Dennis McLeod

A federated architecture for information management

An approach to the coordinated sharing and interchange of computerized information is described emphasizing partial, controlled sharing among autonomous databases. Office information systems provide a particularly appropriate context for this type of information sharing and exchange. A federated database architecture is described in which a collection of independent database systems are united into a loosely coupled federation in order to share and exchange information. A federation consists of components (of which there may be any number) and a single federal dictionary. The components represent individual users, applications, workstations, or other components in an office information system. The federal dictionary is a specialized component that maintains the topology of the federation and oversees the entry of new components. Each component in the federation controls its interactions with other components by means of an export schema and an import schema. The export schema specifies the information that a component will share with other components, while the import schema specifies the nonlocal information that a component wishes to manipulate. The federated architecture provides mechanisms for sharing data, for sharing transactions (via message types) for combining information from several components, and for coordinating activities among autonomous components (via negotiation). A prototype implementation of the federated database mechanism is currently operational on an experimental basis.

Yoda: An Accurate and Scalable Web-Based Recommendation System

Recommendation systems are applied to personalize and customize the Web environment. We have developed a recommendation system, termed Yoda, that is designed to support large-scale Web-based applications requiring highly accurate recommendations in real-time. With Yoda, we introduce a hybrid approach that combines collaborative filtering (CF) and content-based querying to achieve higher accuracy. Yoda is structured as a tunable model that is trained off-line and employed for real-time recommendation on-line. The on-line process benefits from an optimized aggregation function with low complexity that allows realtime weighted aggregation of the soft classification of active users to predefined recommendation sets. Leveraging on localized distribution of the recommendable items, the same aggregation function is further optimized for the off-line process to reduce the time complexity of constructing the pre-defined recommendation sets of the model. To make the off-line process scalable furthermore, we also propose a filtering mechanism, FLSH, that extends the Locality Sensitive Hashing technique by incorporating a novel distance measure that satisfies specific requirements of our application. Our end-to-end experiments show while Yodas complexity is low and remains constant as the number of users and/or items grow, its accuracy surpasses that of the basic nearest-neighbor method by a wide margin (in most cases more than 100%).

Journal on Data Semantics II

International Conference on Ontologies, DataBases, and Applications of Semantics for Large Scale Information Systems (ODBase 2003).- Incrementally Maintaining Materializations of Ontologies Stored in Logic Databases.- Ontology Translation on the Semantic Web.- Compound Term Composition Algebra: The Semantics.- Dynamic Pattern Mining: An Incremental Data Clustering Approach.- International Conference on Cooperative Information Systems (CoopIS 2003).- A Knowledge Network Approach for Implementing Active Virtual Marketplaces.- Stream Integration Techniques for Grid Monitoring.- 6th IFIP TC 11 WG 11.5 Working Conference on Integrity and Internal Control in Information Systems (IICIS 2003).- Information Release Control: A Learning-Based Architecture.- Enforcing Semantics-Aware Security in Multimedia Surveillance.

A Comparative Study for Email Classification

Email has become one of the fastest and most economical forms of communication. However, the increase of email users have resulted in the dramatic increase of spam emails during the past few years. In this paper, email data was classified using four different classifiers (Neural Network, SVM classifier, Naive Bayesian Classifier, and J48 classifier). The experiment was performed based on different data size and different feature size. The final classification result should be ‘1’ if it is finally spam, otherwise, it should be ‘0’. This paper shows that simple J48 classifier which make a binary tree, could be efficient for the dataset which could be classified as binary tree.

Semantic heterogeneity resolution in federated databases by metadata implantation and stepwise evolution

Abstract. A key aspect of interoperation among data-intensive systems involves the mediation of metadata and ontologies across database boundaries. One way to achieve such mediation between a local database and a remote database is to fold remote metadata into the local metadata, thereby creating a common platform through which information sharing and exchange becomes possible. Schema implantation and semantic evolution, our approach to the metadata folding problem, is a partial database integration scheme in which remote and local (meta)data are integrated in a stepwise manner over time. We introduce metadata implantation and stepwise evolution techniques to interrelate database elements in different databases, and to resolve conflicts on the structure and semantics of database elements (classes, attributes, and individual instances). We employ a semantically rich canonical data model, and an incremental integration and semantic heterogeneity resolution scheme. In our approach, relationships between local and remote information units are determined whenever enough knowledge about their semantics is acquired. The metadata folding problem is solved by implanting remote database elements into the local database, a process that imports remote database elements into the local database environment, hypothesizes the relevance of local and remote classes, and customizes the organization of remote metadata. We have implemented a prototype system and demonstrated its use in an experimental neuroscience environment.

A federated architecture for database systems

The contemporary approach to database system architecture requires the complete integration of data into a single, centralized database; while multiple logical databases can be supported by current database management software, techniques for relating these databases are strictly ad hoc. This problem is aggravated by the trend toward networks of small to medium size computer systems, as opposed to large, stand-alone main-frames. Moreover, while current research on distributed databases aims to provide techniques that support the physical distribution of data items in a computer network environment, current approaches require a distributed database to be logically centralized.

The 3DIS: an extensible object-oriented information management environment

The 3-Dimensional Information Space (3DIS) is an extensible object-oriented framework for information management. It is specifically oriented toward supporting the database requirements for data-intensive information system applications in which (1) information objects of various levels of abstraction and modalities must be accommodated, (2) descriptive and structural information (metadata) is rich and dynamic, and (3) users who are not database experts must be able to design, manipulate, and evolve databases. In response to these needs, the 3DIS provides an approach in which data and the descriptive information about data are handled uniformly in an extensible framework. The 3DIS provides a simple, geometric, and formal representation of data which forms a basis for understanding, defining, and manipulating databases. Several prototype implementations based upon the 3DIS have been designed and implemented and are in experimental use.

Report of the Workshop on Semantic Heterogeneity and Interpolation in multidatabase Systems

This report presents a review of the problems that were discussed during the Workshop on Semantic Heterogeneity and Interoperability in Multidatabase Systems. The workshop participants discussed the importance of interoperation in the U S WEST information processing environment and the progress that has been achieved in three major research areas: resolution of semantic heterogeneity among cooperating heterogeneous systems, transaction management in such environments, and software architecture for interoperation. The workshop provided researchers with necessary feedback from the industrial perspective and helped in identifying the major issues that need further research. The following problems concerning the applicability of the methods proposed for data processing in the heterogeneous, autonomous information systems have been identified: (i) many of the assumptions made in the research community are too restrictive to make the results directly applicable to existing environments; (ii) performance ramifications of various heterogeneous architectures need to be understood; (iii) the prototype systems need to be put to the test with real data, schemas, and transaction streams to verify their utility.

A Unified Model and Methodology for Conceptual Database Design

The event model integrates a set of data structuring and manipulation primitives with a database schema design and evolution methodology. A number of database research efforts have concentrated on expanding the expressiveness of database modelling mechanisms in order to increase the understandability and usability of database conceptual schemas. The event model includes a simple set of such high-level “semantic” modelling constructs; an associated methodology provides prescriptive assistance in the task of specifying and maintaining a conceptual schema. A primary goal of this approach is to reduce the expertise required to design, evolve, and access databases. An interactive database design and evolution system based upon the event model has been implemented and is in use on an experimental basis.

The identification and resolution of semantic heterogeneity in multidatabase systems

Several aspects are given of the Remote-Exchange project at USC, which focuses on the controlled sharing and exchange of information among autonomous, heterogeneous database systems. The spectrum of heterogeneity which may exist among the components in a federation of database systems is examined, and an approach to accommodating such heterogeneity is described. An overview of the Remote-Exchange experimental system is provided.<<ETX>>