Advantages
- Enterprises use NLP technology for streamlining their documentation processes
- NLP can be used for better on-site search, as it provides more accurate search results while mining through more data by deciphering exactly what the user wants to look for on a website
- In the healthcare industry, NLP helps doctors better understand patients with mental illnesses. Additionally, NLP can be used for analyzing health records and finding correlations between symptoms and diagnostics
- NLP can automatically translate full sentences from one language to another and it can do so even if a sentence has typos while understanding the context
Disadvantages
- When it comes to spoken language, NLP systems still have trouble understanding accents
- NLP is an expensive technology, which requires a lot of computing power
- NLP programs have low accuracy upon implementation and they still have to undergo various types of training before providing error-free results
Components
- Grammatical rules
- Definitions and dictionary
- Part-of-speech
- Entity extraction
- Syntactic analysis
- Semantic analysis
- Sentiment analysis
- Pragmatic analysis
- Output processing
Development tools
- Apache OpenNLP
- Solr
- Natural Language Toolkit (NLTK)
- Stanford Core NLP Suite
- Apache Lucene
- GATE
- Apache UIMA
- MALLET
- MaltParser
- Kyfd
- SRILM
- Travatar
- Chasen
- CMU Sphinx
