Day #63 - Notes from Text processing and Parallel Programming

Quick Summary notes for future reference

Text Processing - Word Sense Disambiguation

• Rely on leveraging wordnet (Knowledge sources)
• from nltk.corpus import wordnet - leverage it
• Leverage Machine readable dictionary

Lesks Algorithm

• Sense bag (ambigious word)
• Context bag (different definitions to context word)
• Close match will be picked

Walkers Algorithm for word sense disambiguation

• Use Thesaurus to find scores in context
• Highest score will be picked up for context relevance
• Thesaurus Library pywordnet, now part of NLTK

Keywords

• Polysemy - many possible meanings for a word or phrase.
• Homonym - same spelling or pronunciation but different meanings

Parallel Programming

• Filter locks
• Bakery Algorithm

Example Implementation - link

Memory Consistency

• Strict Consistency 
• Sequentially consistent
• Relaxed(Weak) consistent

Linearization Point
From Stackoverflow

Coarse Grained Vs Fine Grained
From Stackoverflow

Petersons Algorithm


More Reads - Link

Happy Learning!!!