That return data conforming to a well-defined schema are essential, but the This chapter employs different techniques that are more context-drivenĪnd delves deeper into the semantics of human language data. Remarkably well in many circumstances, a recurring shortcoming is that theyĭo not maximize cues from the immediate context that ground words in Information retrieval (IR) theory, which generally treats text asĭocument-centric “bags of words” (unordered collections of words) that canīe modeled and manipulated as vectors. The previous chapter introduced some foundational techniques from It to the vast source of human language data that you’ll encounter on the social web (or elsewhere). Is a modest attempt to introduce natural language processing (NLP) and apply This chapter follows closely on the heels of the chapter before it and Human Language, Summarize Blog Posts, and More Chapter 5. Mining Web Pages: Using Natural Language Processing to Understand
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