Natural Language Processing
This chapter explores how genetic algorithms can enhance the performance of natural language processing (NLP) tasks while offering insights into their underlying mechanisms.
The chapter begins by introducing the field of NLP and explaining the concept of word embeddings. We employ this technique to task a genetic algorithm with playing a Semantle-like mystery-word game, challenging it to guess the mystery word.
Subsequently, we investigate n-grams and document classification. We harness genetic algorithms to pinpoint a compact yet effective subset of features, shedding light on the classifier’s operation.
By the end of this chapter, you will have achieved the following:
- Become familiar with the field of NLP and its applications
- Gained an understanding of the concept of word embeddings and their importance
- Implemented a mystery-word game using word embeddings and created a genetic algorithms-driven player to guess the mystery...
