 Christopher D. Manning

Christopher D. Manning is a researcher in natural language processing whose work connects linguistic structure with statistical and neural methods. Stanford's institutional biography identifies contributions to learned word representations, language understanding and computational analysis of sentence structure.^[ref]

He is a coauthor of Introduction to Information Retrieval by Christopher D. Manning and others. The book gives precise mathematical formulations of problems that arise when a system retrieves documents in response to a query. This connects an algorithm's output to a measurable task instead of evaluating it only by a few convincing examples.^[ref]

For instance, suppose a query has twelve relevant documents, and a system returns ten documents of which six are relevant. Its precision is $6/10=0.6$, while its recall is $6/12=0.5$. Returning more documents can change the two measures differently. This example illustrates the distinction between making useful predictions and choosing a reproducible way to evaluate them, a recurring issue in natural language processing.