基于简单本体的农业P2P搜索引擎关键技术研究
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摘要
随着互联网上资源爆炸式的增长,越来越多的网络用户依靠专门的检索工具,如Google、Yahoo!、Baidu等搜索引擎来查找自己所需的信息。这些站点在帮助用户快速找到所需信息的同时,也取得了巨大的商业成功。通常情况下,搜索引擎首先从数以百万计的网站中检索相关网页,并将它们存储在文件服务器中,然后通过分析这些下载页面来建立索引,搜索引擎使用生成的索引来定位网页中的所有查询关键字,并根据某些具体的相关函数返回最恰当的内容。从逻辑体系架构上分析,目前大型网络搜索引擎都是集中式的,而其检索的站点遍布世界每一个角落,拥有其自身的索引和查询处理机制,所以搜索引擎的扩展性、覆盖率、安全性和专业性等问题将是其在成功路上面临的巨大挑战。
本文针对集中式搜索引擎存在的问题,利用基于P2P网络的分布式搜索引擎。即面向两种不同的拓扑结构——结构化P2P网络和非结构化P2P网络——分别采用了相应的检索方法,通过潜在语义索引对两种检索机制的结果进行聚类合并,论文同时将这几种关键技术应用到基于简单本体的农业搜索引擎系统中。
具体而言,论文的研究内容主要包括：
(1)论文以《农业科学叙词表》为基础,使用本体编辑器protege进行简单农业本体的构建,并通过设计算法,实现词表向本体的大批量自动转化。
(2)论文提出了一种基于简单本体的农业P2P搜索引擎的体系框架PSAOS (P2P Search Engines Based on Agriculture Ontology System, PSAOS),构建一个基于简单农业本体的、全局的分布式索引目录(Index Directory),构建在P2P网络之上,用来保存聚合、压缩节点索引的元信息,以及对农业本体中各位类建立联系,提供依据。
(3)论文主要基于P2P的两种网络拓扑结构,分别采用不同的方法来面向结构化网络和非结构化网络进行检索。
针对结构化P2P网络,本文采用了一种自适应索引检索方法,将Chord环和平衡树相结合,通过统计树结构的检索词的个数并按其重要性适当分类,Chord环用来对树上的结点进行索引。在树结构中,根据词的权重,结点将词语划分为重点词语和非重点词语两类,具有较高分值的词语可用来区分孩子结点与邻居结点,故需要在Chord环中建立索引,并链接到相应的结点。剩下的,无论是高频词还是低频词,都将进行汇总,并传递给父亲结点。这种方法可从任一结点对查询请求进行处理,而不必每次都从根结点开始。因此,即使这种方法采用一种树状结构,也不用担心在根结点或根结点附近的瓶颈问题。
针对非结构化P2P网络,本文将向量空间模型(VSM)和相关性排序算法相结合来构造层叠网络,利用基于语义组的K阶迭代方法进行检索,这种方法有效地解决了检索的效率和查准率低下的问题,降低了系统的检索成本。
(4)在分布式搜索引擎中,每个查询请求被转发给多个结点；然后根据结果相关度的大小进行排序,合并成一个结果列表。由于各结点所处的网络拓扑结构不同,采用的检索机制也有所差异,所以从各节点返回的信息文档不能够直接用于比较合并。
针对此问题,本文采用一种对检索结果进行聚类的方法,利用潜在语义索引对整篇文档进行聚类,采用Apache Lucene作为索引引擎,利用Spring Rich客户端平台进行聚类引擎测试,取得了比较理想的结果。
本文研究的系统,利用JAVA JDK1.5模拟出P2P网络,每个结点用一组IP地址和端口号来表示,模拟器用几个参数来控制网络的不同属性。通过与同类方法的试验结果对比,本文的方法在查全率,查准率及查询延迟等方面都具有明显的优势。
With the explosive growth of resources on the Internet, more and more internet users rely on specialized search tools, such as Google, Yahoo, Baidu and other search engines to retrieval the information they want. Normally, the search engine firstly retrieves relevant web pages from the hundreds of sites and stores them in a file server. By analyzing the pages and indexing, search engine uses the generated index to locate all query keywords in the web, and returns the most appropriate content according to some specific function. From the analysis of the logical architecture, Large-scale Web search engines are centralized and the sites are spread all over corner of the world, which has its own indexing and query processing mechanism. Therefore, it is a great challenge in the way to success for the search engine with scalability, coverage, security and professionalism.
For the problems of the centralized search engine, this paper proposes a distributed search engine based on P2P network. That is separately proposing the retrieval methods for two different topologies, structured P2P network and unstructured P2P network, and clustering and merging the results of two retrieval mechanisms by latent semantic indexing. This paper applies the several of the key technology to the agricultural search engine system based on a simple ontology.
Specifically, the results of the research in this article mainly include the following aspects:
(1) This paper is based on "Agricultural Sciences Thesaurus", using the ontology editor protege to construct the simple agricultural ontology, and designing an algorithm to convert the vocabulary to the ontology in large quantities.
(2) This paper presents a framework of P2P search engines based on agriculture ontology system and builds a global distributed index directory based on simple agricultural ontology on top of the P2P network, which is used to save the meta information of the node index, establish contact with the Class of agricultural ontology and provide a basis for system.
(3) The research of this paper is based on two network topology of P2P, using different methods for structured network and unstructured network to retrieve.
For structured P2P network, this paper presents an adaptive index retrieval method, combines a Chord ring and a balanced tree. It statistics the number of the search terms in the tree structure and classify the terms with their importance, while the chord ring is used to index terms of nodes in the tree. Specifically, at each node of the tree, the system classifies terms as either important or unimportant. Important terms, which can distinguish the node from its neighbor nodes, are indexed in the Chord ring. On the other hand, unimportant terms, which are either popular or rare terms, are aggregated to the parent node. This method can be carried out from any node on the query request, while not always have to start from the root. Therefore, even using a tree structure, it is not worried about bottlenecks in the root and nearby.
For unstructured P2P network, it takes an algorithm of merging the vector space model (VSM) and relevance ranking to construct the overlay network, which is used K-iteration preference based on semantic group to retrieval. This method effectively solves the problem of retrieval efficiency and precision, and reduces the cost of system of retrieval.
(4) In a distributed search engine, each query request is forwarded to a plurality of nodes, then sorted the results according to the size of the degree of correlation and combined into a results list. Each node with the different network topology has a difference retrieval mechanism. The document returned from each node can not be directly used to compare and merge.
To solve this problem, this paper uses take a method of search results clustering, which uses latent semantic indexing on the whole document content, takes Apache Lucene as the indexing engine, uses spring rich client platform for clustering engine test and obtains more satisfactory results.
In this paper, the system uses Java JDK1.5to analog the P2P networks, in which each node is indicated with a set of IP address and port number and the simulator uses several parameters to control the different properties of the network. In contrast to the similar methods with the experimental results, the method has obvious advantages in the recall, precision and query latency.
本文针对集中式搜索引擎存在的问题,利用基于P2P网络的分布式搜索引擎。即面向两种不同的拓扑结构——结构化P2P网络和非结构化P2P网络——分别采用了相应的检索方法,通过潜在语义索引对两种检索机制的结果进行聚类合并,论文同时将这几种关键技术应用到基于简单本体的农业搜索引擎系统中。
具体而言,论文的研究内容主要包括：
(1)论文以《农业科学叙词表》为基础,使用本体编辑器protege进行简单农业本体的构建,并通过设计算法,实现词表向本体的大批量自动转化。
(2)论文提出了一种基于简单本体的农业P2P搜索引擎的体系框架PSAOS (P2P Search Engines Based on Agriculture Ontology System, PSAOS),构建一个基于简单农业本体的、全局的分布式索引目录(Index Directory),构建在P2P网络之上,用来保存聚合、压缩节点索引的元信息,以及对农业本体中各位类建立联系,提供依据。
(3)论文主要基于P2P的两种网络拓扑结构,分别采用不同的方法来面向结构化网络和非结构化网络进行检索。
针对结构化P2P网络,本文采用了一种自适应索引检索方法,将Chord环和平衡树相结合,通过统计树结构的检索词的个数并按其重要性适当分类,Chord环用来对树上的结点进行索引。在树结构中,根据词的权重,结点将词语划分为重点词语和非重点词语两类,具有较高分值的词语可用来区分孩子结点与邻居结点,故需要在Chord环中建立索引,并链接到相应的结点。剩下的,无论是高频词还是低频词,都将进行汇总,并传递给父亲结点。这种方法可从任一结点对查询请求进行处理,而不必每次都从根结点开始。因此,即使这种方法采用一种树状结构,也不用担心在根结点或根结点附近的瓶颈问题。
针对非结构化P2P网络,本文将向量空间模型(VSM)和相关性排序算法相结合来构造层叠网络,利用基于语义组的K阶迭代方法进行检索,这种方法有效地解决了检索的效率和查准率低下的问题,降低了系统的检索成本。
(4)在分布式搜索引擎中,每个查询请求被转发给多个结点；然后根据结果相关度的大小进行排序,合并成一个结果列表。由于各结点所处的网络拓扑结构不同,采用的检索机制也有所差异,所以从各节点返回的信息文档不能够直接用于比较合并。
针对此问题,本文采用一种对检索结果进行聚类的方法,利用潜在语义索引对整篇文档进行聚类,采用Apache Lucene作为索引引擎,利用Spring Rich客户端平台进行聚类引擎测试,取得了比较理想的结果。
本文研究的系统,利用JAVA JDK1.5模拟出P2P网络,每个结点用一组IP地址和端口号来表示,模拟器用几个参数来控制网络的不同属性。通过与同类方法的试验结果对比,本文的方法在查全率,查准率及查询延迟等方面都具有明显的优势。
With the explosive growth of resources on the Internet, more and more internet users rely on specialized search tools, such as Google, Yahoo, Baidu and other search engines to retrieval the information they want. Normally, the search engine firstly retrieves relevant web pages from the hundreds of sites and stores them in a file server. By analyzing the pages and indexing, search engine uses the generated index to locate all query keywords in the web, and returns the most appropriate content according to some specific function. From the analysis of the logical architecture, Large-scale Web search engines are centralized and the sites are spread all over corner of the world, which has its own indexing and query processing mechanism. Therefore, it is a great challenge in the way to success for the search engine with scalability, coverage, security and professionalism.
For the problems of the centralized search engine, this paper proposes a distributed search engine based on P2P network. That is separately proposing the retrieval methods for two different topologies, structured P2P network and unstructured P2P network, and clustering and merging the results of two retrieval mechanisms by latent semantic indexing. This paper applies the several of the key technology to the agricultural search engine system based on a simple ontology.
Specifically, the results of the research in this article mainly include the following aspects:
(1) This paper is based on "Agricultural Sciences Thesaurus", using the ontology editor protege to construct the simple agricultural ontology, and designing an algorithm to convert the vocabulary to the ontology in large quantities.
(2) This paper presents a framework of P2P search engines based on agriculture ontology system and builds a global distributed index directory based on simple agricultural ontology on top of the P2P network, which is used to save the meta information of the node index, establish contact with the Class of agricultural ontology and provide a basis for system.
(3) The research of this paper is based on two network topology of P2P, using different methods for structured network and unstructured network to retrieve.
For structured P2P network, this paper presents an adaptive index retrieval method, combines a Chord ring and a balanced tree. It statistics the number of the search terms in the tree structure and classify the terms with their importance, while the chord ring is used to index terms of nodes in the tree. Specifically, at each node of the tree, the system classifies terms as either important or unimportant. Important terms, which can distinguish the node from its neighbor nodes, are indexed in the Chord ring. On the other hand, unimportant terms, which are either popular or rare terms, are aggregated to the parent node. This method can be carried out from any node on the query request, while not always have to start from the root. Therefore, even using a tree structure, it is not worried about bottlenecks in the root and nearby.
For unstructured P2P network, it takes an algorithm of merging the vector space model (VSM) and relevance ranking to construct the overlay network, which is used K-iteration preference based on semantic group to retrieval. This method effectively solves the problem of retrieval efficiency and precision, and reduces the cost of system of retrieval.
(4) In a distributed search engine, each query request is forwarded to a plurality of nodes, then sorted the results according to the size of the degree of correlation and combined into a results list. Each node with the different network topology has a difference retrieval mechanism. The document returned from each node can not be directly used to compare and merge.
To solve this problem, this paper uses take a method of search results clustering, which uses latent semantic indexing on the whole document content, takes Apache Lucene as the indexing engine, uses spring rich client platform for clustering engine test and obtains more satisfactory results.
In this paper, the system uses Java JDK1.5to analog the P2P networks, in which each node is indicated with a set of IP address and port number and the simulator uses several parameters to control the different properties of the network. In contrast to the similar methods with the experimental results, the method has obvious advantages in the recall, precision and query latency.
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