Top-k相似短文本快速抽取算法-计算机科学与探索.PDF

顾彦慧，赵 斌，周俊生，等.Top-k 相似短文本快速抽取算法[J].计算机科学与探索，2014 ，8（8）：919-932. ISSN 1673-9418 CODEN JKYTA8 E-mail: fcst@vip. 163.com Journal of Frontiers of Computer Science and Technology 1673-9418/2014/08(08)-0919-14 Tel: +86-10 doi: 10.3778/j.issn. 1673-9418.1403053 Top-k 相似短文本快速抽取算法* 1 1 1 1,2+ 顾彦慧 ，赵 斌 ，周俊生 ，曲维光 1. 南京师范大学 计算机科学与技术学院，南京 210023 2. 南京大学 计算机软件新技术国家重点实验室，南京 210023 Efficient Top-k Similar Short Texts Extraction Algorithm 1 1 1 1,2+ GU Yanhui , ZHAO Bin , ZHOU Junsheng , QU Weiguang 1. School of Computer Science and Technology, Nanjing Normal University, Nanjing 210023, China 2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China + Corresponding author: E-mail: wgqu@ GU Yanhui, ZHAO Bin, ZHOU Junsheng, et al. Efficient top-k similar short texts extraction algorithm. Journal of Frontiers of Computer Science and Technology, 2014, 8(8) ：919-932. Abstract: Extracting similar short texts efficiently is an essential research issue for many applications. However, most of the existing strategies focus on the effectiveness aspect. The existing state-of-the-art strategies cannot satisfy the users ’performance requirement while efficiency issue is important especially for current big data applications. This paper addresses the efficiency issue of extracting similar short texts, i.e., how to efficiently get the top-k semantic similar short texts to a query for a give sentence collection. This paper also proposes an efficient strategy to tackle the performance problems based