基于Petri网可达分析的代码搜索方法

复用已有高质量源代码可提高软件开发效率及软件质量.当前,基于用户提供的输入/输出对的匹配判断是代码语义搜索的主要方法之一,但该方法难以刻画完整代码行为,且仅能处理单输入类型.提出一种针对多种形式类型匹配的代码语义搜索方法.首先将代码集内各个代码片段中数据对象个数及类型的加工过程转换为Petri网模型;其次根据用户查询中...     

基于多特征权重分配的源代码搜索优化

对开源代码进行准确搜索是实现代码复用的前提。在基于关键字搜索的研究中,目前只关注匹配方法签名。结合源代码注释对方法功能的语义描述,提出结合代码注释的关键字搜索方法。通过生成源代码抽象语法树,从中识别方法签名与各类型注释等组合代码特征;将代码特征与查询语句分别用向量表示,并计算向量间的余弦相似度,然后制定针对搜索结果多特征权重分配的评分机制。根据评分对搜索结果进行排序,得到与查询语句相关的结果序列。实验结果表明,多个代码特征在不同权重影响下可以提升源代码搜索准确度。     

带有高效索引的语义Web服务I/O匹配优化方法

目前Web环境中蕴涵着大量的Web服务和Web服务请求,基于语义的Web服务匹配能够提高Web服务发现的准确性,但由于其复杂的语义计算,导致系统响应速度慢。首先,对语义Web服务过程进行了分析,确定大量的语义计算主要集中在输入/输出（I/O）匹配环节;然后,在研究现有I/O匹配算法和分析影响语义相似度的主要因素基础上,给出了一种带有高效索引的语义Web服务I/O匹配优化方法,包括：高效索引的建立和基于哈希二次探测再散列的启发式筛选机制的提出;最后,通过实例证明了该方法切实可行。该方法通过筛除无关Web服务,减少了语义计算量,提高了系统响应速度,进而带来了更好的用户体验。     

一种基于语义的Web服务匹配算法

概要:在当前Web服务发现过程中,采用基于数据类型和关键词的搜索匹配算法,而忽略了人类语言表达的多样性。通常服务请求者对需求描述不能很好符合Web服务匹配算法的要求,是造成服务匹配率较低的主要原因。本文探讨一种基于语义的Web服务匹配算法,分别对服务提供者注册Web服务,服务请求者提交Web服务请求以及服务注册中心进行Web服务匹配等三个过程提出了改进算法,从而可提高服务匹配率。     

基于语义的Web服务自动组合算法

为了实现组合相关处理的自动化和智能化,提出一种基于语义的Web服务自动组合算法。该算法采用深度优先的方法计算概念间的语义相似度,基于前驱服务生成从请求输入到请求输出的服务组合方案。实验结果表明该算法充分利用Web服务功能的语义信息,与已有算法相比,简化了自动组合过程。     

本体匹配的网格服务发现模型研究

如何从大规模网格服务集合中快速而准确地发现满足用户请求的服务,是语义环境下网络应用的一个重要方面。针对传统的基于关键字匹配的Web服务发现方法无法准确描述网格服务服务能力和应用领域的问题,提出了一种基于输入和输出领域本体的语义网格服务描述模型和基于本体匹配的语义网格服务发现流程,构造了基于本体匹配语义相似度计算的语义网格服务发现算法。实验结果表明,基于本体匹配的语义网格发现方法能够获得很好的查全率和查准率。     

一种基于语义与QoS感知的Web服务匹配机制

Web服务匹配是动态服务组合的一个重要环节,然而目前大多数的研究仅从单个抽象服务的角度进行局部语义匹配,没有考虑到服务组合的全局匹配,此外,即使考虑了全局匹配也仅从QoS角度进行匹配,没有考虑到全局语义匹配.针对服务组合流程,提出了基于抽象服务的局部语义匹配与基于QoS感知的全局语义匹配,设计了语义匹配算法,并扩展对服务输入/输出匹配的可用性分析,建立了全局匹配的QoS模型及其评价方法,基于该模型及评价方法,采用遗传算法实现全局语义匹配度最大化及满足用户的QoS指标需求.仿真实验结果表明:基于语义与QoS感知的服务匹配算法是可行的和有效的.     

基于Petri网的语义Web服务自动组合方法

Web服务组合使得开发人员可以快速地创建自己的应用程序.但是,随着Internet上可用的Web服务数目的增加,Web服务组合是一项高度复杂的任务.针对语义Web服务的自动组合问题,提出了一种既考虑服务输入/输出又考虑服务行为约束的自动组合方法.首先,注册服务被转化为一组Horn子句形规则,用户的输入和输出请求分别被转化为Horn子句中的事实和目标,从而将寻找满足用户输入/输出请求的合成服务问题转化为Horn子句的逻辑推理问题;然后,用Petri网来为该Horn子句集建模,T-不变量技术被用来判定是否存在满足用户输入/输出请求的合成服务;最后给出了两种算法来获取既满足用户输入/输出请求又满足用户行为约束的合成服务的Petri网模型.     

ChinaGrid图像处理网格平台中的语义信息服务研究

在网格中要实现更加准确有效的服务发现、查询及其动态分配和替换,需要在语法匹配的基础上进一步实现语义匹配.介绍了在图像处理网格平台上开发的、基于语义的信息服务组件;描述了该组件的设计框架结构,并给出该组件的核心算法即网格服务语义匹配算法的描述.该组件能有效实现对图像处理网格服务的语义查询和工作流构建时的自动语义匹配以及工作流执行中网格服务的动态分配和替换.与传统语义服务匹配算法相比,所提出的网格服务匹配算法显著提高了网格服务的匹配准确度.     

一种基于语义Web服务的匹配算法研究

传统的Web服务发现只是简单的基于关键字的语法匹配,查询得到的服务往往不是用户想要的,如何正确定位合适的Web服务成为主要问题。在服务使用OWL-S描述的前提下,服务匹配通常认为是本体概念的匹配,给出了一种基于语义Web服务的匹配算法,通过服务发布者提供的服务和服务消费者寻求的服务的关系来进行匹配算法研究,提出了相应的服务匹配技术,详细介绍了服务请求时进行服务匹配使用的匹配算法,达到服务发布者和请求者可以实现语义的匹配。最后对服务匹配算法进行了实现,提高了服务的查准率和查全率。     

Integrating bilingual search results for automatic junk image filtering

Keyword-based image search engines are now very popular for accessing large amounts of Web images on the Internet. Most existing keyword-based image search engines may return large amounts of junk images (which are irrelevant to the given query word), because the text terms that are loosely associated with the Web images are also used for image indexing. The objective of the proposed work is to effectively filter out the junk images from image search results. Therefore, bilingual image search results for the same keyword-based query are integrated to identify the clusters of the junk images and the clusters of the relevant images. Within relevant image clusters, the results are further refined by removing the duplications under a coarse-to-fine structure. Experiments for a large number of bilingual keyword-based queries (5,000 query words) are simultaneously performed on two keyword-based image search engines (Google Images in English and Baidu Images in Chinese), and our experimental results have shown that integrating bilingual image search results can filter out the junk images effectively.     

Deep learning the semantics of change sequences for query expansion

The overexpansion problem negatively affects the quality of query expansion. To improve the quality of queries for searching code, this paper proposed a DBN-based algorithm for effective query expansion. The deep belief network (DBN) model is trained on the code sequences and their change sequences, which aims to capture the meaningful terms during the evolution of source code. In contrast to previous studies, the proposed model not only extracts relevant terms to expand a query but also excludes irrelevant terms from the query. It addresses two problems in query expansion, including the overexpansion of the original query and the negative influence of the changed terms in the target source code. Experiments on both artificial queries and real queries show that the proposed algorithm outperforms several query expansion algorithms for code search.     

Ontology based user query interpretation for semantic multimedia contents retrieval

Users who are familiar with the existing keyword-based search have problems of not being able to configure the formal query because they don’t have generic knowledge on knowledge base when using the semantic-based retrieval system. User wants the search results which are more accurate and match the user’s search intents with the existing keyword-based search and the same search keyword without the need to recognize what technology the currently used retrieval system is based on to provide the search results. In order to do the semantic analysis of the ambiguous search keyword entered by users who are familiar with the existing keyword-based search, ontological knowledge base constructed based on refined meta-data is necessary, and the keyword semantic analysis technique which reflects user’s search intents from the well-established knowledge base and can generate accurate search results is necessary. In this paper, therefore, by limiting the knowledge base construction to multimedia contents meta-data, the applicable prototype has been implemented and its performance in the same environment as Smart TV has been evaluated. Semantic analysis of user’s search keyword is done, evaluated and recommended through the proposed ontological knowledge base framework so that accurate search results that match user’s search intents can be provided.     

Optimizing sort order query execution in balanced and nested gridfiles

Disk input/output (I/O) efficient query execution is an important topic with respect to DBMS performance. In this context, we elaborate on the construction of disk access plans for sort order queries in balanced and nested grid files. The key idea is to use the order information contained in the directory of the multiattribute search structure. The presented algorithms are shown to yield a significant decrease in the number of disk I/O operations by appropriate use of the order information. Two algorithms for the construction of appropriate disk access plans are proposed, namely a greedy approach and a heuristic divide-and-conquer approach. Both approaches yield considerable I/O savings compared to straightforward query processing without consideration of any directory order information. The former performs well for small buffer page allocations, i.e., for a small number of buffer pages relative to the number of data buckets processed in the query. The latter is superior to the greedy algorithm with respect to the total number of I/O operations and with respect to the overall maximum of buffer pages needed to achieve the minimal number of disk I/O operations. Both approaches rely on a binary trie as a temporary data structure. This trie is used as an explicit representation of the order information. The storage consumption of the temporary data structure is shown to be negligible in realistic cases, Even for pathological cases with respect to degenerated balanced and nested grid files, reasonable upper bounds can be given     

A tool for organizing Web information

The physical and logical differences among information sources on the Internet complicate information retrieval. For instance, data is no longer just simple text or tuples, but now includes objects and multimedia. Data can also have varied and often arcane semantics. Sources have different policies, procedures, and conventions and are hosted by diverse platforms. Ontologies-models of concepts and their relationships-are a powerful way to organize query formulation and semantic reconciliation in large distributed information environments. They can capture both the structure and semantics of information environments, so an ontology-based search engine can handle both simple keyword-based queries as well as complex queries on structured data. Ontology-based interoperation is especially good at dealing with inconsistent semantics. However; ontologies are difficult to construct. The Java Ontology Editor (JOE) helps users build and browse ontologies. It also enables query formulation at several levels of abstraction. The authors discuss the use of JOE to develop a health care information system     

A query algebra for program databases

Querying source code is an essential aspect of a variety of software engineering tasks such as program understanding, reverse engineering, program structure analysis and program flow analysis. In this paper, we present and demonstrate the use of an algebraic source code query technique that blends expressive power with query compactness. The query framework of Source Code Algebra (SCA) permits users to express complex source code queries and views as algebraic expressions. Queries are expressed on an extensible, object-oriented database that stores program source code. The SCA algebraic approach offers multiple benefits such as an applicative query language, high expressive power, seamless handling of structural and flow information, clean formalism and potential for query optimization. We present a case study where SCA expressions are used to query a program in terms of program organization, resource flow, control flow, metrics and syntactic structure. Our experience with an SCA-based prototype query processor indicates that an algebraic approach to source code queries combines the benefits of expressive power and compact query formulation     

Improving legal information retrieval using an ontological framework

A variety of legal documents are increasingly being made available in electronic format. Automatic Information Search and Retrieval algorithms play a key role in enabling efficient access to such digitized documents. Although keyword-based search is the traditional method used for text retrieval, they perform poorly when literal term matching is done for query processing, due to synonymy and ambivalence of words. To overcome these drawbacks, an ontological framework to enhance the user’s query for retrieval of truly relevant legal judgments has been proposed in this paper. Ontologies ensure efficient retrieval by enabling inferences based on domain knowledge, which is gathered during the construction of the knowledge base. Empirical results demonstrate that ontology-based searches generate significantly better results than traditional search methods.