| Key | Value |
|---|---|
| FileSize | 3563096 |
| MD5 | 18C7F827F37A0A6E78847F5CF9776022 |
| PackageDescription | Jieba Chinese text segmenter (common documentation) "Jieba" (Chinese for "to stutter")is a high-accuracy Chinese text segmenteran based on HMM-model and Viterbi algorithm. It uses dynamic programming to find the most probable combination based on the word frequency. . This is the common documentation package. |
| PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
| PackageName | python-jieba-doc |
| PackageSection | doc |
| PackageVersion | 0.42.1-2 |
| SHA-1 | 0E7374218C5D2CD67AC6092933F45E2B3F0F2147 |
| SHA-256 | 1B8DFB7B7709E67E85490DF885437178133913AD6B6E1CC228F6CD744C1313A9 |
| hashlookup:children-total | 46 |
| hashlookup:trust | 50 |
The searched file hash includes 46 children files known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-jieba-doc/examples/test/test_pos_no_hmm.py |
| FileSize | 4872 |
| MD5 | A65172BAA47160ACAFFDC3056499636F |
| SHA-1 | 018AD6A88C8E82A82C069A2AFC246007D6AAB517 |
| SHA-256 | 2EC97D57598C6287C76DE3A1E0406D0DFD724CABAE334674D3AB3762480181B4 |
| SSDEEP | 96:nmBR3D29C+vckX1D+yaFjeuDHilg/CdSSgqgaZ3:nmBkFFC9FjRHiG/CjB |
| TLSH | T158A1B3F0C7332BF80763268942678575ABB0C9BB0287414CF6A9D5E64F8767F05D08AE |
| Key | Value |
|---|---|
| CRC32 | C0F7D0F5 |
| FileName | ./usr/share/doc/python-jieba-doc/examples/extra_dict/dict.txt.small |
| FileSize | 1552161 |
| MD5 | E71CD9FDF5F604FC79610C4D504A6C22 |
| OpSystemCode | 362 |
| ProductCode | 237673 |
| RDS:package_id | 305120 |
| SHA-1 | 06F0CD6380DDCEE9788DE9AB52AFC693178A9278 |
| SHA-256 | 479CF8CC37E78BC908AE330D9153375547D4FF7F7D03A1AC4D4908D3677FF664 |
| SSDEEP | 24576:VKZZFGjo4EhydxvuBB4vIzKpYeTb3rpeIOk6eZr+GW98DMPT:sj4TZUr |
| SpecialCode | |
| TLSH | T14375C37D0B2A7C59CDE7AAC88F108AD0962ED628C305E8F4916E53F7664CDFD81E485C |
| db | nsrl_android |
| insert-timestamp | 1703173640.7959874 |
| source | db.sqlite |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-jieba-doc/examples/test/test_cut_for_search.py |
| FileSize | 4804 |
| MD5 | 9E8622D6ABCC78B2963A6AEF62E99A84 |
| SHA-1 | 09819F9ABFDE057E3A73759D0C43E59DE8942318 |
| SHA-256 | 26DB0F3E43CE0C3137AAB442E6738E74342933848A88BFAC4E07C89E246A677A |
| SSDEEP | 96:naYR3D29C+vckX1D+yaFjeuDHilg/CdSSgqgaZz:naYkFFC9FjRHiG/CjB |
| TLSH | T18FA1C4F0D7332BF80723268A42678575ABB0C97B0287414CF6A9C5E54F87A3F45D08AE |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-jieba-doc/examples/test/parallel/test_cut_for_search.py |
| FileSize | 4525 |
| MD5 | 222429DE306E404B9A5DB623ECDF3C9B |
| SHA-1 | 0A184D6CFED0897EFE2E2CD0047EFD6749555A33 |
| SHA-256 | 3AE7597747B52A1D92A60F7E5046CC632999C56F468D62D99F4B7CF456E41BD8 |
| SSDEEP | 96:nkYR3D29C+vckX1D+yaFjeuDHilg/CdSSgqg6:nkYkFFC9FjRHiG/Cj1 |
| TLSH | T1F891C5F0D3372BF80733268942678575ABB0C97B0286454CF6A9D9E54F87A7F05D08AE |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-jieba-doc/examples/test/parallel/test_disable_hmm.py |
| FileSize | 4524 |
| MD5 | FC2B02C2DCCEEB8A2822071F0F442982 |
| SHA-1 | 0B653B7835D277F74E2E130D2AB5D7A21CBD2FC8 |
| SHA-256 | EC96B8AE6E47922715EF51A7EDE3EC42FA0E90F99032614AE92CC2F62A0774C5 |
| SSDEEP | 96:nkJR3D29C+vckX1D+yaFjeuDHilg/CdSSgqg6:nkJkFFC9FjRHiG/Cj1 |
| TLSH | T18B91C5F0D3332BF80733268942678575ABB0C97B0286554CF6A9D9E50F8767F01D086E |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-jieba-doc/examples/test/test_paddle.py |
| FileSize | 5127 |
| MD5 | 1517AB1C57E94B74779CA297E8488BAD |
| SHA-1 | 0E1A2AE0C2F52BE5E8FEAD6EE41A10619867B951 |
| SHA-256 | 38370E9BEDC2E26D69877F6BB932AFFB38D7BB838F51C7223F2F01BE97C9F5A2 |
| SSDEEP | 96:9/EGCR3D29C+vckX1D+yaFjeuDHilg/CdSSgqgaZSpU:9cxkFFC9FjRHiG/CjopU |
| TLSH | T196B1B5F0D3732BF80767268D426B45B4AB70C97B1286414CF9A9D5D60F8763F05D08AE |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-jieba-doc/examples/test/extract_tags_idfpath.py |
| FileSize | 594 |
| MD5 | 17B76F6D1ECD07D4ED64C20A7F56E467 |
| SHA-1 | 0E3F1238D839FEE1560ED1E4DB98CB8163227DC0 |
| SHA-256 | 808D10BFF0C3DB8EDEB78BB3D7E26399A877FF2C7E9E62812C4D901738876C6E |
| SSDEEP | 12:kkBaBq6uXNN1nnKgun5gyihaRgkQXhorlRdtT3ivi:kkE/oKg85XihuugdtT3ivi |
| TLSH | T102F0AC4110E11120CB0582C6ACAC3862C7776962AFC59A322B047659AFC1A60EBD2624 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-jieba-doc/examples/test/userdict.txt |
| FileSize | 151 |
| MD5 | C9DC30755C983AF7FB436A850865304C |
| SHA-1 | 160E191A880299FF0944E660F350A2165746D8D4 |
| SHA-256 | 67B204DB82EE54172DDFFBCDD4D16B8918574D9456B2727A9C17D62C2823F62A |
| SSDEEP | 3:20LEPKDqFXYFQUnLWgLSvNdNQcmvwAUHL0HU0rFQWNv:2yXqtoQ+WgG7Ngmr81GWNv |
| TLSH | T11BC08C9CAC4A38A962C0A0D0A14999D5480E6890E49BF06F269361690854DAFF804043 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-jieba-doc/examples/test/demo.py |
| FileSize | 2678 |
| MD5 | C974FC64EB68BB591039A5311D7F1BBF |
| SHA-1 | 2D8E039AFD6E3D83CCFB412449D80A30505928F6 |
| SHA-256 | 301594AF8F199F654578316E8E385F075C599D99D434F1FE9BF6A15D2281B222 |
| SSDEEP | 48:6u/kuCR4X44IGGiyx1xDzh3ztoi7LVlfQFN2dywo4wnH14Oxpzv4Ou:f0AoJNtoi7h9Qboywzwnr4 |
| TLSH | T1FA51985235FA260C15C1C1CBE3AC61023507EE4EA2FD3C649B514AD7C972AD6B7B503E |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-jieba-doc/examples/test/test_multithread.py |
| FileSize | 830 |
| MD5 | B63D05B75E8512362FBD5B17EC8237F1 |
| SHA-1 | 2E8B501B968696A8D1A08AFCCC2736A48B4ECF92 |
| SHA-256 | 18857F6073DAE96CED204AF16F286A5DB3091BEADC3E9C60823CFBED66240C8B |
| SSDEEP | 24:IkOiuil8ugIEdu9JqEur86EhQFyxSReTE8rK:9Oiuo/z0miyxGeQ |
| TLSH | T14E01892699E7140C66C2CB8BB2909331951ECDC324992470BF6C9B29CFF6E1943D287D |