|
|
|
| Query Expansion Oriented Algorithm of Feature-words Frequent Itemsets Mining |
| Huang Mingxuan1, Ma Ruixing2, Lan Huihong1 |
1. Department of Math and Computer Science, Guangxi College of Education, Nanning 530023, China;
2. Department of Computer Science, Guangxi Economic Mangement Cadre College, Nanning 530007, China |
|
|
|
|
Abstract In this paper, a novel algorithm is proposed to mine feature-words frequent itemsets in text database, in order to obtain high-quality expansion terms for query expansion. This algorithm uses the support to measure the frequent itemsets, and only to mine those frequent itemsets containing original query terms and non- query terms synchronously. It can tremendously enhance the mining efficiency. The experimental results demonstrate that the algorithm is more efficient and more feasible than traditional ones.
|
|
Received: 15 February 2011
Published: 11 June 2011
|
|
|
| [1] Agrawal R, Srikant R. Fast Algorithms for Mining Association Rules[C]. In:Proceedings of the 20th International Conference on Very Large Data Bases.1994:487-499.[2] Han J, Pei J, Yin Y. Mining Frequent Patterns Without Candidate Generation[C]. In:Proceedings of 2000 ACM-SIGMOD International Conference Management of Data (SIGMOD’00).2000: 1-12.[3] Burdick D, Calimlim M, Gehrke J. MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases [C].In:Proceedings of the 17th International Conference on Data Engineering. Heidelberg: IEEE, 2001:443-452.[4] Li Q,Zhou X,Wang L,et al. Mining Maximal Frequent Pattems Using Minimal Combination Algorithm[J].Application Research of Computers,2008,25(3):702-704.[5] 崔贯勋,李梁,王柯柯,等. 关联规则挖掘中Apriori算法的研究与改进[J].计算机应用,2010,30(11):2952-2955.[6] 王强. 基于事务标识列表的关联规则挖掘算法[J]. 现代图书情报技术,2008(8):63-69. [7] Cui H, Wen J R, Nie J Y,et al. Query Expansion by Mining User Logs [J]. IEEE Transactions on Knowledge and Data Engineering, 2003,15(4): 829-839.[8] Zhang C, Qin Z,Yan X. Association-Based Segmentation for Chinese-Crossed Query Expansion [J]. IEEE Intelligent Informatics Bulletin, 2005,5 (1): 18-25. [9] Qin Z, Liu L, Zhang S. Mining Term Association Rules for Heuristic Query Construction[C]. In:Proceedings of the 8th Pacific-Asia Conference(PAKDD 2004).2004: 145-154.[10] Song M, Song I Y,Hu X,et al. Integration of Association Rules and Ontology for Semantic-based Query Expansion[C]. In:Proceedings of the 7th International Congress on Data Warehouse and Knowledge Discovery (DAWAK’05).2005: 326-335.[11]Fonseca B M, Golgher P B, De Moura E S, et al. Discovering Search Engine Related Query Using Association Rules [J]. Journal of Web Engineering,2003, 2(4): 215-227. [12] 黄名选,严小卫,张师超.基于矩阵加权关联规则挖掘的伪相关反馈查询扩展[J].软件学报,2009,20(7):1854-1865.[13] 黄名选,严小卫,张师超. 基于完全加权关联规则的局部反馈查询扩展[J].计算机工程与应用, 2008, 44(7): 190-192. |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
