Bindu, M S; Dr.Sumam Mary,Idicula(Cochin University Of Science And Technology, 2012)
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Abstract:
This is a Named Entity Based Question Answering System for Malayalam
Language. Although a vast amount of information is available today in digital
form, no effective information access mechanism exists to provide humans with
convenient information access. Information Retrieval and Question Answering
systems are the two mechanisms available now for information access.
Information systems typically return a long list of documents in response to a
user’s query which are to be skimmed by the user to determine whether they
contain an answer. But a Question Answering System allows the user to state
his/her information need as a natural language question and receives most
appropriate answer in a word or a sentence or a paragraph.
This system is based on Named Entity Tagging and Question Classification.
Document tagging extracts useful information from the documents which will be used
in finding the answer to the question. Question Classification extracts useful
information from the question to determine the type of the question and the way in
which the question is to be answered. Various Machine Learning methods are used to
tag the documents. Rule-Based Approach is used for Question Classification.
Malayalam belongs to the Dravidian family of languages and is one of the
four major languages of this family. It is one of the 22 Scheduled Languages of
India with official language status in the state of Kerala. It is spoken by 40 million
people. Malayalam is a morphologically rich agglutinative language and relatively
of free word order. Also Malayalam has a productive morphology that allows the
creation of complex words which are often highly ambiguous.
Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker,
Named Entity Tagger, and Compound Word Splitter are developed as a part of
this research work. No such tools were available for Malayalam language. Finite
State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the
design of these document preprocessing tools.
This research work describes how the Named Entity is used to represent
the documents. Single sentence questions are used to test the system. Overall
Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be
extended in several directions. The coverage of non-factoid questions can be
increased and also it can be extended to include open domain applications.
Reference Resolution and Word Sense Disambiguation techniques are suggested as
the future enhancements
Description:
Dept. Of Computer Science
Cochin University Of Science And Technology