Michael V. Mannino

Statistical profile estimation in database systems

A statistical profile summarizes the instances of a database. It describes aspects such as the number of tuples, the number of values, the distribution of values, the correlation between value sets, and the distribution of tuples among secondary storage units. Estimation of database profiles is critical in the problems of query optimization, physical database design, and database performance prediction. This paper describes a model of a database of profile, relates this model to estimating the cost of database operations, and surveys methods of estimating profiles. The operators and objects in the model include build profile, estimate profile, and update profile. The estimate operator is classified by the relational algebra operator (select, project, join), the property to be estimated (cardinality, distribution of values, and other parameters), and the underlying method (parametric, nonparametric, and ad-hoc). The accuracy, overhead, and assumptions of methods are discussed in detail. Relevant research in both the database and the statistics disciplines is incorporated in the detailed discussion.

Introduction to Data Mining and Knowledge Discovery

While knowledge discovery often refers to the process of discovering useful knowledge from data, data mining focuses on the application of algorithms for extracting patterns from data. Knowledge discovery seeks to find patterns in data and to infer rules (that is, to discover new information) that queries and reports do not reveal effectively. Thus, knowledge discovery has a R&D flavor and data mining an operational process one. Data mining is a basis of knowledge discovery.

Information technology acceptance in the internal audit profession: Impact of technology features and complexity

Although various information technologies have been studied using the technology acceptance model (TAM), the study of acceptance of specific technology features for professional groups employing information technologies such as internal auditors (IA) has been limited. To address this gap, we extended the TAM for technology acceptance among IA professionals and tested the model using a sample of internal auditors provided by the Institute of Internal Auditors (IIA). System usage, perceived usefulness, and perceived ease of use were tested with technology features and complexity. Through the comparison of TAM variables, we found that technology features were accepted by internal auditors in different ways. The basic features such as database queries, ratio analysis, and audit sampling were more accepted by internal auditors while the advanced features such as digital analysis, regression/ANOVA, and classification are less accepted by internal auditors. As feature complexity increases, perceived ease of use decreased so that system usage decreased. Through the path analysis between TAM variables, the results indicated that path magnitudes were significantly changed by technology features and complexity. Perceived usefulness had more influence on feature acceptance when basic features were used, and perceived ease of use had more impact on feature acceptance when advanced features were used.

An expert database design system based on analysis of forms

A form model and an expert database system that analyzes instances of the form model to derive a conceptual schema are proposed. The form model describes the properties of form fields such as their origin, hierarchical structure, and cardinality. The expert database design system creates a conceptual schema by incrementally integrating related collections of forms. The rules of the expert systems are divided into six phases form selection; entity identification; attribute attachment; relationship identification; cardinality identification; and integrity constraints. The rules of the first phase use knowledge about the form flow to determine the order in which forms are analyzed. The rules in other phases are used in conjunction with a designer dialog to identify the entities, relationships, and attributes of a schema that represents the collection of forms. >

The Integrated Dictionary/Directory System

The concept of an integrated Dictionary/Directory (D/D) System is discussed in detail, and the state of current systems in both the centralized and distributed database environments is surveyed For the centrahzed database environment, three aspects are emphasized: (1) the software tnterfaces between the D / D System and other software packages, (2) the convert functmns of the D / D System, and (3) the environmental dependency between the D / D System and a Database Management System (DBMS). For the distributed database environment, the artmle elucidates the necessary extensions to the centrahzed D/D, the additional software interfaces required, and the use of the D / D as a distributed database. An example of a commercial D / D System that is integrated with a distributed DBMS is presented.

A form-based approach for database analysis and design

ost organizations use business forms to conduct daily operations and to communicate internally and externally with customers, suppliers, government agencies, and other entities. Traditionally, paper forms have been used and stored with obvious disadvantages of high retrieval and storage cost. With advances in computing technology, electronic forms have begun to supplant their paper counterparts. A number of form management systems have been developed [7, 11, 12, 18, 191. Typically, these systems are closely integrated with a

Efficiency evaluation of data warehouse operations

We evaluate an efficiency model for data warehouse operations using data from USA and non-USA-based (mostly Korean) organizations. The analysis indicates wide dispersions in operational efficiency, industry and region differences, large differences in labor budgets between efficient and inefficient firms, few organizations efficient in both refresh processing and query production, and difficulty of providing some variables. Follow-up interviews provide insights about the value of efficiency comparisons of information technology organizations and suggestions to improve the model. Using this analysis, we propose a framework containing data warehouse characteristics and firm characteristics to explain IT operational efficiency at the subfirm level.

Model Libraries: Knowledge Representation and Reasoning

We propose a knowledge representation and operators for large, diverse model libraries. The knowledge representation distinguishes between model types that are classes of models defined by a collection of assumptions and model templates and instances that instantiate model types through decomposition and specialization of components. Underlying the knowledge representation are inheritance to represent the level of generalization and multiple levels of instantiation to represent the level of details among models. For inheritance, we define partial order relations for models and their components including domains, classes, units, assumptions, metrics, and constraints. For instantiation, we define constraints on transformations between model types, templates, and instances. The inexact search operators support content-based retrieval especially when it is difficult for a user to exactly specify the characteristics of models of interest. The operators use similarity functions to measure the closeness of a mat...

Extensions to query languages for graph traversal problems

Extensions to database query languages for retrievals that involve inferencing on the nodes and edges of a graph are surveyed. Common types of inferencing are to find paths between two nodes, compute a value for a path such as a distance or an elapsed time, and to choose among alternative paths. The survey is based on the data model (relational or functional), method of extension (iteration, recursion, or special operators), interface style (string or tabular), and restrictions (data- and problem-oriented). The Quel, objected-oriented functional data, G-Whin, and Alpha languages are examined in detail with different values for these properties. The characteristics of other languages are summarized in several tables. The results of the survey indicate the diversity of language extensions and the need to provide data-model and query-language features to address such problems. >

Matching techniques in global schema design

A global schema is an integrated view of heterogeneous databases. Identifying common types of information from the various local Schemas is an important part of designing a global schema. After matching the entity types and attributes, the designer constructs the global schema by applying a set of integration operators. In this paper, we propose two types of matching techniques and discuss their use in global schema design. Entity type matching partitions the entity types of the local Schemas into subsets with common information. Attributes within each entity type cluster are then matched according to the similarity of their meaning and scope. We define assertion types for both kinds of matching and provide an algorithm to check the consistency and completeness of attribute assertions.