A Formal Specification for Web Services Composition and Verification
Due to the promising features of Web services, their deployment and research are booming. Among them, various techniques for Web service composition have been developed. In this paper, we propose a new composition framework. We use automata to describe behaviors of Web services. Each of underlying Web services can interact with others through asynchronous messages passing according to its interaction role (client or server). All these messages are recorded by a virtual global observer and the observation result is just the composition conversation of Web services. We also develop a formal a top-down verification mechanism on this framework and provide some realizable conditions for a successful composition

title: Dealing with different distributions in learning from
abstract: In the problem of learning with positive and unlabeled examples, existing research all assumes that positive examples P and the hidden positive examples in the unlabeled set U are generated from the same distribution. This assumption may be violated in practice. In such cases, existing methods perform poorly. This paper proposes a novel technique A-EM to deal with the problem. Experimental results with product page classification demonstrate the effectiveness of the proposed technique.

title: Speed-up iterative frequent itemset mining with constraint changes
abstract: Mining of frequent itemsets is a fundamental data mining task. Past research has proposed many efficient algorithms for this purpose. Recent work also highlighted the importance of using constraints to focus the mining process to mine only those relevant itemsets. In practice, data mining is often an interactive and iterative process. The user typically changes constraints and runs the mining algorithm many times before being satisfied with the final results. This interactive process is very time consuming. Existing mining algorithms are unable to take advantage of this iterative process to use previous mining results to speed up the current mining process. This results in an enormous waste of time and computation. In this paper, we propose an efficient technique to utilize previous mining results to improve the efficiency of current mining when constraints are changed. We first introduce the concept of tree boundary to summarize useful information available from previous mining. We then show that the tree boundary provides an effective and efficient framework for the new mining. The proposed technique has been implemented in the context of two existing frequent itemset mining algorithms, FP-tree and tree projection. Experiment results on both synthetic and real-life datasets show that the proposed approach achieves a dramatic saving of computation.

title: Finding Actionable Knowledge via Automated Comparison
abstract: The problem of finding interesting and actionable patterns is a major challenge in data mining. It has been studied by many data mining researchers. The issue is that data mining algorithms often generate too many patterns, which make it very hard for the user to find those truly useful ones. Over the years many techniques have been proposed. However, few have made it to real-life applications. At the end of 2005, we built a data mining system for Motorola (called Opportunity Map) to enable the user to explore the space of a large number of rules in order to find actionable knowledge. The approach is based on the concept of rule cubes and operations on rule cubes. A rule cube is similar to a data cube, but stores rules. Since its deployment, some issues have also been identified during the regular use of the system in Motorola. One of the key issues is that although the operations on rule cubes are flexible, each operation is primitive and has to be initiated by the user. Finding a piece of actionable knowledge typically involves many operations and intense visual inspections, which are labor-intensive and time-consuming. From interactions with our users, we identified a generic problem that is crucial for finding actionable knowledge. The problem involves extensive comparison of sub-populations and identification of the cause of their differences. This paper first defines the problem and then proposes an effective method to solve the problem automatically. To the best of our knowledge, there is no reported study of this problem. The new method has been added to the Opportunity Map system and is now in daily use in Motorola.

title: Entity discovery and assignment for opinion mining applications
abstract: Opinion mining became an important topic of study in recent years due to its wide range of applications. There are also many companies offering opinion mining services. One problem that has not been studied so far is the assignment of entities that have been talked about in each sentence. Let us use forum discussions about products as an example to make the problem concrete. In a typical discussion post, the author may give opinions on multiple products and also compare them. The issue is how to detect what products have been talked about in each sentence. If the sentence contains the product names, they need to be identified. We call this problem entity discovery. If the product names are not explicitly mentioned in the sentence but are implied due to the use of pronouns and language conventions, we need to infer the products. We call this problem entity assignment. These problems are important because without knowing what products each sentence talks about the opinion mined from the sentence is of little use. In this paper, we study these problems and propose two effective methods to solve the problems. Entity discovery is based on pattern discovery and entity assignment is based on mining of comparative sentences. Experimental results using a large number of forum posts demonstrate the effectiveness of the technique. Our system has also been successfully tested in a commercial setting.

title: Opinion Mining
abstract: Описанл процедуру формування інтегрального показника об’єкта згідно з відгуками користувачів під час застосування методів оцінювання опінії текстової інформації у web-документах. Запропоновано використання лінгвістичних змінних та застосування вагових коефіцієнтів для достовірнішого результату оцінювання емоційного забарвлення текстової інформації. Ключові слова: опінія, емоційне забарвлення, об’єкт, інтегральний показник, лінгвістична змінна, ваговий коефіцієнт.

title: Numerical Experiments with Monte Carlo Methods and SPAI Preconditioner for Solving System of Linear Equations
abstract: In this paper we present the results of experiments comparing the performance of the mixed Monte Carlo algorithms and SPAI preconditener with BICGSTAB. The experiments are carried out on a Silicon Graphics ONYX2 machine. Based on our experiments, we conclude that these techniques are comparable from the point of view of robustness and rates of convergence, with the Monte Carlo approach performing better for some general cases and SPAI approach performing better in case of very sparse matrices.

title: A Quality Metric Based on Color Similarity for Image Fusion
abstract: This paper proposes a new objective, non-reference quality metric for evaluating the performance of pixel-level image fusion. The metric is designed on a likelihood function for color cue that measures the similarity of color- or grey-level distributions. We have provided a theoretical analysis on how the quality metric responds to weighted averaging fusion algorithm. Then the slide window is used to calculate the metric over local region with the weight which is assessed by local saliency and indicates the relative importance. Extensive experiments have demonstrated that the metric is more effective and consistent with subjective evaluations compared with other metrics.

title: Repairing Inconsistency and Uncertainty in DL-based Ontologies
abstract: A method of detecting malignant or pre-malignant conditions of the cervix, and test kits therefor, involves selecting a fraction of a cervical cell sample consisting predominantly of epithelial cells and determining characteristics indicative of the malignant or pre-malignant conditions therein.

title: A New Performance Evaluation Model and AHP-Based Analysis Method in Service-Oriented Workflow
abstract: In service-oriented architecture, services and workflows are closely related so that the research on service-oriented workflow attracts the attention of academia. Because of the loosely-coupled, autonomic and dynamic nature of service, the operation and performance evaluation of workflow meet some challenges, such as how to judge the quality of service (QoS) and what is the relation between QoS and workflow performance. In this paper we are going to address these challenges. First the definition of service is proposed, and the characteristics and operation mechanism of service-oriented workflow are presented. Then a service-oriented workflow performance evaluation model is described which combines the performance of the business system and IT system. The key performance indicators (KPI) are also depicted with their formal representation. Finally the improved Analytic Hierarchy Process is brought forward to analyze the correlation between different KPIs and select services.

title: A High-Performance Intelligent Integrated Data Services System in Data Grid
abstract: It is very complex and of low efficiency for grid users to access heterogeneous diverse data resources distributed over the whole wide area network. The integrated data services can implement more wide range of transparent access to data resources in Data Grid. One of the important building blocks for any Data Grid is the server which implements data services. In this paper, we describe HPIIDS which implements integrated data services and achieves more wide range of transparencies. In order to improve its performances, we emphasis on the server called DSB which provides integrated data services. The DSB bases on cluster and agent technologies. Agent-based DSB can cleverly prefetch required data, replicate them among DSBs. Multiple DSBs are formed cluster HPIIDS. Cluster-based HPIIDS implements a single entry, provides a virtual integrated storage system for users, hides distributed heterogeneous low-level data resources, and insures load balance of each server. HPIIDS architecture supporting these various scenarios, are also described.