Lucidworks CTO Grant Ingersoll’s latest column on Opensource.com gives you a rundown on five of the most popular and powerful open source projects for taming text and processing natural language in both queries and indexing. Highlights projects from Stanford and the Apache Software Foundation:

Thankfully, open source is chock full of high-quality libraries to solve common problems in text processing like sentiment analysis, topic identification, automatic labeling of content, and more. More importantly, open source also provides many building block libraries that make it easy for you to innovate without having to reinvent the wheel. If all of this stuff is giving you flashbacks to your high school grammar classes, not to worry—we’ve included some useful resources at the end to brush up your knowledge as well as explain some of the key concepts around natural language processing (NLP). To begin your journey, check out these projects.

Read all of Grant’s columns on Opensource.com or follow him on Twitter.

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