | 0.967 | 0.912 | 0.879 | 0.725 |
29 | 0.573 | 0.987 | 1.000 | 0.987 | 0.980 |
30 | 0.944 | 0.993 | 0.986 | 0.986 | 0.938 |
31 | 0.935 | 0.979 | 0.986 | 0.993 | 0.986 |
32 | 0.796 | 0.956 | 0.949 | 0.956 | 0.912 |
33 | 0.496 | 0.957 | 0.957 | 0.931 | 0.862 |
34 | 0.635 | 0.971 | 0.964 | 0.927 | 0.891 |
35 | 0.757 | 0.966 | 0.946 | 0.960 | 0.886 |
36 | 0.907 | 0.953 | 0.953 | 0.930 | 0.930 |
37 | 0.879 | 0.955 | 0.939 | 0.939 | 0.894 |
38 | 0.781 | 0.930 | 0.947 | 0.947 | 0.947 |
39 | 0.822 | 0.980 | 0.980 | 0.932 | 0.905 |
40 | 0.437 | 0.944 | 0.958 | 0.958 | 0.901 |
41 | 0.896 | 0.976 | 0.976 | 0.976 | 0.952 |
42 | 0.857 | 0.946 | 0.967 | 0.946 | 0.957 |
43 | 0.902 | 0.967 | 0.976 | 0.951 | 0.943 |
44 | 0.875 | 0.975 | 0.975 | 0.963 | 0.925 |
45 | 0.828 | 0.970 | 0.970 | 0.939 | 0.899 |
46 | 0.802 | 0.978 | 0.967 | 0.957 | 0.946 |
47 | 0.931 | 1.000 | 0.966 | 1.000 | 0.966 |
48 | 0.811 | 1.000 | 0.962 | 0.962 | 0.981 |
MRR Method
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
1 | 0.877 | 0.886 | 0.882 | 0.848 | 0.874 |
2 | 0.357 | 0.786 | 0.786 | 0.560 | 0.653 |
3 | 0.636 | 0.682 | 0.636 | 0.636 | 0.636 |
4 | 0.689 | 0.807 | 0.800 | 0.800 | 0.800 |
5 | 0.722 | 0.889 | 0.833 | 0.800 | 0.844 |
6 | 0.676 | 0.917 | 0.917 | 0.792 | 0.833 |
7 | 0.533 | 0.880 | 0.867 | 0.867 | 0.867 |
8 | 0.589 | 0.889 | 0.933 | 0.933 | 0.807 |
9 | 0.667 | 0.917 | 0.917 | 0.833 | 0.875 |
10 | 0.855 | 0.860 | 0.716 | 0.842 | 0.613 |
11 | 0.717 | 0.946 | 0.932 | 0.883 | 0.928 |
12 | 0.787 | 0.959 | 0.952 | 0.937 | 0.958 |
13 | 0.739 | 0.927 | 0.908 | 0.915 | 0.934 |
14 | 0.813 | 0.965 | 0.954 | 0.876 | 0.954 |
15 | 0.662 | 0.963 | 0.963 | 0.907 | 0.926 |
16 | 0.894 | 0.962 | 0.942 | 0.905 | 0.915 |
17 | 0.555 | 0.982 | 0.961 | 0.760 | 0.895 |
18 | 0.641 | 0.982 | 0.986 | 0.938 | 0.955 |
19 | 0.805 | 0.969 | 0.965 | 0.931 | 0.966 |
20 | 0.301 | 0.979 | 0.968 | 0.955 | 0.984 |
21 | 0.242 | 0.838 | 0.778 | 0.667 | 0.723 |
22 | 0.912 | 0.989 | 0.979 | 0.954 | 0.959 |
23 | 0.707 | 0.992 | 0.973 | 0.957 | 0.970 |
24 | 0.489 | 0.809 | 0.775 | 0.752 | 0.790 |
25 | 0.396 | 0.824 | 0.739 | 0.449 | 0.610 |
26 | 0.568 | 0.953 | 0.919 | 0.942 | 0.952 |
27 | 0.583 | 0.980 | 0.942 | 0.934 | 0.941 |
28 | 0.382 | 0.945 | 0.766 | 0.606 | 0.793 |
29 | 0.434 | 0.978 | 0.983 | 0.954 | 0.971 |
30 | 0.876 | 0.993 | 0.957 | 0.901 | 0.971 |
31 | 0.838 | 0.972 | 0.976 | 0.974 | 0.993 |
32 | 0.643 | 0.946 | 0.918 | 0.898 | 0.951 |
33 | 0.363 | 0.938 | 0.923 | 0.812 | 0.882 |
34 | 0.530 | 0.955 | 0.938 | 0.842 | 0.898 |
35 | 0.673 | 0.945 | 0.912 | 0.845 | 0.941 |
36 | 0.841 | 0.953 | 0.919 | 0.930 | 0.930 |
37 | 0.798 | 0.934 | 0.899 | 0.837 | 0.905 |
38 | 0.635 | 0.890 | 0.885 | 0.911 | 0.922 |
39 | 0.695 | 0.963 | 0.959 | 0.854 | 0.903 |
40 | 0.312 | 0.927 | 0.926 | 0.851 | 0.899 |
41 | 0.817 | 0.966 | 0.937 | 0.924 | 0.954 |
42 | 0.756 | 0.940 | 0.914 | 0.893 | 0.915 |
43 | 0.800 | 0.941 | 0.952 | 0.863 | 0.920 |
44 | 0.836 | 0.975 | 0.964 | 0.916 | 0.939 |
45 | 0.772 | 0.944 | 0.947 | 0.868 | 0.913 |
46 | 0.744 | 0.952 | 0.922 | 0.923 | 0.943 |
47 | 0.826 | 0.972 | 0.943 | 0.940 | 0.957 |
48 | 0.697 | 0.970 | 0.953 | 0.920 | 0.937 |
Task 1a Summary Results by Query
Simple Hit/Miss Counting [1]
MRR Method [2]
Task 1b, ThinkIT's dataset Results
Task 1b Overall Results
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
Simple Count | 0.806 | 0.434 | 0.49 | 0.445 | 0.904 |
MRR | 0.704 | 0.416 | 0.469 | 0.423 | 0.844 |
Total Count | 355 | 355 | 355 | 355 | 355 |
Task 1b Friedman's Test for Significant Differences
The Friedman test was run in MATLAB against the QBSH Task 1b Simple/MRR data over the 106 ground truth song groups. Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
Simple Hit/Miss Count:
TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
---|---|---|---|---|---|
YF2 | HAFR1 | -0.0077 | 0.4481 | 0.9039 | FALSE |
YF2 | JY2 | 1.0536 | 1.5094 | 1.9653 | TRUE |
YF2 | YF1 | 1.2376 | 1.6934 | 2.1492 | TRUE |
YF2 | JY1 | 1.2706 | 1.7264 | 2.1822 | TRUE |
HAFR1 | JY2 | 0.6055 | 1.0613 | 1.5171 | TRUE |
HAFR1 | YF1 | 0.7895 | 1.2453 | 1.7011 | TRUE |
HAFR1 | JY1 | 0.8225 | 1.2783 | 1.7341 | TRUE |
JY2 | YF1 | -0.2719 | 0.1840 | 0.6398 | FALSE |
JY2 | JY1 | -0.2388 | 0.2170 | 0.6728 | FALSE |
YF1 | JY1 | -0.4228 | 0.0330 | 0.4888 | FALSE |
MRR Method:
TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
---|---|---|---|---|---|
YF2 | HAFR1 | 0.1253 | 0.6085 | 1.0916 | TRUE |
YF2 | JY2 | 1.0168 | 1.5000 | 1.9832 | TRUE |
YF2 | YF1 | 1.1819 | 1.6651 | 2.1482 | TRUE |
YF2 | JY1 | 1.1914 | 1.6745 | 2.1577 | TRUE |
HAFR1 | JY2 | 0.4084 | 0.8915 | 1.3747 | TRUE |
HAFR1 | YF1 | 0.5735 | 1.0566 | 1.5398 | TRUE |
HAFR1 | JY1 | 0.5829 | 1.0660 | 1.5492 | TRUE |
JY2 | YF1 | -0.3181 | 0.1651 | 0.6482 | FALSE |
JY2 | JY1 | -0.3086 | 0.1745 | 0.6577 | FALSE |
YF1 | JY1 | -0.4737 | 0.0094 | 0.4926 | FALSE |
Task 1b Summary Results by Query Group
Simple Hit/Miss Count
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
1 | 0.909 | 0.364 | 0.364 | 0.636 | 1.000 |
2 | 0.800 | 0.600 | 0.600 | 0.600 | 0.800 |
3 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
4 | 1.000 | 0.000 | 0.500 | 0.500 | 1.000 |
5 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
6 | 0.833 | 0.000 | 0.000 | 0.000 | 1.000 |
7 | 0.833 | 1.000 | 1.000 | 1.000 | 1.000 |
8 | 0.333 | 0.333 | 0.333 | 0.333 | 0.667 |
9 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
10 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
11 | 0.500 | 0.000 | 0.000 | 0.000 | 1.000 |
12 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
13 | 0.600 | 0.000 | 0.000 | 0.200 | 0.600 |
14 | 0.500 | 0.000 | 1.000 | 0.000 | 1.000 |
15 | 0.000 | 0.000 | 0.500 | 0.000 | 0.500 |
16 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
17 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
18 | 0.500 | 0.500 | 0.500 | 0.500 | 1.000 |
19 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
20 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
21 | 0.500 | 0.500 | 0.000 | 0.000 | 0.500 |
22 | 0.889 | 0.444 | 0.667 | 0.444 | 0.889 |
23 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
24 | 1.000 | 0.000 | 0.500 | 0.000 | 1.000 |
25 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
26 | 0.909 | 0.636 | 0.636 | 0.636 | 0.909 |
27 | 0.000 | 0.500 | 0.250 | 0.500 | 1.000 |
28 | 0.750 | 0.500 | 0.500 | 0.500 | 1.000 |
29 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
30 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
31 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
32 | 0.857 | 0.000 | 0.000 | 0.000 | 1.000 |
33 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
34 | 0.000 | 0.500 | 0.500 | 0.500 | 0.500 |
35 | 1.000 | 0.000 | 1.000 | 1.000 | 1.000 |
36 | 0.600 | 0.000 | 0.000 | 0.000 | 0.800 |
37 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
38 | 1.000 | 0.500 | 1.000 | 0.500 | 1.000 |
39 | 1.000 | 0.429 | 0.429 | 0.429 | 1.000 |
40 | 0.500 | 1.000 | 1.000 | 1.000 | 1.000 |
41 | 0.750 | 0.125 | 0.125 | 0.125 | 0.875 |
42 | 0.500 | 0.667 | 0.667 | 0.667 | 0.917 |
43 | 0.556 | 0.778 | 0.667 | 0.667 | 0.778 |
44 | 1.000 | 0.556 | 0.556 | 0.556 | 1.000 |
45 | 0.667 | 1.000 | 1.000 | 1.000 | 1.000 |
46 | 0.750 | 0.500 | 0.500 | 0.500 | 0.750 |
47 | 1.000 | 0.750 | 0.750 | 0.750 | 1.000 |
48 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
49 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
50 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
51 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
52 | 0.750 | 0.250 | 0.750 | 0.250 | 1.000 |
53 | 0.833 | 0.333 | 0.333 | 0.333 | 1.000 |
54 | 1.000 | 0.833 | 0.333 | 0.667 | 1.000 |
55 | 0.750 | 0.000 | 0.000 | 0.000 | 1.000 |
56 | 0.500 | 0.500 | 0.500 | 0.500 | 0.500 |
57 | 0.400 | 1.000 | 1.000 | 1.000 | 1.000 |
58 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
59 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
60 | 0.500 | 1.000 | 1.000 | 1.000 | 1.000 |
61 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
62 | 1.000 | 0.333 | 0.333 | 0.333 | 1.000 |
63 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
64 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
65 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
66 | 1.000 | 0.500 | 0.750 | 0.500 | 0.750 |
67 | 0.667 | 0.000 | 0.000 | 0.000 | 1.000 |
68 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
69 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
70 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
71 | 1.000 | 0.000 | 0.000 | 0.000 | 0.667 |
72 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
73 | 0.500 | 1.000 | 1.000 | 1.000 | 1.000 |
74 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
75 | 0.667 | 0.333 | 0.333 | 0.333 | 0.667 |
76 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
77 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
78 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
79 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
80 | 1.000 | 0.333 | 0.333 | 0.333 | 1.000 |
81 | 1.000 | 0.333 | 0.333 | 0.333 | 0.667 |
82 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
83 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
84 | 0.500 | 0.250 | 0.000 | 0.000 | 0.250 |
85 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
86 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
87 | 0.333 | 0.000 | 0.000 | 0.000 | 1.000 |
88 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
89 | 1.000 | 0.429 | 0.429 | 0.571 | 1.000 |
90 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
91 | 0.500 | 0.000 | 0.000 | 0.000 | 1.000 |
92 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
93 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
94 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
95 | 0.000 | 0.000 | 1.000 | 0.000 | 1.000 |
96 | 1.000 | 1.000 | 1.000 | 1.000 | 0.000 |
97 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
98 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
99 | 1.000 | 0.750 | 0.750 | 0.750 | 1.000 |
100 | 1.000 | 0.333 | 0.333 | 0.333 | 1.000 |
101 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
102 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
103 | 0.750 | 0.375 | 0.625 | 0.375 | 0.875 |
104 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
105 | 1.000 | 0.000 | 0.000 | 1.000 | 0.000 |
106 | 0.000 | 0.000 | 0.000 | 0.000 | 0.667 |
MRR Method
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
1 | 0.909 | 0.364 | 0.364 | 0.450 | 0.955 |
2 | 0.550 | 0.600 | 0.600 | 0.600 | 0.800 |
3 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
4 | 0.500 | 0.000 | 0.500 | 0.083 | 0.667 |
5 | 0.000 | 0.000 | 0.000 | 0.000 | 0.250 |
6 | 0.833 | 0.000 | 0.000 | 0.000 | 0.792 |
7 | 0.833 | 1.000 | 1.000 | 1.000 | 1.000 |
8 | 0.333 | 0.333 | 0.167 | 0.333 | 0.500 |
9 | 0.850 | 0.000 | 1.000 | 0.000 | 1.000 |
10 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
11 | 0.167 | 0.000 | 0.000 | 0.000 | 0.750 |
12 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
13 | 0.295 | 0.000 | 0.000 | 0.100 | 0.600 |
14 | 0.500 | 0.000 | 1.000 | 0.000 | 0.667 |
15 | 0.000 | 0.000 | 0.500 | 0.000 | 0.500 |
16 | 1.000 | 1.000 | 0.813 | 1.000 | 0.667 |
17 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
18 | 0.500 | 0.500 | 0.500 | 0.500 | 1.000 |
19 | 1.000 | 0.000 | 0.000 | 0.000 | 0.667 |
20 | 0.571 | 0.000 | 0.000 | 0.000 | 0.000 |
21 | 0.500 | 0.125 | 0.000 | 0.000 | 0.250 |
22 | 0.648 | 0.444 | 0.667 | 0.444 | 0.806 |
23 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
24 | 1.000 | 0.000 | 0.500 | 0.000 | 1.000 |
25 | 0.583 | 0.500 | 0.500 | 0.500 | 1.000 |
26 | 0.818 | 0.636 | 0.568 | 0.564 | 0.848 |
27 | 0.000 | 0.292 | 0.250 | 0.300 | 1.000 |
28 | 0.525 | 0.500 | 0.500 | 0.500 | 0.875 |
29 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
30 | 1.000 | 1.000 | 1.000 | 0.800 | 1.000 |
31 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
32 | 0.786 | 0.000 | 0.000 | 0.000 | 1.000 |
33 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
34 | 0.000 | 0.500 | 0.500 | 0.125 | 0.125 |
35 | 1.000 | 0.000 | 1.000 | 0.100 | 1.000 |
36 | 0.600 | 0.000 | 0.000 | 0.000 | 0.800 |
37 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
38 | 1.000 | 0.500 | 1.000 | 0.500 | 1.000 |
39 | 0.702 | 0.429 | 0.429 | 0.429 | 1.000 |
40 | 0.500 | 1.000 | 1.000 | 1.000 | 1.000 |
41 | 0.688 | 0.125 | 0.125 | 0.125 | 0.729 |
42 | 0.417 | 0.667 | 0.667 | 0.667 | 0.861 |
43 | 0.457 | 0.678 | 0.611 | 0.667 | 0.778 |
44 | 0.849 | 0.556 | 0.556 | 0.556 | 1.000 |
45 | 0.667 | 1.000 | 1.000 | 1.000 | 1.000 |
46 | 0.500 | 0.375 | 0.067 | 0.500 | 0.500 |
47 | 1.000 | 0.750 | 0.750 | 0.750 | 1.000 |
48 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
49 | 0.500 | 1.000 | 1.000 | 1.000 | 1.000 |
50 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
51 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
52 | 0.750 | 0.250 | 0.750 | 0.250 | 1.000 |
53 | 0.833 | 0.333 | 0.333 | 0.333 | 1.000 |
54 | 1.000 | 0.583 | 0.139 | 0.667 | 1.000 |
55 | 0.363 | 0.000 | 0.000 | 0.000 | 1.000 |
56 | 0.500 | 0.500 | 0.500 | 0.500 | 0.500 |
57 | 0.229 | 1.000 | 1.000 | 1.000 | 1.000 |
58 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
59 | 0.464 | 0.000 | 0.000 | 0.000 | 1.000 |
60 | 0.500 | 1.000 | 1.000 | 1.000 | 1.000 |
61 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
62 | 0.833 | 0.167 | 0.111 | 0.333 | 1.000 |
63 | 1.000 | 1.000 | 1.000 | 1.000 | 0.750 |
64 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
65 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
66 | 1.000 | 0.500 | 0.750 | 0.500 | 0.750 |
67 | 0.370 | 0.000 | 0.000 | 0.000 | 1.000 |
68 | 0.625 | 1.000 | 1.000 | 1.000 | 1.000 |
69 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
70 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
71 | 1.000 | 0.000 | 0.000 | 0.000 | 0.667 |
72 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
73 | 0.500 | 1.000 | 1.000 | 1.000 | 1.000 |
74 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
75 | 0.667 | 0.333 | 0.333 | 0.333 | 0.381 |
76 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
77 | 0.777 | 1.000 | 1.000 | 1.000 | 1.000 |
78 | 0.200 | 1.000 | 0.250 | 1.000 | 1.000 |
79 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
80 | 1.000 | 0.333 | 0.333 | 0.333 | 1.000 |
81 | 1.000 | 0.333 | 0.333 | 0.333 | 0.667 |
82 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
83 | 1.000 | 0.000 | 0.000 | 0.000 | 0.528 |
84 | 0.090 | 0.125 | 0.000 | 0.000 | 0.042 |
85 | 0.875 | 0.500 | 0.500 | 0.500 | 1.000 |
86 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
87 | 0.333 | 0.000 | 0.000 | 0.000 | 1.000 |
88 | 1.000 | 0.000 | 0.000 | 0.000 | 0.500 |
89 | 0.871 | 0.304 | 0.429 | 0.571 | 0.802 |
90 | 0.292 | 0.000 | 1.000 | 0.000 | 1.000 |
91 | 0.500 | 0.000 | 0.000 | 0.000 | 1.000 |
92 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
93 | 1.000 | 0.500 | 0.500 | 0.500 | 1.000 |
94 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
95 | 0.000 | 0.000 | 1.000 | 0.000 | 1.000 |
96 | 1.000 | 1.000 | 0.333 | 0.500 | 0.000 |
97 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
98 | 0.333 | 0.000 | 0.000 | 0.000 | 1.000 |
99 | 0.778 | 0.750 | 0.750 | 0.750 | 0.833 |
100 | 1.000 | 0.333 | 0.333 | 0.333 | 1.000 |
101 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
102 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
103 | 0.583 | 0.375 | 0.625 | 0.375 | 0.708 |
104 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
105 | 0.143 | 0.000 | 0.000 | 1.000 | 0.000 |
106 | 0.000 | 0.000 | 0.000 | 0.000 | 0.333 |
Task 1b Summary Results by Query
Simple Hit/Miss Counting [3]
MRR Method [4]
Task 1c, IOACAS2's dataset Results
As argued by Jang, there are some abnormal in the IOACAS2 data set. Therefore, we just provide the raw result without any further analysis.
Task 1c Summary Results by Query Group
Simple Hit/Miss Count
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
1 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
2 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
3 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
4 | 0.333 | 0.000 | 0.000 | 0.000 | 0.000 |
5 | 0.364 | 0.000 | 0.091 | 0.273 | 0.364 |
6 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
7 | 0.500 | 0.000 | 0.000 | 0.500 | 1.000 |
8 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
9 | 1.000 | 0.000 | 0.000 | 1.000 | 0.000 |
10 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000 |
11 | 0.750 | 0.000 | 0.000 | 0.000 | 1.000 |
12 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
13 | 0.429 | 0.000 | 0.000 | 0.286 | 0.143 |
14 | 0.400 | 0.000 | 0.000 | 0.200 | 0.400 |
15 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
16 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000 |
17 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
18 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
19 | 0.000 | 0.000 | 0.000 | 0.500 | 0.000 |
20 | 0.500 | 0.000 | 0.000 | 0.500 | 0.250 |
21 | 1.000 | 0.000 | 0.500 | 0.000 | 0.000 |
22 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
23 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
24 | 0.143 | 0.000 | 0.000 | 0.000 | 0.571 |
25 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
26 | 1.000 | 0.000 | 0.000 | 0.000 | 0.250 |
27 | 0.000 | 1.000 | 0.000 | 0.000 | 0.000 |
28 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
29 | 0.625 | 0.000 | 0.000 | 0.375 | 0.375 |
30 | 1.000 | 0.000 | 1.000 | 0.000 | 0.000 |
31 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
32 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
33 | 0.333 | 0.000 | 0.000 | 0.333 | 0.333 |
34 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
35 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
36 | 1.000 | 1.000 | 0.500 | 0.500 | 0.000 |
37 | 0.889 | 0.000 | 0.000 | 0.000 | 0.444 |
38 | 0.500 | 0.000 | 0.000 | 0.500 | 0.500 |
39 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
40 | 1.000 | 0.500 | 0.500 | 0.500 | 0.500 |
41 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000 |
42 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
43 | 1.000 | 0.000 | 0.000 | 0.333 | 0.000 |
44 | 1.000 | 0.000 | 0.000 | 0.500 | 0.500 |
45 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
46 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
47 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
48 | 0.000 | 0.000 | 1.000 | 0.000 | 1.000 |
49 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
50 | 0.875 | 0.000 | 0.250 | 0.250 | 0.125 |
51 | 0.750 | 0.000 | 0.000 | 0.000 | 0.250 |
52 | 0.667 | 0.333 | 0.667 | 0.333 | 0.667 |
53 | 0.500 | 0.000 | 0.000 | 0.000 | 0.500 |
54 | 0.500 | 0.000 | 0.000 | 0.000 | 0.500 |
55 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
56 | 0.000 | 0.000 | 0.000 | 0.667 | 0.667 |
57 | 1.000 | 0.000 | 0.000 | 0.000 | 0.333 |
58 | 0.286 | 0.286 | 0.143 | 0.000 | 0.000 |
59 | 0.000 | 0.000 | 0.000 | 1.000 | 0.000 |
60 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
61 | 0.500 | 0.000 | 0.000 | 0.000 | 0.500 |
62 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
63 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
64 | 0.333 | 0.000 | 0.000 | 0.333 | 0.556 |
65 | 0.000 | 0.000 | 0.000 | 1.000 | 0.000 |
66 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
67 | 0.500 | 0.000 | 0.000 | 0.000 | 0.000 |
68 | 0.500 | 0.700 | 0.600 | 0.500 | 0.600 |
69 | 0.333 | 0.000 | 0.000 | 0.000 | 0.333 |
70 | 0.300 | 0.000 | 0.500 | 0.000 | 0.700 |
71 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
72 | 0.333 | 0.500 | 0.000 | 0.500 | 0.333 |
73 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
74 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
75 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
76 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
77 | 1.000 | 1.000 | 0.000 | 0.000 | 0.000 |
78 | 0.167 | 0.000 | 0.000 | 0.833 | 0.333 |
79 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
80 | 0.846 | 0.462 | 0.231 | 0.615 | 0.692 |
81 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
82 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
83 | 1.000 | 0.000 | 0.000 | 1.000 | 0.857 |
84 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
85 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
86 | 0.250 | 0.000 | 0.000 | 0.000 | 1.000 |
87 | 1.000 | 0.000 | 1.000 | 1.000 | 1.000 |
88 | 0.750 | 0.000 | 0.000 | 0.250 | 0.750 |
89 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
90 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
91 | 1.000 | 0.000 | 0.500 | 0.500 | 0.500 |
92 | 1.000 | 0.000 | 0.000 | 0.500 | 1.000 |
93 | 0.800 | 0.000 | 0.400 | 0.400 | 0.600 |
94 | 0.000 | 0.000 | 0.000 | 1.000 | 0.000 |
95 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
96 | 1.000 | 0.000 | 0.000 | 0.667 | 0.667 |
97 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
98 | 0.500 | 0.500 | 0.500 | 1.000 | 1.000 |
99 | 0.000 | 1.000 | 0.000 | 1.000 | 1.000 |
100 | 1.000 | 0.000 | 0.000 | 0.000 | 0.500 |
101 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
102 | 0.500 | 0.625 | 0.625 | 0.625 | 0.500 |
103 | 0.000 | 0.000 | 1.000 | 0.000 | 0.000 |
104 | 1.000 | 0.000 | 0.000 | 1.000 | 0.000 |
105 | 0.000 | 0.000 | 1.000 | 0.000 | 1.000 |
106 | 0.000 | 0.000 | 0.500 | 0.000 | 0.000 |
107 | 1.000 | 0.000 | 0.500 | 0.000 | 1.000 |
108 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
109 | 1.000 | 1.000 | 0.500 | 1.000 | 0.500 |
110 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
111 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
112 | 0.500 | 0.000 | 0.000 | 0.000 | 0.000 |
113 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
114 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
115 | 0.500 | 1.000 | 0.000 | 1.000 | 0.000 |
116 | 0.500 | 0.000 | 0.000 | 0.500 | 0.000 |
117 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
118 | 1.000 | 1.000 | 1.000 | 1.000 | 0.000 |
119 | 0.400 | 0.000 | 0.400 | 0.200 | 0.200 |
120 | 1.000 | 0.000 | 0.000 | 1.000 | 0.000 |
121 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
122 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000 |
123 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
124 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
125 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
126 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
127 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
128 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
129 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
130 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
131 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
132 | 0.500 | 0.000 | 0.000 | 0.000 | 0.000 |
133 | 0.000 | 1.000 | 1.000 | 1.000 | 1.000 |
134 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
135 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
136 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
137 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
138 | 1.000 | 0.000 | 0.667 | 0.000 | 1.000 |
139 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
140 | 1.000 | 0.000 | 0.000 | 1.000 | 0.000 |
141 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000 |
142 | 1.000 | 0.000 | 0.250 | 0.000 | 0.500 |
143 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
144 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
145 | 1.000 | 0.333 | 0.000 | 0.333 | 0.333 |
146 | 0.000 | 0.500 | 0.000 | 0.000 | 0.000 |
147 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
148 | 0.500 | 0.500 | 0.500 | 0.500 | 1.000 |
149 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000 |
150 | 1.000 | 0.000 | 0.500 | 0.500 | 0.500 |
151 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
152 | 1.000 | 0.333 | 0.333 | 0.333 | 0.333 |
153 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
154 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
155 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
156 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000 |
157 | 1.000 | 1.000 | 0.000 | 1.000 | 1.000 |
158 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
159 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
160 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
161 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
162 | 0.000 | 1.000 | 1.000 | 1.000 | 0.000 |
163 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
164 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
165 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
166 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
167 | 1.000 | 1.000 | 0.000 | 1.000 | 1.000 |
168 | 0.000 | 1.000 | 1.000 | 1.000 | 1.000 |
169 | 1.000 | 0.000 | 1.000 | 1.000 | 1.000 |
170 | 1.000 | 1.000 | 0.000 | 1.000 | 1.000 |
171 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
172 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
173 | 1.000 | 0.000 | 1.000 | 1.000 | 0.000 |
174 | 1.000 | 1.000 | 1.000 | 1.000 | 0.000 |
175 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
176 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
177 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
178 | 1.000 | 0.000 | 0.000 | 1.000 | 0.500 |
179 | 1.000 | 0.000 | 0.000 | 1.000 | 0.000 |
180 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
181 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
182 | 1.000 | 0.000 | 1.000 | 0.000 | 0.000 |
183 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
184 | 0.000 | 0.000 | 1.000 | 0.000 | 1.000 |
185 | 1.000 | 0.000 | 1.000 | 1.000 | 1.000 |
186 | 0.333 | 0.000 | 0.333 | 0.000 | 0.667 |
187 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
188 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
189 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
190 | 1.000 | 0.000 | 0.000 | 0.500 | 1.000 |
191 | 1.000 | 1.000 | 1.000 | 1.000 | 0.000 |
192 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
MRR Method
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
1 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
2 | 0.583 | 0.000 | 0.000 | 0.000 | 0.000 |
3 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
4 | 0.333 | 0.000 | 0.000 | 0.000 | 0.000 |
5 | 0.195 | 0.000 | 0.013 | 0.132 | 0.197 |
6 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
7 | 0.500 | 0.000 | 0.000 | 0.500 | 1.000 |
8 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
9 | 1.000 | 0.000 | 0.000 | 1.000 | 0.000 |
10 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000 |
11 | 0.625 | 0.000 | 0.000 | 0.000 | 0.486 |
12 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
13 | 0.429 | 0.000 | 0.000 | 0.063 | 0.143 |
14 | 0.400 | 0.000 | 0.000 | 0.025 | 0.167 |
15 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
16 | 1.000 | 0.000 | 0.000 | 1.000 | 0.167 |
17 | 0.625 | 0.000 | 0.000 | 0.000 | 0.000 |
18 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
19 | 0.000 | 0.000 | 0.000 | 0.056 | 0.000 |
20 | 0.500 | 0.000 | 0.000 | 0.090 | 0.031 |
21 | 1.000 | 0.000 | 0.167 | 0.000 | 0.000 |
22 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
23 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
24 | 0.014 | 0.000 | 0.000 | 0.000 | 0.571 |
25 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
26 | 0.567 | 0.000 | 0.000 | 0.000 | 0.250 |
27 | 0.000 | 0.500 | 0.000 | 0.000 | 0.000 |
28 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
29 | 0.406 | 0.000 | 0.000 | 0.313 | 0.266 |
30 | 1.000 | 0.000 | 0.333 | 0.000 | 0.000 |
31 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
32 | 0.750 | 0.000 | 0.000 | 0.000 | 0.000 |
33 | 0.167 | 0.000 | 0.000 | 0.333 | 0.037 |
34 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
35 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
36 | 0.750 | 0.750 | 0.167 | 0.167 | 0.000 |
37 | 0.750 | 0.000 | 0.000 | 0.000 | 0.315 |
38 | 0.500 | 0.000 | 0.000 | 0.500 | 0.250 |
39 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
40 | 1.000 | 0.500 | 0.500 | 0.500 | 0.500 |
41 | 1.000 | 0.000 | 0.000 | 0.333 | 1.000 |
42 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
43 | 0.778 | 0.000 | 0.000 | 0.111 | 0.000 |
44 | 1.000 | 0.000 | 0.000 | 0.125 | 0.500 |
45 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
46 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
47 | 0.333 | 0.000 | 0.000 | 0.000 | 0.250 |
48 | 0.000 | 0.000 | 0.500 | 0.000 | 1.000 |
49 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
50 | 0.661 | 0.000 | 0.030 | 0.030 | 0.125 |
51 | 0.531 | 0.000 | 0.000 | 0.000 | 0.250 |
52 | 0.667 | 0.333 | 0.667 | 0.333 | 0.400 |
53 | 0.125 | 0.000 | 0.000 | 0.000 | 0.500 |
54 | 0.500 | 0.000 | 0.000 | 0.000 | 0.188 |
55 | 0.143 | 0.000 | 0.000 | 0.000 | 0.000 |
56 | 0.000 | 0.000 | 0.000 | 0.117 | 0.500 |
57 | 0.156 | 0.000 | 0.000 | 0.000 | 0.033 |
58 | 0.286 | 0.143 | 0.024 | 0.000 | 0.000 |
59 | 0.000 | 0.000 | 0.000 | 1.000 | 0.000 |
60 | 0.333 | 0.000 | 1.000 | 0.000 | 1.000 |
61 | 0.250 | 0.000 | 0.000 | 0.000 | 0.500 |
62 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
63 | 0.000 | 0.000 | 0.000 | 0.000 | 0.200 |
64 | 0.204 | 0.000 | 0.000 | 0.333 | 0.254 |
65 | 0.000 | 0.000 | 0.000 | 1.000 | 0.000 |
66 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
67 | 0.071 | 0.000 | 0.000 | 0.000 | 0.000 |
68 | 0.425 | 0.558 | 0.398 | 0.500 | 0.533 |
69 | 0.333 | 0.000 | 0.000 | 0.000 | 0.333 |
70 | 0.300 | 0.000 | 0.303 | 0.000 | 0.650 |
71 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
72 | 0.125 | 0.269 | 0.000 | 0.417 | 0.125 |
73 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
74 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
75 | 0.600 | 0.000 | 0.000 | 0.000 | 0.000 |
76 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
77 | 1.000 | 1.000 | 0.000 | 0.000 | 0.000 |
78 | 0.021 | 0.000 | 0.000 | 0.611 | 0.097 |
79 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
80 | 0.552 | 0.088 | 0.042 | 0.387 | 0.551 |
81 | 0.800 | 0.000 | 0.000 | 0.000 | 0.000 |
82 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
83 | 0.814 | 0.000 | 0.000 | 0.800 | 0.356 |
84 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
85 | 0.500 | 0.000 | 0.000 | 0.000 | 0.000 |
86 | 0.125 | 0.000 | 0.000 | 0.000 | 1.000 |
87 | 1.000 | 0.000 | 1.000 | 1.000 | 1.000 |
88 | 0.750 | 0.000 | 0.000 | 0.250 | 0.750 |
89 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 |
90 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
91 | 1.000 | 0.000 | 0.125 | 0.100 | 0.500 |
92 | 1.000 | 0.000 | 0.000 | 0.500 | 1.000 |
93 | 0.700 | 0.000 | 0.400 | 0.400 | 0.600 |
94 | 0.000 | 0.000 | 0.000 | 0.200 | 0.000 |
95 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
96 | 0.778 | 0.000 | 0.000 | 0.667 | 0.444 |
97 | 1.000 | 0.000 | 0.000 | 0.000 | 0.750 |
98 | 0.500 | 0.250 | 0.250 | 1.000 | 1.000 |
99 | 0.000 | 0.250 | 0.000 | 0.500 | 0.200 |
100 | 0.667 | 0.000 | 0.000 | 0.000 | 0.083 |
101 | 0.250 | 0.000 | 0.000 | 0.000 | 0.000 |
102 | 0.438 | 0.625 | 0.542 | 0.563 | 0.500 |
103 | 0.000 | 0.000 | 1.000 | 0.000 | 0.000 |
104 | 0.143 | 0.000 | 0.000 | 0.200 | 0.000 |
105 | 0.000 | 0.000 | 1.000 | 0.000 | 1.000 |
106 | 0.000 | 0.000 | 0.250 | 0.000 | 0.000 |
107 | 0.667 | 0.000 | 0.056 | 0.000 | 1.000 |
108 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
109 | 0.556 | 0.571 | 0.100 | 1.000 | 0.500 |
110 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
111 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
112 | 0.500 | 0.000 | 0.000 | 0.000 | 0.000 |
113 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
114 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
115 | 0.500 | 0.225 | 0.000 | 1.000 | 0.000 |
116 | 0.050 | 0.000 | 0.000 | 0.500 | 0.000 |
117 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
118 | 1.000 | 1.000 | 1.000 | 0.143 | 0.000 |
119 | 0.133 | 0.000 | 0.072 | 0.100 | 0.200 |
120 | 1.000 | 0.000 | 0.000 | 0.250 | 0.000 |
121 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
122 | 0.143 | 0.000 | 0.000 | 1.000 | 0.125 |
123 | 1.000 | 0.000 | 0.100 | 0.000 | 1.000 |
124 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
125 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
126 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
127 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
128 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
129 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
130 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
131 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
132 | 0.500 | 0.000 | 0.000 | 0.000 | 0.000 |
133 | 0.000 | 0.500 | 1.000 | 1.000 | 1.000 |
134 | 0.333 | 1.000 | 1.000 | 1.000 | 1.000 |
135 | 0.000 | 0.000 | 0.000 | 0.000 | 0.167 |
136 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
137 | 0.333 | 0.000 | 0.500 | 0.000 | 0.500 |
138 | 1.000 | 0.000 | 0.381 | 0.000 | 0.611 |
139 | 1.000 | 0.250 | 1.000 | 1.000 | 1.000 |
140 | 1.000 | 0.000 | 0.000 | 1.000 | 0.000 |
141 | 1.000 | 0.000 | 0.000 | 1.000 | 0.200 |
142 | 0.578 | 0.000 | 0.083 | 0.000 | 0.115 |
143 | 0.111 | 0.000 | 0.000 | 0.000 | 0.111 |
144 | 0.500 | 0.000 | 0.000 | 0.000 | 0.000 |
145 | 1.000 | 0.056 | 0.000 | 0.167 | 0.333 |
146 | 0.000 | 0.050 | 0.000 | 0.000 | 0.000 |
147 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
148 | 0.500 | 0.125 | 0.500 | 0.500 | 1.000 |
149 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000 |
150 | 0.625 | 0.000 | 0.071 | 0.500 | 0.167 |
151 | 1.000 | 0.000 | 0.000 | 0.000 | 0.500 |
152 | 0.833 | 0.083 | 0.067 | 0.056 | 0.333 |
153 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
154 | 0.000 | 0.000 | 0.000 | 0.000 | 0.500 |
155 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
156 | 0.333 | 0.000 | 0.000 | 1.000 | 1.000 |
157 | 1.000 | 0.143 | 0.000 | 1.000 | 1.000 |
158 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
159 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
160 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
161 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
162 | 0.000 | 1.000 | 0.333 | 0.250 | 0.000 |
163 | 0.250 | 0.000 | 0.000 | 0.000 | 0.000 |
164 | 0.000 | 0.000 | 0.000 | 0.000 | 0.167 |
165 | 1.000 | 0.000 | 0.000 | 0.000 | 0.167 |
166 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
167 | 1.000 | 0.167 | 0.000 | 1.000 | 1.000 |
168 | 0.000 | 1.000 | 0.500 | 1.000 | 0.500 |
169 | 1.000 | 0.000 | 0.333 | 1.000 | 1.000 |
170 | 1.000 | 0.333 | 0.000 | 1.000 | 1.000 |
171 | 0.111 | 0.000 | 0.000 | 0.000 | 0.000 |
172 | 0.500 | 1.000 | 1.000 | 1.000 | 1.000 |
173 | 1.000 | 0.000 | 1.000 | 0.167 | 0.000 |
174 | 0.250 | 1.000 | 0.200 | 0.500 | 0.000 |
175 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
176 | 1.000 | 0.000 | 0.000 | 0.000 | 0.333 |
177 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
178 | 0.625 | 0.000 | 0.000 | 1.000 | 0.100 |
179 | 0.333 | 0.000 | 0.000 | 1.000 | 0.000 |
180 | 1.000 | 0.000 | 0.000 | 0.000 | 0.200 |
181 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
182 | 1.000 | 0.000 | 1.000 | 0.000 | 0.000 |
183 | 0.250 | 0.000 | 1.000 | 0.000 | 0.333 |
184 | 0.000 | 0.000 | 0.333 | 0.000 | 1.000 |
185 | 1.000 | 0.000 | 0.333 | 0.500 | 1.000 |
186 | 0.033 | 0.000 | 0.037 | 0.000 | 0.667 |
187 | 0.250 | 0.000 | 0.000 | 0.000 | 1.000 |
188 | 1.000 | 0.000 | 0.000 | 0.000 | 0.000 |
189 | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 |
190 | 1.000 | 0.000 | 0.000 | 0.500 | 1.000 |
191 | 1.000 | 1.000 | 1.000 | 1.000 | 0.000 |
192 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
Task 1c Summary Results by Query
Simple Hit/Miss Counting [5]
MRR Method [6]
Task 2 Results
Task 2 Overall Results
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
Simple Count | 6.979 | 9.135 | 9.073 | 8.741 | 8.741 |
Total Count | 2020 | 2040 | 2040 | 2040 | 2040 |
Task 2 Friedman's Test for Significant Differences
The Friedman test was run in MATLAB against the QBSH Task 2 data over the 48 ground truth song groups. Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
---|---|---|---|---|---|
JY1 | JY2 | -0.3070 | 0.5417 | 1.3903 | FALSE |
JY1 | YF2 | 0.3597 | 1.2083 | 2.0570 | TRUE |
JY1 | YF1 | 0.3597 | 1.2083 | 2.0570 | TRUE |
JY1 | HAFR1 | 2.2347 | 3.0833 | 3.9320 | TRUE |
JY2 | YF2 | -0.1820 | 0.6667 | 1.5153 | FALSE |
JY2 | YF1 | -0.1820 | 0.6667 | 1.5153 | FALSE |
JY2 | HAFR1 | 1.6930 | 2.5417 | 3.3903 | TRUE |
YF2 | YF1 | -0.8486 | 0.0000 | 0.8486 | FALSE |
YF2 | HAFR1 | 1.0264 | 1.8750 | 2.7236 | TRUE |
YF1 | HAFR1 | 1.0264 | 1.8750 | 2.7236 | TRUE |
Task 2 Summary Results by Query Group
HAFR1 | JY1 | JY2 | YF1 | YF2 | |
---|---|---|---|---|---|
1 | 4.111 | 5.444 | 5.444 | 5.333 | 5.333 |
2 | 0.250 | 4.000 | 3.500 | 2.250 | 2.250 |
3 | 0.000 | 3.000 | 1.000 | 0.000 | 0.000 |
4 | 2.600 | 3.200 | 3.000 | 4.400 | 4.400 |
5 | 4.800 | 8.400 | 6.800 | 6.800 | 6.800 |
6 | 1.500 | 4.000 | 3.500 | 5.000 | 5.000 |
7 | 2.200 | 7.600 | 7.000 | 6.600 | 6.600 |
8 | 4.000 | 5.400 | 5.200 | 6.800 | 6.800 |
9 | 2.500 | 2.500 | 2.500 | 2.000 | 2.000 |
10 | 3.000 | 4.333 | 4.222 | 4.556 | 4.556 |
11 | 6.326 | 9.140 | 9.047 | 8.791 | 8.791 |
12 | 6.930 | 9.361 | 9.333 | 9.542 | 9.542 |
13 | 7.347 | 7.421 | 7.447 | 9.237 | 9.237 |
14 | 8.690 | 9.278 | 9.236 | 8.722 | 8.722 |
15 | 3.929 | 6.286 | 6.286 | 5.214 | 5.214 |
16 | 7.384 | 9.784 | 9.824 | 8.946 | 8.946 |
17 | 5.408 | 9.625 | 9.542 | 9.111 | 9.111 |
18 | 8.145 | 9.737 | 9.842 | 9.026 | 9.026 |
19 | 7.691 | 9.870 | 9.710 | 9.333 | 9.333 |
20 | 8.272 | 9.707 | 9.610 | 9.341 | 9.341 |
21 | 3.265 | 9.088 | 9.059 | 8.971 | 8.971 |
22 | 8.098 | 9.470 | 9.458 | 9.398 | 9.398 |
23 | 4.933 | 9.387 | 9.355 | 8.516 | 8.516 |
24 | 6.862 | 7.644 | 7.610 | 9.136 | 9.136 |
25 | 7.448 | 9.254 | 9.085 | 8.119 | 8.119 |
26 | 6.000 | 9.762 | 9.810 | 7.667 | 7.667 |
27 | 4.756 | 9.311 | 9.267 | 8.156 | 8.156 |
28 | 7.065 | 9.348 | 9.087 | 9.043 | 9.043 |
29 | 7.309 | 9.735 | 9.721 | 9.426 | 9.426 |
30 | 9.045 | 9.940 | 9.866 | 9.687 | 9.687 |
31 | 7.828 | 9.300 | 9.417 | 9.650 | 9.650 |
32 | 7.844 | 9.766 | 9.734 | 9.719 | 9.719 |
33 | 6.520 | 9.588 | 9.431 | 7.824 | 7.824 |
34 | 8.382 | 9.485 | 9.441 | 9.441 | 9.441 |
35 | 7.500 | 9.609 | 9.565 | 8.971 | 8.971 |
36 | 4.333 | 7.667 | 6.750 | 7.792 | 7.792 |
37 | 6.250 | 6.036 | 5.536 | 7.250 | 7.250 |
38 | 7.704 | 8.204 | 8.278 | 8.593 | 8.593 |
39 | 7.191 | 9.794 | 9.765 | 7.574 | 7.574 |
40 | 6.444 | 9.296 | 9.333 | 8.815 | 8.815 |
41 | 7.586 | 9.814 | 9.847 | 9.305 | 9.305 |
42 | 5.707 | 8.357 | 8.310 | 7.214 | 7.214 |
43 | 6.678 | 8.500 | 8.550 | 8.500 | 8.500 |
44 | 6.556 | 10.000 | 10.000 | 9.361 | 9.361 |
45 | 5.085 | 9.702 | 9.702 | 7.277 | 7.277 |
46 | 6.703 | 8.842 | 8.789 | 8.316 | 8.316 |
47 | 3.385 | 7.846 | 7.231 | 8.231 | 8.231 |
48 | 7.591 | 9.955 | 9.773 | 8.273 | 8.273 |
Task 2 Summary Results by Query
Runtime Results
Participant | Task | Runtime(min) | Machine |
---|---|---|---|
HAFR1 | Task1a | 1752 | nema-c-1-2 |
HAFR1 | Task1b | 247 | nema-c-1-2 |
HAFR1 | Task1c | 369 | nema-c-1-2 |
HAFR1 | Task2 | 411 | nema-c-1-2 |
JY1 | Task1a | 324 | win-0-1-1 |
JY1 | Task1b | 43 | win-0-1-1 |
JY1 | Task1c | 43 | win-0-1-1 |
JY1 | Task2 | 232 | win-0-1-1 |
JY2 | Task1a | 1136 | win-0-1-1 |
JY2 | Task1b | 177 | win-0-1-1 |
JY2 | Task1c | 323 | win-0-1-1 |
JY2 | Task2 | 499 | win-0-1-1 |
YF1 | Task1a | 90 | FAST3 |
YF1 | Task1b | 8 | FAST3 |
YF1 | Task1c | 10 | FAST3 |
YF1 | Task2 | 512 | FAST3 |
YF2 | Task1a | 2922 | FAST3 |
YF2 | Task1b | 367 | FAST3 |
YF2 | Task1c | 593 | FAST3 |
YF2 | Task2 | 510 | FAST3 |