Author : [email protected]
Description : Tokenizes chunks of text efficiently using a producer comsumer threading architecture and stores the word frequency in a pickled dictionary
- Tokenize words
- Removes stop words
- Stems the word using NLTK Lancaster stemmer i.e playing => play , played => play
- Removes punctuations and irrelavant charecters like ( !@#$%& )
- Removes more than 2 repeatition of charecters in a text like heyyyy => heyy , yeaaaahh => yeaahh
- Removes links,#tags and @username references
- Removes numbers like 1, 12 but not words like g8 , n8 , m8 etc
- The data to be processed is assumed to be saved in a file called data.txt.
- The stopwords.p contains basic stop words.
- Custom stop words list could be created by writting the words line by line in a stop.txt file and running the stop_pickle.py script
- If u dont need to remove stop words create an empty stopwords.p file and save it in the same directory as Tokenizer.py or remove the appropriate code from Tokenizer.py
- data.txt
- Write each data line by line
- stop.txt
- Write each word in a line
- Run the stop_pickle.py script to pickle stop.txt file to stopwords.p file