I will classify the problems in Natural Language Processing into 3 categories :
1. Easy or mostly solved
- Spam detection
- Part of Speech Tagging - Example
INPUT:
Profits soared at Boeing Co., easily topping forecasts on Wall Street, as
their CEO Alan Mulally announced first quarter results.
OUTPUT:
Profits/N soared/V at/P Boeing/N Co./N ,/, easily/ADV topping/V forecasts/
N on/P Wall/N Street/N ,/, as/P their/POSS CEO/N Alan/N Mulally/
N announced/V first/ADJ quarter/N results/N ./.
KEY: N = Noun, V = Verb, P = Preposition, Adv = Adverb
- Named Entity Recognition - Example
INPUT:
Profits soared at Boeing Co., easily topping forecasts on Wall Street, as
their CEO Alan Mulally announced first quarter results.
OUTPUT:
Profits/NA soared/NA at/NA Boeing/SC Co./CC ,/NA easily/NA topping/
NA forecasts/NA on/NA Wall/SL Street/CL ,/NA as/NA their/NA CEO/NA
Alan/SP Mulally/CP announced/NA first/NA quarter/NA results/NA ./NA
KEY: NA = No entity, SC = Start Company, CC = Continue Company, SL = Start Location, CL = Continue Location
2. Intermediate or making good progress
- Sentiment analysis- Example:
Best roast chicken in San Francisco! -- Positive
The waiter ignored us for 20 minutes. -- Negative
- Coreference resolution - Example: "Carter told Mubarak he shouldn't run again." To solve whether "he" is related to "Carter" or "Mubarak".
- Word sense disambiguation - Example :
I need new batteries for my mouse. - "mouse" is ambiguous here.
- Parsing - the basic problem of parsing sentences.
- Machine Translation - translating sentences from one language to another, best example would be Google translate.
- Information Translation - to take a text as input and represent it in a structured form like a database entries.
3. Hard or still need lot of work
- Text Summarization - to take input as text document(s) and try to condense them into a summary.
- Machine dialog system - Example:
User - I need a flight from New York to London, arriving at 10 pm ?
System - What day are you leaving?
User - Tomorrow.
System detects the missing information in your sentences.
