Littera Deusto

Modern Languages, Basque Studies and Humanities

Question answering systems (3rd Questionnaire)

abril 4th, 2009 · No hay Comentarios

When we search for information on the net we can obtain it from different places and in different ways, for there is loads of available data on the internet.

Question answering, also known as QA, is a way of getting that information; this system should be able to answer our questions (done in natural language), searching in pre-structured database or documents written in natural language.

As Dell Zhang and Wee Sun Lee wrote in one article “it is important for an online question answering system to be practical, because it is time-consuming to download and analyze the original web documents”. A question answering system is another information retrieval system, but what QA systems do is supply just the information we need, not a list of possibilities as searching engines usually do. To obtain the answers, the QA systems combine some NLP techniques, because the answer depends on the type of question.

And as I have told, depending on the question, the methods used to find the answers are different. There are two methods: shallow and deep. The first one finds fragments of documents, filters the information based on the presence of the answer required, and then the answers are ordered based on different criteria, such as word order. If the way the question is formulated is not enough (or, for example, some of the questions based are classified with an incorrect type), the second method is used. “More sophisticated syntactic, semantic and contextual processing must be performed to extract or construct the answer”.

So, there have been many advances on this kind of information retrieval systems, but dealing with Natural Language with computers is quite difficult, and it can be hard to get the data we are looking for using that kind of language with systems that have to improve a lot.

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