Changes between Initial Version and Version 1 of en/AdvancedNlpCourse2015/Stylometry

Timestamp:

Sep 11, 2017, 4:34:19 PM (7 years ago)

Author:

Ales Horak

Comment:

copied from private/AdvancedNlpCourse/Stylometry

en/AdvancedNlpCourse2015/Stylometry

@@ +1 @@
+= Stylometry =
+
+[[https://is.muni.cz/auth/predmet/fi/ia161|IA161]] [[en/AdvancedNlpCourse|Advanced NLP Course]], Course Guarantee: Aleš Horák
+
+Prepared by: Honza Rygl
+
+== State of the Art ==
+
+The analysis of author's characteristic
+writing style and vocabulary has been used to uncover author's traits such as authorship, age, or gender
+documents by both manual linguistic approaches and automatic algorithmic methods.
+
+The most common approach to stylometry problems
+is to combine stylistic analysis with machine learning techniques:
+ 1. specific style markers are extracted,
+ 2. a classification procedure is applied to extracted markers
+
+
+=== References ===
+
+ 1. Stamatatos, E. (2009), A Survey of Modern Authorship Attribution Methods (2009), Journal of the American Society for Information Science and Technology, 60(3), 538-556. [[http://www.clips.ua.ac.be/~walter/educational/material/Stamatatos_survey2009.pdf | pdf]]
+ 2. Kestemont, M. (2014), Function Words in Authorship Attribution From Black Magic to Theory? Proceedings of the 3rd Workshop on Computational Linguistics for Literature, EACL 2014, 59–66 [[http://aclweb.org/anthology/W14-0908 | pdf]]
+ 1. Walter, D.  Explanation in Computational Stylometry
+
+== Practical Session ==
+
+Student will get to know a *Style & Identity Recognition* tool. They will test this tool on prepared data.
+Their goal will be to implement a small function to extract style markers from a text.
+
+1. go to `asteria04.fi.muni.cz` server:
+{{{
+ssh asteria04.fi.muni.cz
+}}}
+2. Download a  [[htdocs:bigdata/stylometry-assignment.zip|python package with the assignment]] 
+3. Unzip the downloaded file
+{{{
+unzip stylometry-assignment.zip
+}}}
+4. Go to the unziped folder
+{{{
+cd sir-assignment
+}}}
+5. Test the prepared program that analyses data from on-line dating services to distinguish gender (masculine/feminine) by text style features
+{{{
+./run.sh
+}}}
+
+`run.sh` can have two optional parameters:
+{{{
+./run.sh  [number_of_testing_cycles]  [show_first_N_erroneously_predicted_documents]
+}}}
+The default values, i.e. running `./run.sh` without parameters, are `100` cycles and `no documents` (`./run.sh 100 0`). For faster feature testing even `./run.sh 10` should be sufficient.
+
+Example with document output:
+{{{
+[xrygl@asteria04:~/temp/sir-assignment]$ ./run.sh 10 1
+author: on
+text: Ahoj, (nejen) pro výlety do víru podivnězimního velkoměsta, či divočiny
+venkova, hledá se partnerka přiměřených rozměrů, tvarů a úrovně. Slečny veselé
+povahy preferovány; ona je to nejspíš nutnost :-)
+morphology: ((u'<s>', u'<s>'), (u'Ahoj', u'N.N.I.S.1.-.-.-.-.-.A.-.-.-.-'),
+(u',', u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'), (u'(',
+u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'), (u'nejen', u'T.T.-.-.-.-.-.-.-.-.-.-.-.-.-'),
+(u')', u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'), (u'pro',
+u'R.R.-.-.4.-.-.-.-.-.-.-.-.-.-'), (u'v\xfdlety',
+u'N.N.I.P.4.-.-.-.-.-.A.-.-.-.-'), (u'do', u'R.R.-.-.2.-.-.-.-.-.-.-.-.-.-'),
+(u'v\xedru', u'N.N.I.S.2.-.-.-.-.-.A.-.-.-.-'), (u'podivn\u011bzimn\xedho',
+u'A.A.N.S.2.-.-.-.-.1.A.-.-.-.-'), (u'velkom\u011bsta',
+u'N.N.N.S.2.-.-.-.-.-.A.-.-.-.-'), (u',', u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'),
+(u'\u010di', u'J.^.-.-.-.-.-.-.-.-.-.-.-.-.-'), (u'divo\u010diny',
+u'N.N.F.S.2.-.-.-.-.-.A.-.-.-.-'), (u'venkova',
+u'N.N.I.S.2.-.-.-.-.-.A.-.-.-.-'), (u',', u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'),
+(u'hled\xe1', u'V.B.-.S.-.-.-.3.P.-.A.A.-.-.-'), (u'se',
+u'P.7.-.X.4.-.-.-.-.-.-.-.-.-.-'), (u'partnerka',
+u'N.N.F.S.1.-.-.-.-.-.A.-.-.-.-'), (u'p\u0159im\u011b\u0159en\xfdch',
+u'A.A.I.P.2.-.-.-.-.1.A.-.-.-.-'), (u'rozm\u011br\u016f',
+u'N.N.I.P.2.-.-.-.-.-.A.-.-.-.-'), (u',', u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'),
+(u'tvar\u016f', u'N.N.I.P.2.-.-.-.-.-.A.-.-.-.-'), (u'a',
+u'J.^.-.-.-.-.-.-.-.-.-.-.-.-.-'), (u'\xfarovn\u011b',
+u'N.N.F.S.2.-.-.-.-.-.A.-.-.-.-'), (u'.', u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'),
+(u'<s>', u'<s>'), (u'Sle\u010dny', u'N.N.F.P.1.-.-.-.-.-.A.-.-.-.-'),
+(u'vesel\xe9', u'A.A.N.S.1.-.-.-.-.1.A.-.-.-.-'), (u'povahy',
+u'N.N.F.S.2.-.-.-.-.-.A.-.-.-.-'), (u'preferov\xe1ny',
+u'V.s.T.P.-.-.-.X.X.-.A.P.-.-.-'), (u';', u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'),
+(u'ona', u'P.P.F.S.1.-.-.3.-.-.-.-.-.-.-'), (u'je',
+u'V.B.-.S.-.-.-.3.P.-.A.A.-.-.-'), (u'to', u'P.D.N.S.1.-.-.-.-.-.-.-.-.-.-'),
+(u'nejsp\xed\u0161', u'D.g.-.-.-.-.-.-.-.3.A.-.-.-.-'), (u'nutnost',
+u'N.N.F.S.1.-.-.-.-.-.A.-.-.-.-'), (u':', u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'),
+(u'-', u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'), (u')',
+u'Z.:.-.-.-.-.-.-.-.-.-.-.-.-.-'))
+Acc: 73.7 +- 2.2% (baseline 50.0%, 10 iterations)
+}}}
+
+=== Task ===
+Examine files in  `stylometry_features` folder.
+Modify the `assignment.py` file to increase the accuracy of methods.
+You can create another classes inside, change their names and class names to improve the accuracy score. Don't forget to add new classes into the `assignments` list in this file.
+
+Suggestions for your inspiration include:
+ * diacritics usage (yes/no), a regular expression will be needed
+ * sentence endings (number of sentences, or typical endings)
+ * repetitions of words in sentences/in the text
+ * usage of uppercase letters
+ * length of sentences/text
+ * POS tags (n-grams)
+ * word n-grams
+ * character n-grams
+
+Each modification can be tested by running `./run.sh` again.
+The first call of `run.sh` can be slower, because documents are morphologically analysed during the first run.
+
+Submit your assignment file. Write nice Python code and don't forget about PEP8 (https://www.python.org/dev/peps/pep-0008/).