This paper reports the authors' TREC 2005 QA participation. The authors' QA system Eagle QA developed last year was expanded and modified for this year's QA experiments. Particularly, the authors used Lemur 4.1 as the Information Retrieval (IR) Engine this year to find documents that may contain answers for the test questions from the document collection. The authors' result shows Lemur did a reasonable job on finding relevant documents. But certainly there is room for further improvement.
Situated at the intersection of people, technology, and information, the College of Information's faculty, staff and students invest in innovative research, collaborative partnerships, and student-centered education to serve a global information society. The college offers programs of study in information science, learning technologies, and linguistics.
This paper reports the authors' TREC 2005 QA participation. The authors' QA system Eagle QA developed last year was expanded and modified for this year's QA experiments. Particularly, the authors used Lemur 4.1 as the Information Retrieval (IR) Engine this year to find documents that may contain answers for the test questions from the document collection. The authors' result shows Lemur did a reasonable job on finding relevant documents. But certainly there is room for further improvement.
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