초록

AI-Helper

검색 시스템들의 평가를 위해 국내에서도 테스트 컬렉션에 관한 여러 연구가 진행되어왔다. 그러나 그 규모나 대상 분야가 편중되어 있고 질의 및 문헌 특성의 균형 등에 대한 고려가 반영되어 있지 않아 평가 결과를 객관화하기는 사실상 어려운 실정이다. 본 논문에서는 분야별, 사용자별 균형을 고려한 대규모 테스트 컬렉션인 HANTEC에 대해 기술한다. HANTEC 테스트 컬렉션은 총 12만 건의 문헌집합으로 구성되었는데 일반, 사회과학, 과학기술 각 분야별 4만 건씩으로 특정 분야에 편중되지 않도록 하였고 질의집합도 각 분야별 10개씩 30개로 구성하였다.

Abstract ▼ AI-Helper

There has been some research in Korea on test collections for evaluation of information retrieval (IR) systems. The test collections constructed as an outcome from the research have provided a starting point and opportunities to test Korean IR systems in an objective manner. However, they are well s...

There has been some research in Korea on test collections for evaluation of information retrieval (IR) systems. The test collections constructed as an outcome from the research have provided a starting point and opportunities to test Korean IR systems in an objective manner. However, they are well short of the standard practice in the broader IR community in that they are small in their size and usually unbalanced in terms of the characteristics of the documents and the queries (such as the subject domains). In this article, we describe our research effort to alleviate this problem and the resulting test collection, called HANTEC (Hangul TEst Collection). HANTEC is balanced in terms of the subject domains, document lengths, and user types, and currently consists of 120,000 documents divided into three groups: general area, social science area and scienceltechnology area. The 30 queries in the collection are grouped into the same three areas in one dimension and into three distinct user groups in the other dimension.