15738525
Dynamic Collaboration Simulation in Service-Oriented Computing Paradigm
In service-oriented architecture (SOA) and service-oriented computing (SOC), service collaboration is an important aspect. While service collaboration protocols for data exchange are well explored, the dynamic process collaboration (DPC) is still a challenging issue. The DPC brings new features and uncertainty to the current SOA/SOC, such as run-time behavior evaluation, dynamic collaboration performance measurement and dynamic recomposition/reconfiguration capability assessment. This paper presents the dynamic service-oriented collaboration simulation (DSOCS) framework we have developed, which supports the dynamic collaboration, development, simulation, and evaluation of large scale SOA systems. The distinct features of the framework include automated simulation code generation from the specification, code deployment, and simulation of different architectures with a template-based platform builder, service-oriented multi-agent simulation for easy reconfiguration, and dynamic analyses of results from evaluation and monitoring. The framework and the associated tools have been implemented and applied in several governmental and industrial projects
2511748
QPIAD: Query Processing over Incomplete Autonomous Databases
Incompleteness due to missing attribute values (aka "null values") is very common in autonomous Web databases, on which user accesses are usually supported through mediators. Traditional query processing techniques that focus on the strict soundness of answer tuples often ignore tuples with critical missing attributes, even if they wind up being relevant to a user query. Ideally we would like the mediator to retrieve such relevant uncertain answers and gauge their relevance by accessing their likelihood of being relevant answers to the query. However, the autonomous nature of the databases poses several challenges, such as the restricted access privileges, limited query patterns, and sensitivity of database and network resource consumption in the Web environment. We introduce a novel query rewriting and optimization framework QPIAD that tackles these challenges to retrieve relevant uncertain answers. Our technique involves reformulating the user query based on approximate functional dependencies (AFDs) among the database attributes and ranking these queries using value distributions learned from naive Bayes classifiers. Empirical studies demonstrate the effectiveness of our approach in retrieving relevant uncertain answers with high precision, high recall and manageable cost.
5650965
L-Tree: A Dynamic Labeling Structure for Ordered XML Data
With the ever growing use of XML as a data representation format, we see an increasing need for robust, high performance XML database systems While most of the recent work focuses on efficient XML query processing, XML databases also need to support efficient updates To speed up query processing, various labeling schemes have been proposed However, the vast majority of these schemes have poor update performance In this paper, we introduce a dynamic labeling structure for XML data: L-Tree and its order-preserving labeling scheme with O(log n) amortized update cost and O(log n) bits per label L-Tree has good performance on updates without compromising the performance of query processing We present the update algorithm for L-Tree and analyze its complexity.
5453537
Testability of Software in Service-Oriented Architecture
Service-oriented architecture (SOA) is a system architecture in which a collection of loosely coupled services communicate with each other using standard interfaces and message-exchanging protocols. As an emerging technology in software development, the SOA presents a new paradigm, and it affects the entire software development cycle including analysis, specification, design, implementation, verification, validation, maintenance and evaluation. This paper proposes several testability evaluation criteria for SOA software, which serves as a reference for both service providers and application builders to evaluate the test support to SOA software. The proposed evaluation criteria are illustrated in a stock-trading case study
3132727
Query Processing over Incomplete Autonomous Databases
Incompleteness due to missing attribute values (aka "null values") is very common in autonomous web databases, on which user accesses are usually supported through mediators. Traditional query processing techniques that focus on the strict soundness of answer tuples often ignore tuples with critical missing attributes, even if they wind up being relevant to a user query. Ideally we would like the mediator to retrieve such possible answers and gauge their relevance by accessing their likelihood of being pertinent answers to the query. The autonomous nature of web databases poses several challenges in realizing this objective. Such challenges include the restricted access privileges imposed on the data, the limited support for query patterns, and the bounded pool of database and network resources in the web environment. We introduce a novel query rewriting and optimization framework QPIAD that tackles these challenges. Our technique involves reformulating the user query based on mined correlations among the database attributes. The reformulated queries are aimed at retrieving the relevant possible answers in addition to the certain answers. QPIAD is able to gauge the relevance of such queries allowing tradeoffs in reducing the costs of database query processing and answer transmission. To support this framework, we develop methods for mining attribute correlations (in terms of Approximate Functional Dependencies), value distributions (in the form of Naive Bayes Classifiers), and selectivity estimates. We present empirical studies to demonstrate that our approach is able to effectively retrieve relevant possible answers with high precision, high recall, and manageable cost.
37282807
Testing Web Services Using Progressive Group Testing
This paper proposes progressive group testing techniques to test large number of Web services (WS) available on Internet. At the unit testing level, the WS with the same functionality are tested in group using progressively increasing number of test cases. A small number of WS that scored best will be integrated into the real environment for operational testing. At the integration testing level, many composite services will be constructed and tested by group integration testing. The results of group testing at both unit and integration levels are verified by weighted majority voting mechanisms. The weights are based on the reliability history of the WS under test. A case study is designed and implemented, where the dependency among the test cases in WS is analyzed and used to generate progressive layers of test cases.
535520
Detection of Entity Mentions Occuring in English and Chinese Text
In this paper, we describe an integrated approach to entity mention detection that yields a monolithic, almost language independent system. It is optimal in the sense that all categorical constraints are simultaneously considered. The system is compact and easy to develop and maintain, since only a single set of features and classifiers are needed to be designed and optimized. It is implemented using one-versus-all support vector machine (SVM) classifiers and a number of feature extractors at several linguistic levels. SVMs are well known for their ability to handle a large set of overlapping features with theoretically sound generalization properties. Data sparsity might be an important issue as a result of a large number of classes and relatively moderate training data size. However, we report results that the integrated system performs as good as a pipelined system that decomposes the problem into a few smaller sub-tasks. We conduct all our experiments using ACE 2004 data, evaluate the systems using ACE metrics and report competitive performance.
17575068
Yoda, an adaptive soft classification model: content-based similarity queries and beyond
Abstract. Providing a customized result set based upon a user preference is the ultimate objective of many content-based image retrieval systems. There are two main challenges in meeting this objective: First, there is a gap between the physical characteristics of digital images and the semantic meaning of the images. Secondly, different people may have different perceptions on the same set of images. To address both these challenges, we propose a model, named Yoda, that conceptualizes content-based querying as the task of soft classifying images into classes. These classes can overlap, and their members are different for different users. The “soft” classification is hence performed for each and every image feature, including both physical and semantic features. Subsequently, each image will be ranked based on the weighted aggregation of its classification memberships. The weights are user-dependent, and hence different users would obtain different result sets for the same query. Yoda employs a fuzzy-logic based aggregation function for ranking images. We show that, in addition to some performance benefits, fuzzy aggregation is less sensitive to noise and can support disjunctive queries as compared to weighted-average aggregation used by other content-based image retrieval systems. Finally, since Yoda heavily relies on user-dependent weights (i.e., user profiles) for the aggregation task, we utilize the users' relevance feedback to improve the profiles using genetic algorithms (GA). Our learning mechanism requires fewer user interactions, and results in a faster convergence to the user's preferences as compared to other learning techniques.
24794561
Finding Short Patterns to Classify Text Documents
Many classification methods have been proposed to find patterns in text documents. However, according to Occam's razor principle, "the explanation of any phenomenon should make as few assumptions as possible", short patterns usually have more explainable and meaningful for classifying text documents. In this paper, we propose a depth-first pattern generation algorithm, which can find out short patterns from text document more effectively, comparing with breadth-first algorithm
17883721
Classification of self-consumable highlights for soccer video summaries
An effective scheme for soccer summarization is significant to improve the usage of this massively growing video data. The paper presents an extension to our recent work which proposed a framework to integrate highlights into play-breaks to construct more complete soccer summaries. The current focus is to demonstrate the benefits of detecting some specific audio-visual features during play-break sequences in order to classify highlights contained within them. The main purpose is to generate summaries which are self-consumable individually. To support this framework, the algorithms for shot classification and detection of near-goal and slow-motion replay scenes is described. The results of our experiment using 5 soccer videos (20 minutes each) show the performance and reliability of our framework
2875554
A note on domination and minus domination numbers in cubic graphs
Abstract Let G = ( V , E ) be a graph. A subset S of V is called a dominating set if each vertex of V − S has at least one neighbor in S . The domination number γ ( G ) equals the minimum cardinality of a dominating set in G . A minus dominating function on G is a function f : V → { − 1 , 0 , 1 } such that f ( N [ v ] ) = ∑ u ∈ N [ v ] f ( u ) ≥ 1 for each v ∈ V , where N [ v ] is the closed neighborhood of v . The minus domination number of G is γ − ( G ) = min { ∑ v ∈ V f ( v ) ∣ f  is a minus dominating function on  G } . It was incorrectly shown in [X. Yang, Q. Hou, X. Huang, H. Xuan, The difference between the domination number and minus domination number of a cubic graph, Applied Mathematics Letters 16 (2003) 1089–1093] that there is an infinite family of cubic graphs in which the difference γ − γ − can be made arbitrary large. This note corrects the mistakes in the proof and poses a new problem on the upper bound for γ − γ − in cubic graphs.