ANSWER EXTRACTION

Answer extraction or Question Answering (QA) is a way of information retrieval. When a quantity of documents is given, the system should be able to answer questions written in natural language. QA needs a more complicated technology of natural language processing than other types of document retrieval.

Question answering systems are one of the most complicated systems in the information retrieval, because this system has to find a fragment of text that answers to the question made in natural language. This systems have to recognise questions like who, how, why, ..

A good QA system needs a good search engine that selects the documents that contain the answer. If we are searching in the web, where we have lots of documents, it common to find parts of the answer in different documents, but this has its benefits, because we can choose the answers that appear more.

We have two different methods, deep and shallow.

Shallow: Some methods use keyword techniques to find passages and sentences in documents and filter based on the presence of the desired answer. They made the ranking based on syntactic characteristics like word order.

Deep: Sometimes using keyword searching is not enough, and we need to use the system that include named-entity recognition, word sense disambiguation,… If the question done is why or how, we will also need this system.

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retrieved from, wikipedia the free encylcopedia, sep. 05, 10:51