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A Java program to check Plagiarisms between multiple documents using the method of Shingling, MinHashing and Locality Sensitive Hashing.

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P1.java
P1.java
 
 
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README.txt
 
 

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README -
----------------------------
COEN 281 Programming Assignment 1 
Submitted by,

Shruti Jagadeesh Bhat
CSE Grad Student, Santa Clara University'21
----------------------------
Assumptions:
- If a file is empty, it is skipped from the computations.
- All the test files, (eg: t1*.dat and .txt) files are assumed to be in the same folder as the mentioned path - "/home/mwang2/test/coen281"

----------------------------
Self - submission details:

[sbhat1@linux10610 ~]$ perl Autotest 1
sbhat1
P1/
P1/Makefile
P1/P1.java
P1/README.txt
gmake under /DCNFS/users/student/sbhat1/AutoTestDir/sbhat1/P1
javac P1.java
time java P1 < /home/mwang2/test/coen281/t10.dat >> out

real	0m0.501s
user	0m0.979s
sys	0m0.065s
time java P1 < /home/mwang2/test/coen281/t11.dat >> out

real	0m0.239s
user	0m0.377s
sys	0m0.037s
time java P1 < /home/mwang2/test/coen281/t19.dat >> out
Wrong file Error: File either doesnt exist or broken! Skipping the file: /home/mwang2/test/coen281/@gamil.com
Empty Bound!

real	0m0.112s
user	0m0.096s
sys	0m0.024s
[sbhat1@linux10610 ~]$ 

----------------------------
References;
Code snippet of transpose of an ArrayList<> Matrix from Stack Overflow.
Text Book - Mining of Massive data sets

My Test Outputs:
grafikos@MacBook-Pro src % javac P1.java    
grafikos@MacBook-Pro src % java P1 < t10.dat
Empty File! Skipping the file: f3.txt
Wrong file Error: File either doesnt exist or broken! Skipping the file: @gmail.com
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>

SET OF UNIQUE SHINGLES:

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nerating , erating t, rating th, ating the, ting the , ing the c, ng the ch, g the cha,  the char, the chart, he chart , e chart t,  chart th, chart the, hart the , art the c, rt the cr, t the cro,  the cros, the cross, he cross , e cross v, idation c, dation ch, ation cha, tion char, ion chart, on chart , n chart i,  chart is, chart is , hart is c, art is cr, rt is cre, t is crea,  is creat, is create, s created,  created , created b, reated by, eated by , ated by u, ted by us, ed by usi, d by usin,  by using, by using , y using a,  using ad, using add, sing addi, ing addit, ng additi, g additio,  addition, additiona, dditional, itional i, tional in, ional inp, onal inpu, nal input, al inputs, l inputs ,  inputs a, inputs av, nputs ava, puts avai, uts avail, ts availa, s availab,  availabl, available, vailable , ailable o, ilable on, lable on , able on t, ble on th, le on the, e on the ,  on the c, on the cr, n the cro, idation t, dation ta, ation tab, ion tab f, on tab fo, n tab for,  tab for , tab for m, ab for mo, b for mor,  for more, for more , or more i, r more in,  more inf, more info, ore infor, re inform, e informa, rmation s, mation se, ation see, tion see , ion see c, on see cr, n see cro,  see cros, see cross, ee cross , idation a, dation an, ation ana, tion anal, ion analy, on analys, n analysi, nalysis s, alysis se, lysis ser, ysis serv, sis servi, is servic, s service,  services, services , ervices d, rvices da, vices dat, ices data, ces data , es data m, s data mi,  data min, data mini, ata minin, ta mining, a mining ,  mining f, mining fo, ining for, ning for , ing for m, ng for mo, g for mor, mation ab, ation abo, tion abou, ion about, on about , n about h,  about ho, about how, bout how , out how t, ut how to, t how to ,  how to u, how to us, ow to use, w to use ,  to use t, to use th, o use the, use the m, se the mi, e the min,  the mini, the minin, he mining, e mining ,  mining a, mining ac, ining acc, ning accu, ing accur, ng accura, g accurac,  accuracy, accuracy , ccuracy c, curacy ch, uracy cha, racy char, acy chart, cy chart , y chart s,  chart se, chart see, hart see , art see t, rt see te, t see tes,  see test, see testi, ee testin, e testing,  testing , testing a, esting an, sting and, ting and , ing and v, ng and va, g and val,  and vali, and valid, nd valida, d validat, idation d, dation da, ation dat, tion data, ion data , on data m, n data mi, similar t, imilar tr, milar tra, ilar trad, lar tradi, ar tradit, r traditi]

SHINGLE-DOCUMENT MATRIX:
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| 0 0 0 0 1 0 |
| 0 0 0 0 1 0 |
| 0 0 0 0 1 0 |
| 0 0 0 0 1 0 |
| 0 0 0 0 1 0 |
| 0 0 0 0 1 0 |
| 0 0 0 0 1 0 |
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| 0 0 0 0 1 0 |
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| 0 0 0 0 1 0 |
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| 0 0 0 0 1 0 |
| 0 0 0 0 1 0 |
| 0 0 0 0 1 0 |
| 0 0 0 0 0 1 |
| 0 0 0 0 0 1 |
| 0 0 0 0 0 1 |
| 0 0 0 0 0 1 |
| 0 0 0 0 0 1 |
| 0 0 0 0 0 1 |
| 0 0 0 0 0 1 |

RANDOMIZED MIN HASH VALUES:
[125, 33, 1184, 1195, 431, 1222, 450, 1022, 299, 1318, 147, 1412, 64, 1238, 355, 945, 1080, 262, 125, 660, 484, 148, 201, 1224, 722, 113, 603, 38, 936, 395, 547, 197, 508, 338, 936, 342, 351, 918, 578, 346, 1059, 839, 558, 221, 893, 685, 862, 1011, 1357, 439, 958, 886, 506, 485, 751, 791, 932, 762, 132, 210, 176, 899, 1400, 932, 599, 407, 584, 1020, 435, 127, 334, 282, 1495, 924, 1420, 754, 1106, 844, 89, 230, 1341, 614, 1176, 1296, 780, 248, 545, 1368, 905, 574, 312, 962, 130, 1014, 1428, 601, 777, 642, 603, 1086]

SIGNATURE MATRIX :
4  3  67  13  6  4  
1  12  487  3  8  1  
0  1  823  6  4  0  
7  1  585  3  23  7  
7  0  615  4  7  7  
10  0  1204  5  0  10  
9  3  5  1  0  9  
22  9  280  2  4  6  
14  2  1  6  2  14  
6  0  922  4  0  6  
0  0  955  0  4  0  
1  1  752  5  16  1  
0  0  1151  2  5  0  
7  1  628  0  1  7  
4  1  118  9  7  4  
1  4  433  7  4  1  
2  9  856  4  4  2  
3  0  540  8  0  3  
16  0  241  15  4  16  
19  0  785  2  0  19  
2  0  469  2  2  2  
2  6  1069  1  4  2  
5  1  853  2  1  5  
4  0  1241  4  1  4  
10  0  281  5  4  10  
6  1  240  3  6  6  
2  0  186  1  0  2  
2  4  106  2  3  2  
6  0  307  2  4  6  
0  1  685  18  15  0  
2  4  755  1  1  2  
1  3  430  2  1  1  
0  1  419  2  5  0  
1  2  246  5  0  1  
0  5  330  6  0  0  
2  7  1064  12  1  13  
1  1  81  1  9  1  
3  0  207  0  1  3  
3  1  586  15  0  3  
3  4  227  9  5  3  
13  0  690  0  3  13  
3  0  64  0  1  3  
0  1  709  10  2  0  
0  6  125  1  0  0  
0  4  259  10  0  0  
2  10  672  2  5  2  
0  1  225  1  0  0  
4  1  152  7  3  4  
1  0  807  1  1  1  
9  1  739  4  0  9  
6  4  1213  0  7  6  
6  1  178  1  1  6  
3  1  808  3  5  3  
0  1  2  2  3  0  
0  0  151  0  1  0  
3  3  438  5  1  3  
0  0  987  0  10  0  
6  3  320  1  0  6  
8  1  93  0  4  8  
4  4  822  0  1  4  
1  10  679  6  5  1  
8  3  117  11  0  8  
2  0  732  4  1  2  
7  0  633  2  15  7  
3  0  664  2  3  3  
1  6  657  0  7  1  
0  4  333  7  1  0  
11  0  8  5  10  11  
1  0  112  4  2  1  
1  3  1168  3  4  1  
0  2  1140  4  9  0  
0  1  74  0  5  0  
1  4  428  5  0  1  
13  1  472  2  0  13  
2  2  723  7  4  2  
3  6  349  1  2  3  
0  3  669  11  7  0  
16  4  844  7  5  16  
0  1  881  6  0  0  
14  1  12  6  4  14  
6  6  260  5  0  6  
2  4  477  2  0  2  
0  2  224  0  10  0  
4  1  193  1  2  4  
1  1  553  6  1  1  
2  4  681  10  1  2  
20  3  958  10  11  20  
0  2  337  2  0  0  
5  0  43  5  1  5  
0  5  801  1  3  0  
8  7  11  6  0  8  
9  1  974  9  1  9  
3  1  889  1  1  3  
0  6  74  0  9  0  
0  0  652  0  0  0  
10  0  384  12  0  10  
3  6  516  8  3  3  
8  3  611  0  0  8  
2  11  735  2  7  2  
0  1  423  0  0  0

About

A Java program to check Plagiarisms between multiple documents using the method of Shingling, MinHashing and Locality Sensitive Hashing.

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hashing locality-sensitive-hashing datamining plagiarism-detection shingling min-hashing

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