8443356
Efficient web change monitoring with page digest
The Internet and the World Wide Web have enabled a publishing explosion of useful online information, which has produced the unfortunate side effect of information overload: it is increasingly difficult for individuals to keep abreast of fresh information. In this paper we describe an approach for building a system for efficiently monitoring changes to Web documents. This paper has three main contributions. First, we present a coherent framework that captures different characteristics of Web documents. The system uses the Page Digest encoding to provide a comprehensive monitoring system for content, structure, and other interesting properties of Web documents. Second, the Page Digest encoding enables improved performance for individual page monitors through mechanisms such as short-circuit evaluation, linear time algorithms for document and structure similarity, and data size reduction. Finally, we develop a collection of sentinel grouping techniques based on the Page Digest encoding to reduce redundant processing in large-scale monitoring systems by grouping similar monitoring requests together. We examine how effective these techniques are over a wide range of parameters and have seen an order of magnitude speed up over existing Web-based information monitoring systems.
13182282
InfoFilter: Supporting quality of service for fresh information delivery
With the explosive growth of the Internet and World Wide Web comes a dramatic increase in the number of users that compete for the shared resources of distributed system environments. Most implementations of application servers and distributed search software do not distinguish among requests to different web pages. This has the implication that the behavior of application servers is quite unpredictable. Applications that require timely delivery of fresh information consequently suffer the most in such competitive environments. This paper presents a model of quality of service (QoS) and the design of a QoS-enabled information delivery system that implements such a QoS model. The goal of this development is two-fold. On one hand, we want to enable users or applications to specify the desired quality of service requirements for their requests so that application-aware QoS adaptation is supported throughout the Web query and search processing. On the other hand, we want to enable an application server to customize how it should respond to external requests by setting priorities among query requests and allocating server resources using adaptive QoS control mechanisms. We introduce the Infopipe approach as the systems support architecture and underlying technology for building a QoS-enabled distributed system for fresh information delivery.
599285
Differential evaluation of continual queries
We define continual queries as a useful tool for monitoring of updated information. Continual queries are standing queries that monitor the source data and notify the users whenever new data matches the query. In addition to periodic refresh, continual queries include Epsilon Transaction concepts to allow users to specify query refresh based on the magnitude of updates. To support efficient processing of continual queries, we propose a differential re-evaluation algorithm (DRA), which exploits the structure and information contained in both the query expressions and the database update operations. The DRA design can be seen as a synthesis of previous research on differential files, incremental view maintenance, and active databases.
33902172
An Object-Centered Approach for Manipulating Hierarchically Complex Objects
We present an object-centered approach for manipulating hierarchically complex objects, which covers an extended object model and an object-centered query algebra. Extensions of the object model are mainly based on a separation of structural and semantic elements in modeling complex objects, including a general distinction between aggregation reference and association reference, an introduction of type inheritance into aggregation hierarchies and a support for combination of aggregation inheritance with subtype inheritance. Based on the extensions, we develop a query algebra as an integral part of the model. Unlike most of existing algebra-based query languages, our object algebra takes complex object collectively as a unit of high level queries and allows complex objects to be accessed at all levels of aggregation hierarchies without having resort to any kind of path expressions. Features of aggregation hierarchies, such as acyclicity and aggregation inheritance, have played important roles in such a development. We have also formally described the output type of each operator in order for dynamic classification of query results in the IsA type/class lattice. Although the design is based on the chosen object-oriented model, other object-oriented databases are possible. We feel that the proposal largely covers the query requirements for complex objects, and meanwhile provides users with an opportunity to remain within the framework of the model of complex objects while querying database. As a consequence, the flexibility and adaptability of the object-oriented model against schema changes are increased.
9143242
Update Monitoring: The CQ Project
In rapidly growing open environments such as the Internet, users experience information starvation in the midst of data overload, due to difficulties similar to finding the needle in a haystack. Update monitoring is a promising area of research where we bring the right information to the user at the right time, instead of forcing the user through manual browsing or repeated submission of queries. As an example of update monitoring research, we outline our work in the Continual Queries (CQ) project, including its basic concepts, software architecture, and current implementation status.
12589406
VISTA: Validating and Refining Clusters Via Visualization
Clustering is an important technique for understanding of large multidimensional datasets. Most of clustering research to date has been focused on developing automatic clustering algorithms and cluster validation methods. The automatic algorithms are known to work well in dealing with clusters of regular shapes, for example, compact spherical shapes, but may incur higher error rates when dealing with arbitrarily shaped clusters. Although some efforts have been devoted to addressing the problem of skewed datasets, the problem of handling clusters with irregular shapes is still in its infancy, especially in terms of dimensionality of the datasets and the precision of the clustering results considered. Not surprisingly, the statistical indices works ineffective in validating clusters of irregular shapes, too. In this paper, we address the problem of clustering and validating arbitrarily shaped clusters with a visual framework (VISTA). The main idea of the VISTA approach is to capitalize on the power of visualization and interactive feedbacks to encourage domain experts to participate in the clustering revision and clustering validation process. The VISTA system has two unique features. First, it implements a linear and reliable visualization model to interactively visualize multi-dimensional datasets in a 2D star-coordinate space. Second, it provides a rich set of user-friendly interactive rendering operations, allowing users to validate and refine the cluster structure based on their visual experience as well as their domain knowledge.
14735447
Representing asymmetric decision problems using coarse valuations
A valuation-based system approach to knowledge representation has shown its advantages in improving computational efficiency and in allowing many decision models including belief networks. This study applies the Dempster-Shafer theory of belief functions and extends its framework to allow coarse valuations, which admit incomplete specification of probabilities and utilities and, therefore, are more flexible in representing asymmetric decision problems. It presents an algorithm for making inferences and decisions in systems using coarse valuations. It shows that a coarse valuation-based system provides a most natural and compact representation of decision problems.
35610063
A Specification-Based Approach to Testing Polymorphic Attributes
The object-oriented features, such as aggregation, inheritance and polymorphism, facilitate software reuse and improve software quality. But those features also cause new problems that traditional testing techniques cannot resolve effectively. Existing researches on object-oriented software testing are mainly based on some graph representations and seldom consider the combinational effect of aggregation, inheritance and polymorphism. For some model-based specifications that do not include graph representations, it is difficult to use the graph based testing techniques to derive test cases. This paper provides an approach to deriving test cases for testing the combinational effect of aggregation, inheritance and polymorphism from a model-based class specification. This approach contains two techniques at intra-class and inter-class testing levels and is mechanized using the algorithms presented in this paper. Finally, through the experimental analysis, we present the effectiveness and applicability of our testing approach.
10550445
Fuzzy Bayesian Networks - A General Formalism for Representation, Inference and Learning with Hybrid Bayesian Networks
This paper proposes a general formalism for representation, inference and learning with general hybrid Bayesian networks in which continuous and discrete variables may appear anywhere in a directed acyclic graph. The formalism fuzzifies a hybrid Bayesian network into two alternative forms: the first form replaces each continuous variable in the given directed acyclic graph (DAG) by a partner discrete variable and adds a directed link from the partner discrete variable to the continuous one. The mapping between two variables is not crisp quantization but is approximated (fuzzified) by a conditional Gaussian (CG) distribution. The CG model is equivalent to a fuzzy set but no fuzzy logic formalism is employed. The conditional distribution of a discrete variable given its discrete parents is still assumed to be multinomial as in discrete Bayesian networks. The second form only replaces each continuous variable whose descendants include discrete variables by a partner discrete variable and adds a directed link from that partner discrete variable to the continuous one. The dependence between the partner discrete variable and the original continuous variable is approximated by a CG distribution, but the dependence between a continuous variable and its continuous and discrete parents is approximated by a conditional Gaussian regression (CGR) distribution. Obviously, the second form is a finer approximation, but restricted to CGR models, and requires more complicated inference and learning algorithms. This results in two general approximate representations of a general hybrid Bayesian networks, which are called here the fuzzy Bayesian network (FBN) form-I and form-II. For the two forms of FBN, general exact inference algorithms exists, which are extensions of the junction tree inference algorithm for discrete Bayesian networks. Learning fuzzy Bayesian networks from data is different from learning purely discrete Bayesian networks because not only all the newly converted discrete variables are latent in the data, but also the number of discrete states for each of these variables and the CG or CGR distribution of each continuous variable given its partner discrete parents or both continuous and discrete parents have to be determined.
10661094
Designing information systems in social context: a goal and scenario modelling approach
In order to design a better information system, a designer would like to have notations to visualize how design experts' know-how can be applied according to one's specific social and technology situation. We propose the combined use of a goal-oriented requirements language (GRL) and a scenario-oriented notation Use Case Maps (UCM) for representing design knowledge of information systems. Goal-oriented modelling is used throughout the requirements and design process. In GRL, goals are used to depict business objectives and system requirements, both functional and non-functional. Tasks are used to represent different ways for achieving goals. Means-ends reasoning is used to explore alternative solutions and their operationalizations into implementable system constructs. Social context is modelled in terms of dependency relationships among agents and roles. Scenarios expressed in UCM are used to describe elaborated business processes or workflow. The complementary use of goal-oriented modelling with GRL and scenario modelling with UCM is illustrated with an example of designing a web-based training system.
8923918
A Linear Belief Function Approach to Portfolio Evaluation
We show how to use linear belief functions to represent market information and financial knowledge, including complete ignorance, statistical observations, subjective speculations, distributional assumptions, linear relations, and empirical asset pricing models. We then appeal to Dempster's rule of combination to integrate the knowledge for assessing an overall belief on portfolio performance, and to update this belief by incorporating additional information.