[1]李慧颖,瞿裕忠.基于关键词的RDF数据查询方法[J].东南大学学报(自然科学版),2010,40(2):270-274.[doi:10.3969/j.issn.1001-0505.2010.02.010]
 Li Huiying,Qu Yuzhong.A keyword query approach on RDF data[J].Journal of Southeast University (Natural Science Edition),2010,40(2):270-274.[doi:10.3969/j.issn.1001-0505.2010.02.010]
点击复制

基于关键词的RDF数据查询方法()
分享到:

《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
40
期数:
2010年第2期
页码:
270-274
栏目:
自动化
出版日期:
2010-03-20

文章信息/Info

Title:
A keyword query approach on RDF data
作者:
李慧颖 瞿裕忠
东南大学计算机科学与工程学院, 南京 210096
Author(s):
Li Huiying Qu Yuzhong
School of Computer Science and Engineering, Southeast University, Nanjing 210096, China
关键词:
资源描述框架(RDF) 关键词查询 RDF句子 语义网
Keywords:
resource description framework(RDF) keyword query RDF sentence semantic web
分类号:
TP18
DOI:
10.3969/j.issn.1001-0505.2010.02.010
摘要:
在建立关键词倒排索引和路径索引的基础上,提出一个利用量化均衡规则和等距规则的启发式查询算法,并按照查询结果的大小排序返回最相关的前k个结果.通过建模RDF数据为RDF句子图,将文本信息封装到句子节点,同时将查询结果建模为包括所有查询关键词并且叶节点是关键词节点的无根树,将关键词查询问题转化为斯坦纳树问题.假设RDF句子图包括n个节点,最坏情况下索引占用的空间是3n2.2假设关键词节点数为k,查询算法的时间复杂度为O(kn).该方法不需要依赖RDF数据的模式信息,支持对数据中的属性和关系名进行关键词查询.实验证明该方法能够快速而有效地实现RDF数据的关键词查询.
Abstract:
Based on the keyword inverted-list index and the path index, a heuristic searching algorithm is proposed. The algorithm uses the cost-balanced strategy and the equi-distance strategy to find the top-k answers. Resource description framework(RDF)data is modeled as an RDF sentence graph, and all text information is encapsulated by the sentence nodes. An answer to a keyword query is an RDF sentence tree which contains all the keywords, and all the leaf nodes are relevant to keywords. Therefore, to find a shortest answer tree is a Steiner tree problem. Supposing that there are n nodes in RDF sentence graph, the index space would be 3n2 in the worst case. Supposing that there are k relevant nodes, the time complexity would be O(kn). The proposed approach supports keywords that match attributes and relation contained in the data, without the information of the RDF data schema. The experimental results show that the approach is feasible and effective.

参考文献/References:

[1] Ding L,Finin T.Characterizing the semantic web on the web [C] //Proc of the 5th International Semantic Web Conference,LNCS 4273.Athens,Greece,2006:242-257.
[2] Perez J,Arenas M,Gutierrez C.Semantics and complexity of SPARQL [C] //Proc of the 5th International Semantic Web Conference,LNCS 4273. Athens,Greece,2006:30-43.
[3] Prudhommeaux E,Seaborne A.SPARQL query language for RDF [EB/OL].(2008-01-15)[2009-05-28].http://www.w3.org/TR/rdf-sparql-query/.
[4] Broekstra J.SeRQL:Sesame RDF query language [EB/OL].(2003-04-09)[2009-05-28].http://swap.semanticweb.org/public/Publications/swap-d3.2.pdf.
[5] He H,Wang H,Yang J,et al.Blinks:ranked keyword searches on graphs [C] //Proc of the ACM SIGMOD International Conference on Management of Data. Beijing,China,2007:305-316.
[6] Li G,Ooi B,Feng J,et al.EASE:an effective 3-in-1 keyword search method for unstructured,semi-structured and structured data [C] //Proc of the ACM SIGMOD International Conference on Management of Data. Vancouver,BC,Canada,2008:903-914.
[7] 吴刚,唐杰,李涓子,等.细粒度语义网检索[J].清华大学学报:自然科学版,2005,45(1):1865-1872.
  Wu Gang,Tang Jie,Li Juanzi,et al.Fine-grained semantic web retrieval [J].Journal of Tsinghua University:Science and Technology, 2005,45(1):1865-1872.(in Chinese)
[8] 黄瑞,史忠植.一种新的Web异构语义信息搜索方法[J].计算机研究与发展,2008,45(8):1338-1345.
  Huang Rui,Shi Zhongzhi.A new approach to heterogeneous semantic search on the web [J].Journal of Computer Research and Development,2008,45(8):1338-1345.(in Chinese)
[9] 田萱,杜小勇,李海华.语义查询扩展中词语-概念相关度的计算[J].软件学报,2008,19(8):2043-2053.
  Tian Xuan,Du Xiaoyong,Li Haihua.Computing term-concept association in semantic-based query expansion [J].Journal of Software, 2008,19(8):2043-2053.(in Chinese)
[10] Lei Y,Uren V,Motta E.Semsearch:a search engine for the semantic web [C] //Proc of 15th International Conference on Knowledge Engineering and Knowledge Management,LNCS 4248. Podebrady,Czech Republic,2006:238-245.
[11] Tran T,Cimiano P,Rudolph S,et al.Ontology-based interpretation of keywords for semantic search [C] //Proc of the 6th International Semantic Web Conference and the 2nd Asian Semantic Web Conference,LNCS 4825. Busan,Republic of Korea,2007:523-536.
[12] Wang H,Zhang K,Liu Q,et al.Q2Semantic:a lightweight keyword interface to semantic search [C] //Proc of the 5th Annual European Semantic Web Conference,LNCS 5021. Tenerife,Spain,2008:584-598.
[13] Zhou Q,Wang C,Xiong M,et al.SPARK:adapting keyword query to semantic search [C] //Proc of the 6th International Semantic Web Conference and the 2nd Asian Semantic Web Conference,LNCS 4825. Busan,Republic of Korea,2007:649-707.
[14] Zhang X,Cheng G,Qu Y Z.Ontology summarization based on RDF sentence graph [C] //Proc of the 6th International World Wide Web Conference. Banff,Alberta, Canada,2007:707-715.
[15] Aleman-Meza B,Hakimpour F,Arpinar I B,et al.SwetoDblp ontology of computer science publications [J].Web Semantics:Science,Service and Agents on the World Wide Web,2007,5(3):151-155.

相似文献/References:

[1]周翔,金远平.用于关系数据库关键词查询的基于划分的候选网络生成算法[J].东南大学学报(自然科学版),2012,42(4):609.[doi:10.3969/j.issn.1001-0505.2012.04.006]
 Zhou Xiang,Jin Yuanping.A partition-based candidate network generation algorithm for keyword search on relational databases[J].Journal of Southeast University (Natural Science Edition),2012,42(2):609.[doi:10.3969/j.issn.1001-0505.2012.04.006]

备注/Memo

备注/Memo:
作者简介: 李慧颖(1977—),女,博士生,讲师; 瞿裕忠(联系人),男,博士,教授,博士生导师,yzqu@seu.edu.cn.
基金项目: 国家自然科学基金资助项目(60773106)、江苏省自然科学基金资助项目(BK2008290).
引文格式: 李慧颖,瞿裕忠.基于关键词的RDF数据查询方法[J].东南大学学报:自然科学版,2010,40(2):270-274. [doi:10.3969/j.issn.1001-0505.2010.02.010]
更新日期/Last Update: 2010-03-20