Re-ranking model based on document clusters |
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| Institution: | 1. Division of Computer Science, Department of Electrical Engineering & Computer Science, Korea Advanced Institute of Science and Technology, KORTERM, 373-1 Kusung Yusong Taejon, 305-701 South Korea;2. K4 M (Knowledge for the New Millennium), Taejon, South Korea;1. DESTEC, School of Engineering University of Pisa Largo, Lucio Lazzarino 2, 56125 Pisa, Italy;2. ANVUR Italian Agency for the Evaluation of Universities and Research Institutes, Via Ippolito Nievo 35, 00153 Rome, Italy;1. Department of Rehabilitation Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, Shaanxi, China;2. Emergency Department, Hanzhong Central Hospital, Hanzhong 723000, Shaanxi, China;3. Beijing Meinuoyikang Health Food Co., Ltd., Beijing 100000, China;4. Second Department of Orthopedics, The First Central Hospital of Baoding, No. 320 North Great Wall Street, Baoding 071000, Hebei, China;5. Department of Orthopedics, The First Hospital of Lanzhou University, No. 1 West Gang Road, East District, Lanzhou 730000, Gansu, China;1. School of Mechanical Engineering, Xi’an Jiaotong University, 28 West Xianning Road, Xi’an 710049, PR China;2. School of Chemical Engineering and Technology, Xi’an Jiaotong University, 28 West Xianning Road, Xi’an 710049, PR China;3. Shaanxi Province Boiler and Pressure Vessel Inspection Institute, 30 West Xianning Road, Xi’an 710048, PR China;4. School of Chemical Engineering, Northwest University, 229 North Taibai Road, Xi’an 71006, PR China |
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| Abstract: | In this paper, we describe a model of information retrieval system that is based on a document re-ranking method using document clusters. In the first step, we retrieve documents based on the inverted-file method. Next, we analyze the retrieved documents using document clusters, and re-rank them. In this step, we use static clusters and dynamic cluster view. Consequently, we can produce clusters that are tailored to characteristics of the query. We focus on the merits of the inverted-file method and cluster analysis. In other words, we retrieve documents based on the inverted-file method and analyze all terms in document based on the cluster analysis. By these two steps, we can get the retrieved results which are made by the consideration of the context of all terms in a document as well as query terms. We will show that our method achieves significant improvements over the method based on similarity search ranking alone. |
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