Changes between Version 34 and Version 35 of private/NlpInPracticeCourse/LanguageResourcesFromWeb

Timestamp:

Apr 10, 2022, 9:09:22 PM (2 years ago)

Author:

Ales Horak

Comment:

edited by hales in edit_page_in_vim.py

private/NlpInPracticeCourse/LanguageResourcesFromWeb

@@ -2 +2 @@
 Web crawling, boilerplate removal, de-duplication and plagiarism detection.
 
-[[https://is.muni.cz/auth/predmet/fi/ia161|IA161]] [[en/AdvancedNlpCourse|Advanced NLP Course]], Course Guarantee: Aleš Horák
+[[https://is.muni.cz/auth/predmet/fi/ia161|IA161]] [[en/NlpInPracticeCourse|NLP in Practice Course]], Course Guarantee: Aleš Horák
 
 
 Prepared by: Vít Suchomel[[BR]]
-[http://nlp.fi.muni.cz/trac/research/raw-attachment/wiki/en/AdvancedNlpCourse/anlp-05-LanguageResourcesFromWeb.pdf Slides]
+[http://nlp.fi.muni.cz/trac/research/raw-attachment/wiki/en/NlpInPracticeCourse/anlp-05-LanguageResourcesFromWeb.pdf Slides]
 
 
@@ -44 +44 @@
 
 Or: Select a detection algorithm and implement it in Python. //The right homework if you want to learn something.//
-  * A basic detection script to extend: [https://nlp.fi.muni.cz/trac/research/raw-attachment/wiki/en/AdvancedNlpCourse/LanguageResourcesFromWeb/plagiarism_simple.py plagiarism_simple.py] -- usage: {{{python plagiarism_simple.py < training_data.vert}}}
+  * A basic detection script to extend: [https://nlp.fi.muni.cz/trac/research/raw-attachment/wiki/en/NlpInPracticeCourse/LanguageResourcesFromWeb/plagiarism_simple.py plagiarism_simple.py] -- usage: {{{python plagiarism_simple.py < training_data.vert}}}
     * A bag of words + cosine similarity of word vectors approach is implemented in this script. //(For the sake of simplicity: A plagiarism cannot have more sources here.)//
     * You can modify the script to
@@ -50 +50 @@
       * or implement other lexical/syntactic based detection approach, e.g. n-grams of words or Levenshtein's distance,
       * or implement other semantic based detection approach, e.g. the similarity of {{{word2vec}}} vectors.
-  * Input format: A 3-column vertical, see above. [https://nlp.fi.muni.cz/trac/research/raw-attachment/wiki/en/AdvancedNlpCourse/LanguageResourcesFromWeb/training_data.vert training_data.vert]
+  * Input format: A 3-column vertical, see above. [https://nlp.fi.muni.cz/trac/research/raw-attachment/wiki/en/NlpInPracticeCourse/LanguageResourcesFromWeb/training_data.vert training_data.vert]
   * Output: One plagiarism per line: id TAB detected source id TAB real source id. Evaluation line: precision, recall F1 measure.
   * Your script will be evaluated using data made by others.