Please wait a minute...
浙江大学学报(工学版)
J4  2010, Vol. 44 Issue (12): 2274-2283    DOI: 10.3785/j.issn.1008-973X.2010.12.008
自动化技术、计算机技术     
词法多重散列与包容语义相结合的服务查找
傅朝阳1,2, 高济1, 周尤明1
1.浙江大学 人工智能研究所,浙江 杭州 310027； 2.苏州科技学院 电子系,江苏 苏州 215011
Service discovery based on integrating lexical multi-level hashing
with subsumption semantics
FU Chao-yang1,2, GAO Ji1, ZHOU You-ming1
1. Institute of Artificial Intelligence, Zhejiang University, Hangzhou 310027, China; 2. Electronic Department,
Suzhou University of Science and Technology, Suzhou 215011, China
 全文: PDF  HTML
摘要：

为进一步提升服务组合性能,提出将词法多重散列与包容语义相结合的快速服务查找法.该方法有如下特点：将服务描述模型分解为不同粒度的词法和语义子块,同时将服务查找过程转换为按词法子块粒度递增的多重散列过程,利用子块间的包容语义消解散列冲突,实现降低查找失败时间至最低；所建立的服务库一方面通过缩减服务组合路径搜索空间降低查找成功时间,另一方面为设计高效组合路径查找算法提供了基础；可提供近似常数时间的原子服务查找和服务建库过程.实验证明该方法查找准确,较当前权威组织提供的基准服务查找方法效率提升显著,并具有查找时间几乎与服务库规模无关的良好稳定性.
Abstract:

A method of fast service discovery based on integrating lexical multi-level hashing with subsumption semantics was presented to promote the performance of service composition. This method decomposes the service description into both lexical and semantic blocks of different granularity, and transforms the process of traditional discovery into a multilevel hashing in term of the ascending order by the granularity of lexical blocks. The subsumption semantics of blocks is utilized to resolve the collision during hashing, and the time for failed discoveries is reduced to the lowest. The service repository constructed accordingly can be used to decrease both the searching space of service composition paths and the time of succeeded service discoveries, and can provide an infrastructure for effective composition algorithm. This method has a nearly-constant time complexity for both atomic service searching and repository constructing. Experiments showed that both the time complexity and the accuracy of this service discovery is improved significantly compared to the benchmark one approbated by a current authority organization, and almost independent of with the size of service repository.
出版日期: 2010-12-01
:  TP 311  
基金资助:

国家“973”重点基础研究发展规划资助项目(2003CB317005)；国家“863”高技术研究发展计划资助项目(2007AA01Z187)；国家自然科学基金资助项目(60775029)；浙江省自然科学基金资助项目（Y1090734）.
通讯作者: 高济,男,教授，博导.     E-mail: gaoji@mail.hz.zj.cn
作者简介: 傅朝阳（1977—）,男,江苏泗阳人,博士生,讲师,从事服务计算、MultiAgent系统、模态逻辑、模型检测等研究.E-mail:zhaoyangfu@gmail.com
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章　　

引用本文:

傅朝阳, 高济, 周尤明. 词法多重散列与包容语义相结合的服务查找[J]. J4, 2010, 44(12): 2274-2283.

FU Chao-yang, GAO Ji, ZHOU You-ming. Service discovery based on integrating lexical multi-level hashing
with subsumption semantics. J4, 2010, 44(12): 2274-2283.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2010.12.008    或    http://www.zjujournals.com/eng/CN/Y2010/V44/I12/2274

［1］ KLIE T, GEBHARD F, FISCHER S. Towards automatic composition of network management web services［C］∥ Proc of 10th IFIP/IEEE International Symposium on Integrated Management (IM). Munich: IFIP/IEEE, 2007: 769-772.
［2］ BENDICK MAHLEKO, ANDREAS WOMBACHER,PETER FANKHAUSER. Processannotated service discovery facilitated by an nGramBased Index［C］∥ Proceedings of the 2005 IEEE International Conference on eTechnology, eCommerce and eService (EEE’05). Washington, DC: IEEE Computer Society,2005: 2-8.
［3］ SYEDAMAHMOOD T,SHAHGAKKIRAJU R. Searching service repositories by combining semantic and ontological matching［C］∥ Proceedings of the IEEE International Conference on Web Services. Orlando: IEEE Computer Society,2005: 13-20.
［4］ 刘家茂,顾宁,施伯乐.基于Mediator的web services无回溯反向链动态合成［J］.计算机研究与发展,2005,42(7): 1153-1158.
LIU Jiamao,GU Ning, SHI Baile. Nonbacktrace backward chaining dynamic composition of web services based on mediator［J］. Journal of Computer Research and Development, 2005,42(7): 1153-1158.
［5］AIELLO MARCO,PLATZER CHRISTIAN,ROSENBERG FLORIAN, et al. Web service indexing for efficient retrieval and composition［C］∥ Proceedings of the the 8th IEEE International Conference on ECommerce Technology and The 3rd IEEE International Conference on Enterprise Computing, ECommerce, and EServices. San Francisco: IEEE Computer Society, 2006:63.
［6］ GEORGETOWN UNIVERSITY. The web service challenge［EB/OL］.［2009-05-16］..http:∥wschallenge.georgetown.edu/wschallenge/WSChallenge.htm.
［7］ ZHENG Xianrong, YAN Yuhong. An efficient syntactic web service composition algorithm based on the planning graph model［C］∥ Proceedings of the 2008 IEEE International Conference on Web Services. Beijing: IEEE Computer Society,2008: 691-699.
［8］ KUSTER U,STERN M,KONIGRIES B.A classification of issues and approaches in automatic service composition. ［EB/OL］.［2010-02-26］.http:∥citeseerx.ist.psu.edu/viewdoc/download？doi=10.1.1.91.438&rep=rep1&type=pdf.
［9］ HU S, MUTHUSAMY V, LI G, et al. Distributed automatic service composition in largescale systems［J］. Distributed Eventbased Systems,2008,32(06): 233-244
［10］ KONA S, BANSAL A, GUPTA G. Automatic composition of semantic web services［C］∥ In IEEE International Conference on Web Services. Utah: IEEE Computer Society,2007: 150-158.
［11］ OH SEOGCHAN, LEE DONGWON, SOUNDAR R T KUMARA. A comparative illustration of AI planningbased web services composition［J］. ACM SIGecom Exchanges,2006,5(5): 1-10.
［12］ WANG Rui, YU Xuili, LI Yingjie, et al. Behavior analysis based automatic composition of semantic web services［C］∥ Advances in Intelligent Web Mastering: Proceedings of the 6th Atlantic Web Intelligence Conference. Prague: Springer, 2007, 43: 357-362.
［13］ SWS CHANLLENGE WIKI. Semantic web service challenge: evaluating semantic web services mediation, choreography and discovery［OB/OL］. ［2009-05-16］.http:∥swschallenge.org/.
［14］ NONAKA I,TAKEUCHHI H. The knowledge creating company［M］. Oxford, UK: Oxford University Press, 1995.
［15］ NAICS ASSOCIATION. NAICS Code［OB/OL］.  ［2009-05-16］.http:∥www.naics.com/.
［16］ COMEN T H, LEISERSON C E, RIVEST R L, et al. Introduction to algorithms［M］. Cambridge, MA:MIT Press, 2001: 245-247,225-228.
［17］ SYCARA K, WIDOFF S, KLUSCH M, et al. Larks: dynamic matchmaking among heterogeneous software agents in cyberspace［J］.Autonomous Agents and Multiagent Systems,2002,5(2): 173-203.
［18］ 高济.支持创新型组织学习：基于任务情景的知识适用性管理［J］.计算机学报,2007,30(9): 1533-1543.
GAO Ji. Supporting creative organizational learning: knowledge applicability management based on task circumstance［J］.Chinese Journal of Computers, 2007,30(9): 1533-1543.
［19］ KUSTER U, KONIGRIESO B. On the empirical evaluation of semantic web service approaches: towards common SWS test collections［C］∥ Proceedings of the 2008 IEEE International Conference on Semantic Computing. Santa Clara:IEEE Computer Society,2008: 339-346.
［20］ TABATABAEI S G H, KADIR W M N W, IBRAHIM SUHAIMI. An evaluation of current approaches for Web service composition［C］∥ Information Technology, 2008. ITSim 2008. International Symposium on.Kuala Lumpur: IEEE Computer Society,2008: 1-9.
[1] 柯海丰,应晶. 基于R-ELM的实时车牌字符识别技术[J]. J4, 2014, 48(2): 0-0.
[2] 金苍宏,吴明晖,应晶. 一种基于上下文索引的文本匹配框架[J]. J4, 2013, 47(9): 1537-1546.
[3] 朱凡微, 吴明晖, 应晶. 面向大规模无结构数据的Web方面搜索方法[J]. J4, 2013, 47(6): 990-999.
[4] 冯培恩, 刘屿, 邱清盈, 李立新. 提高Eclat算法效率的策略[J]. J4, 2013, 47(2): 223-230.
[5] 刘颖, 陈岭, 陈根才, 赵江奇, 王敬昌. 基于历史点击数据的集合选择方法[J]. J4, 2013, 47(1): 23-28.
[6] 殷婷,肖敏,陈岭,赵江奇,王敬昌. 基于CQPM的OLAP查询日志挖掘及推荐[J]. J4, 2012, 46(11): 2052-2060.
[7] 肖敏, 陈岭, 夏海元, 陈根才. 基于数据仓库内在特征的OLAP关键词查询[J]. J4, 2012, 46(6): 974-979.
[8] 张丽平,李松,郝晓红,郝忠孝. Jrv粗糙Vague区域关系[J]. J4, 2012, 46(1): 105-111.
[9] 陈岭,许晓龙,杨清,陈根才. 基于三次样条插值的无线信号强度衰减模型[J]. J4, 2011, 45(9): 1521-1527.
[10] 吴明晖, 应晶. 业务过程建模及其形式化验证[J]. J4, 2011, 45(2): 280-287.
[11] 杨清, 陈岭, 陈根才. 基于单加速度传感器的行走距离估计[J]. J4, 2010, 44(9): 1681-1686.
[12] 熊伟, 王晓暾. 基于质量功能展开的可信软件需求映射方法[J]. J4, 2010, 44(5): 881-886.
[13] 张引, 何浩, 赵丽娜, 张三元. 网构软件模型中的抽象状态机设计[J]. J4, 2010, 44(5): 923-929.
[14] 沈斌, 姚敏. 关联且项项正相关频繁模式挖掘[J]. J4, 2009, 43(12): 2171-2177.
[15] 蒋涛, 应晶, 吴明晖, 等. 一种面向特征增量的软件产品线分析方法[J]. J4, 2009, 43(12): 2142-2148.