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Author

Alfonso F. Cardenas

Other affiliations: University of California, IBM
Bio: Alfonso F. Cardenas is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Query language & Data model. The author has an hindex of 21, co-authored 64 publications receiving 1735 citations. Previous affiliations of Alfonso F. Cardenas include University of California & IBM.


Papers
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Journal ArticleDOI
Alfonso F. Cardenas1
TL;DR: The need to envision and architecture data base systems in a hierarchical level by level framework is stressed, and formulations presented are necessary to be used in conjunction with any index selection criteria to determine the optimum set of index keys.
Abstract: The need to envision and architecture data base systems in a hierarchical level by level framework is stressed. The inverted data base (file) organization is then analyzed, considering implementation oriented aspects. The inverted directory is viewed realistically as another large data base which itself is subjected to inversion. Formulations are derived to estimate average access time (read only) and storage requirements, formalizing the interaction of data base content characteristics, logical complexity of queries, and machine timing and blocking specifications identified as having a first-order effect on performance. The formulations presented are necessary to be used in conjunction with any index selection criteria to determine the optimum set of index keys.

332 citations

Journal ArticleDOI
TL;DR: A knowledge-based approach to retrieve medical images by feature and content with spatial and temporal constructs is developed and the KMeD (Knowledge-based Medical Database) system is implemented using these concepts.
Abstract: A knowledge-based approach to retrieve medical images by feature and content with spatial and temporal constructs is developed. Selected objects of interest in an image are segmented and contours are generated. Features and content are extracted and stored in a database. Knowledge about image features can be expressed as a type abstraction hierarchy (TAH), the high-level nodes of which represent the most general concepts. Traversing TAH nodes allows approximate matching by feature and content if an exact match is not available. TAHs can be generated automatically by clustering algorithms based on feature values in the databases and hence are scalable to large collections of image features. Since TAHs are generated based on user classes and applications, they are context- and user-sensitive. A knowledge-based semantic image model is proposed to represent the various aspects of an image object's characteristics. The model provides a mechanism for accessing and processing spatial, evolutionary and temporal queries. A knowledge-based spatial temporal query language (KSTL) has been developed that extends ODMG's OQL and supports approximate matching of features and content, conceptual terms and temporal logic predicates. Further, a visual query language has been developed that accepts point-click-and-drag visual iconic input on the screen that is then translated into KSTL. User models are introduced to provide default parameter values for specifying query conditions. We have implemented the KMeD (Knowledge-based Medical Database) system using these concepts.

180 citations

Journal ArticleDOI
TL;DR: The PICQUERY/sup +/ language and its underlying stacked image data model are enhanced with major advances that include convenient specification of the data domain space among a multimedia database federation, visualization of underlying data models, knowledge-based hierarchies, and domain rules.
Abstract: PICQUERY/sup +/, a high-level domain-independent query language for pictorial and alphanumeric database management, is introduced. The PICQUERY/sup +/ language and its underlying stacked image data model are enhanced with major advances that include: convenient specification of the data domain space among a multimedia database federation, visualization of underlying data models, knowledge-based hierarchies, and domain rules, understanding of high-level abstract data types, ability to perform data object matches based on imprecise or fuzzy descriptors, imprecise relational correlators, and temporal and object evolutionary events, specification of alphanumeric and image processing algorithms on data, and specification of alphanumeric and image visualization methods for user presentation. The power of PICQUERY/sup +/ is illustrated using examples drawn from the medical imaging domain. A graphical menu-driven user interface is demonstrated for this domain as an example of the menu interface capabilities of PICQUERY/sup +/. >

112 citations

Journal ArticleDOI
TL;DR: A methodology, a model and a programmed system are presented to estimate primarily total storage costs and average access time of several file organizations, given a specific data base, query characterization and device-related specifications.
Abstract: This work first discusses the factors that affect file (data base) organization performance, an elusive subject, and then presents a methodology, a model and a programmed system to estimate primarily total storage costs and average access time of several file organizations, given a specific data base, query characterization and device-related specifications. Based on these estimates, an appropriate file structure may be selected for the specific situation. The system is a convenient tool to study file structures and to facilitate as much as possible the process of data base structure design and evaluation.

91 citations

Journal ArticleDOI
TL;DR: The prototype system to query medical multimedia distributed databases by both image content and alphanumeric content is validated and rules derived from application and domain knowledge, approximate and conceptual queries may be answered.

87 citations


Cited by
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Journal ArticleDOI
Amit P. Sheth, James A. Larson1
TL;DR: In this paper, the authors define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed, and define a methodology for developing one of the popular architectures of an FDBS.
Abstract: A federated database system (FDBS) is a collection of cooperating database systems that are autonomous and possibly heterogeneous. In this paper, we define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed. We then define a methodology for developing one of the popular architectures of an FDBS. Finally, we discuss critical issues related to developing and operating an FDBS.

2,376 citations

Proceedings ArticleDOI
01 Sep 1987
TL;DR: A variation to Guttman’s Rtrees (R+-trees) that avoids overlapping rectangles in intermediate nodes of the tree is introduced and analytical results indicate that R+-Trees achieve up to 50% savings in disk accesses compared to an R-tree when searching files of thousands of rectangles.
Abstract: The problem of indexing multidimensional objects is considered. First, a classification of existing methods is given along with a discussion of the major issues involved in multidimensional data indexing. Second, a variation to Guttman’s Rtrees (R+-trees) that avoids overlapping rectangles in intermediate nodes of the tree is introduced. Algorithms for searching, updating, initial packing and reorganization of the structure are discussed in detail. Finally, we provide analytical results indicating that R+-trees achieve up to 50% savings in disk accesses compared to an R-tree when searching files of thousands of rectangles.

1,481 citations

Journal ArticleDOI
TL;DR: This tutorial introduces the key techniques in the area of text indexing, describing both a core implementation and how the core can be enhanced through a range of extensions.
Abstract: The technology underlying text search engines has advanced dramatically in the past decade. The development of a family of new index representations has led to a wide range of innovations in index storage, index construction, and query evaluation. While some of these developments have been consolidated in textbooks, many specific techniques are not widely known or the textbook descriptions are out of date. In this tutorial, we introduce the key techniques in the area, describing both a core implementation and how the core can be enhanced through a range of extensions. We conclude with a comprehensive bibliography of text indexing literature.

1,218 citations

Journal ArticleDOI
TL;DR: The approach integrates a number of domain-specific high-level features such as pattern class and ridge density at higher levels of the search and incorporates elastic structural feature-based matching for indexing the database at the lowest level.
Abstract: With the current rapid growth in multimedia technology, there is an imminent need for efficient techniques to search and query large image databases. Because of their unique and peculiar needs, image databases cannot be treated in a similar fashion to other types of digital libraries. The contextual dependencies present in images, and the complex nature of two-dimensional image data make the representation issues more difficult for image databases. An invariant representation of an image is still an open research issue. For these reasons, it is difficult to find a universal content-based retrieval technique. Current approaches based on shape, texture, and color for indexing image databases have met with limited success. Further, these techniques have not been adequately tested in the presence of noise and distortions. A given application domain offers stronger constraints for improving the retrieval performance. Fingerprint databases are characterized by their large size as well as noisy and distorted query images. Distortions are very common in fingerprint images due to elasticity of the skin. In this paper, a method of indexing large fingerprint image databases is presented. The approach integrates a number of domain-specific high-level features such as pattern class and ridge density at higher levels of the search. At the lowest level, it incorporates elastic structural feature-based matching for indexing the database. With a multilevel indexing approach, we have been able to reduce the search space. The search engine has also been implemented on Splash 2-a field programmable gate array (FPGA)-based array processor to obtain near-ASIC level speed of matching. Our approach has been tested on a locally collected test data and on NIST-9, a large fingerprint database available in the public domain.

725 citations

Journal ArticleDOI
TL;DR: These methods are presented in the framework of a general query evaluation procedure using the relational calculus representation of queries, and nonstandard query optimization issues such as higher level query evaluation, query optimization in distributed databases, and use of database machines are addressed.
Abstract: Efficient methods of processing unanticipated queries are a crucial prerequisite for the success of generalized database management systems. A wide variety of approaches to improve the performance of query evaluation algorithms have been proposed: logic-based and semantic transformations, fast implementations of basic operations, and combinatorial or heuristic algorithms for generating alternative access plans and choosing among them. These methods are presented in the framework of a general query evaluation procedure using the relational calculus representation of queries. In addition, nonstandard query optimization issues such as higher level query evaluation, query optimization in distributed databases, and use of database machines are addressed. The focus, however, is on query optimization in centralized database systems.

702 citations