Quanyuan Wu

KF-Diff+: Highly Efficient Change Detection Algorithm for XML Documents

Most previous work in change detection on XML documents used the ordered tree, with the best complexity of O(nlogn), where n is the size of the document. The best algorithm we had ever known for unordered model achieves polynomial time in complexity. In this paper, we propose a highly efficient algorithm named KF-Diff+. The key property of our algorithm is that the algorithm transforms the traditional tree-to-tree correction into the comparing of the key trees which are substantially label trees without duplicate paths with the complexity of O(n), where n is the number of nodes in the trees. In addition, KF-Diff+ is tailored to both ordered trees and unordered trees. Experiment shows that KF-Diff+ can handle XML documents at extreme speed.

Contextual correlation based thread detection in short text message streams

Short text message streams are produced by Instant Messaging and Short Message Service which are wildly used nowadays. Each stream contains more than one thread usually. Detecting threads in the streams is helpful to various applications, such as business intelligence, investigation of crime and public opinion analysis. Existing works which are mainly based on text similarity encounter many challenges including the sparse eigenvector and anomaly of short text message. This paper introduces a novel concept of contextual correlation instead of the traditional text similarity into single-pass clustering algorithm to cover the challenges of thread detection. We firstly analyze the contextually correlative nature of conversations in short text message streams, and then propose an unsupervised method to compute the correlative degree. As a reference, a single-pass algorithm employing the contextual correlation is developed to detect threads in massive short text stream. Experiments on large real-life online chat logs show that our approach improves the performance by 11% when compared with the best similarity-based algorithm in terms of F1 measure.

Sockpuppet gang detection on social media sites

Users of social media sites can use more than one account. These identities have pseudo anonymous properties, and as such some users abuse multiple accounts to perform undesirable actions, such as posting false or misleading remarks comments that praise or defame the work of others. The detection of multiple user accounts that are controlled by an individual or organization is important. Herein, we define the problem as sockpuppet gang (SPG) detection. First, we analyze user sentiment orientation to topics based on emotional phrases extracted from their posted comments. Then we evaluate the similarity between sentiment orientations of user account pairs, and build a similar-orientation network (SON) where each vertex represents a user account on a social media site. In an SON, an edge exists only if the two user accounts have similar sentiment orientations to most topics. The boundary between detected SPGs may be indistinct, thus by analyzing account posting behavior features we propose a multiple random walk method to iteratively remeasure the weight of each edge. Finally, we adopt multiple community detection algorithms to detect SPGs in the network. User accounts in the same SPG are considered to be controlled by the same individual or organization. In our experiments on real world datasets, our method shows better performance than other contemporary methods.

QoS aware service composition with multiple quality constraints

Service composition has been recognized as a flexible way for resource sharing and application integration. Quality of service (QoS) is an important issue for composite services. In this paper, we address the issue of component services selection to ensures their composition satisfy given QoS constraints. We propose the concept of reduction tree as a general scheme to aggregate multi-dimensional quality. And then a heuristic algorithm MCSC_HEU is presented to find execution plans satisfying multiple QoS constrains, with the main idea of evaluating partial plans by a heuristic function during the course of reduction. The time complexity of MCSC_HEU is of polynomial level. Extensive evaluations show that MCSC_HEU succeeds in finding feasible plans with very high probability but demands much less time than exhausting search. So it is an efficient solution for QoS aware service selection with multiple constrains.

On Aggregation Operators for Fuzzy Information Sources

During the development of fuzzy information systems, the aggregation fuzzy information sources should be considered. Aggregation operators are the key technique that solve this problem. By assign 0.5 to the generalized triangular norm identy, the harmonic triangular norm operators and strict harmonic triangular norm operators is defined. The properties of the aggregation operators is discussed. We prove the continuous harmonic triangular norm operator does not exist. The operators when the information sources have weights are also given. Four type detail (strict) harmonic triangular norm operators are given. Finally, two measures associated with the operators are defined, one is marginal measure and the other is sensitive measure. Based on the measure, the relationships of those operators and classical operators are evaluated and compared. The result shows that the operators offer a new method to aggregation of fuzzy information sources in fuzzy environments.

Together: a hybrid overlay for application-layer multicast in heterogeneous environment

In this paper, we present a novel hybrid overlay, named as Together, for application multicast in heterogeneous environment. We analyze the reasons to cause bandwidth bottleneck in tree-based approach and correspondingly define a special set called Spare Capacity Set. Based on this definition, we further design a bandwidth adaptive auxiliary mesh which can be reconciled with a stable multiple trees structure under a coherent framework. The hybrid approach can achieve good performance as well as maximized utilization of node bandwidth, which is essential in heterogeneous environment.

A fault-tolerant web services architecture

Web services have been enjoying great popularities in recent years. The high usability of the Web service is becoming a new focus for research. According to the demands of Web services, we present a fault-tolerant Web services architecture named FTWS based on the service approach and the reflection approach. Its characteristics are: (1) The fault-tolerant mechanisms are transparent, easy to use and also flexibly customized; (2) The fault-tolerant properties are flexibly configured; (3) The target service programmers almost needn’t to care the fault-tolerant mechanisms. The Architecture is set forth in detail in the article. The workflow of the system is narrated by three states of a fault-tolerant Web service.

Temporal Restriction Query Optimization for Event Stream Processing

The trend that organizations are linking Service Oriented Architecture (SOA) efforts closely to real-time processes makes research and industrial community increasingly focus on the SOA and Event Stream Processing (ESP) connection. ESP needs to correlate multiple continuous events involved in complex temporal relationship and attribute logic relationship to more abstract complex events in richer semantic. Due to high speed arrival rate of events and vast volume of registered complex event queries, memory consumption and incremental event query evaluation demand a comprehensive dedicate event stream processing framework with low-latency and high scalability. In this paper, we study problems of query optimization for ESP, especially topics on temporal restriction query. We first propose a framework to integrate ESP features with business process management and monitor. We then describe a query plan-based approach to efficiently execute ESP queries. Our approach uses algebraic conversion to efficiently handle temporal restriction queries, which are a key component of complex event processing, and computes temporal relevance condition at compile time to obtain event relevance time for a given expression. We demonstrate the effectiveness of our approach through a performance evaluation of our prototype implementation.

A rule induction method of plant disease description based on rough sets

Knowledge acquisition is the bottleneck to develop expert system. It usually takes a long period to acquire plant disease knowledge using the traditional methods. Aiming at this problem, this paper describes relations between rough set theory and rule-based description of plant diseases. Then the exclusive rules, inclusive rules and disease images of rapeseed disease are built based on the PDES diagnosis model, and the definition of probability rule is put forward. At last, the paper presents the rule-based automated induction reasoning method, including exhaustive search, post-processing procedure, estimation for statistic test and the bootstrap and resampling methods. We also introduce automated induction of the rule-based description, which is used in our plant diseases diagnostic expert system. The experimental results show that this method induces diagnostic rules correctly.

A Plugin-Based Software Production Line Integrated Framework

Software production line can be created by integrated framework which can integrate software tools, software components, software services, and collaboration mechanism. It can be used as one of the important software reuse techniques. This paper provides the definitions and differentiations of software product line, software production line and plugin architecture. A platform independent model of the software production line integrated framework, that is based on the plugin architecture, is put forward. In the end, a runtime monitoring software production line is developed according to this model, to verify the correctness of the model.