| dc.description.abstract | Recent development on Question Answering System (QAS) can accommodate language modeling mechanism for generating a better result. To develop the system, we use Indri Framework toolkit in order to obtain robust document structure and text passages. Documents relevant to a question are first retrieved. The relevant documents are then divided into passages of 2 sentences each. In order to obtain candidate of answers, n-gram weighting is performed in the passage which is contained on the top document. The answer is identified based on matching annotations between the query and the document. One thousand documents and 40 queries are used in the experiment. The result of the experiment indicates 60% of correctness for who questions, 30% of correctness for how much/many questions, 90% of correctness for where question and 80% of correctness for when questions. Our results shows that we need to find ways to improve the effectiveness in finding correct answers, in particular, ways of reducing the number incorrect word tagging. | en |
