Natural Language Processing. Rada Mihalcea. Fall 2011. Any Light at The End of The Tunnel ?. Yahoo, Google, Microsoft Information Retrieval Monster.com, HotJobs.com (Job finders) Information Extraction + Information Retrieval Systran powers Babelfish Machine Translation
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Internet = at least 20 billions pages
Applications for processing large amounts of texts
Classify text into categories
Index and search large texts
Understand phone conversations
Extract useful information from resumes
Condense 1 book into 1 page
Text generations / dialoguesWhy Natural Language Processing ?
Natural Language Processing
“the dog ate my homework” - Who did what?
Dog = noun ; ate = verb ; homework = noun
English POS tagging: 95%
2. Identify collocations
mother in law, hot dog
Compositional versus non-compositional collocates
“the dog chased the bear”
“the dog” “chased the bear”
subject - predicate
Identify basic structures
NP-[the dog] VP-[chased the bear]
Help figuring out (automatically) questions like: Who did what
“The dog entered my room. It scared me”
“I saw the man in the park with a telescope”
plant, works, industrial plant -- (buildings for carrying on industrial labor; "they built a large plant to manufacture automobiles")
plant, flora, plant life -- (a living organism lacking the power of locomotion)
They are producing about 1,000 automobiles in the new plant
The sea flora consists in 1,000 different plant species
The plant was close to the farm of animals.