The Impact of Global Clustering on Spatial Database Systems

Global clustering has rarely been investigated in the area of spatial database systems although dramatic performance improvements can be achieved by using suitable techniques. In this paper, we propose a simple approach to global clustering called cluster organization. We will demonstrate that this cluster organization leads to considerable performance improvements without any algorithmic overhead. Based on real geographic data, we perform a detailed empirical performance evaluation and compare the cluster organization to other organization models not using global clustering. We will show that global clustering speeds up the processing of window queries as well as spatial joins without decreasing the performance of the insertion of new objects and of selective queries such as point queries. The spatial join is sped up by a factor of about 4, whereas non-selective window queries are accelerated by even higher speed up factors

Protocols for Integrity Constraint Checking in Federated Databases

A federated database is comprised of multiple interconnected database systems that primarily operate independently but cooperate to a certain extent. Global integrity constraints can be very useful in federated databases, but the lack of global queries, global transaction mechanisms, and global concurrency control renders traditional constraint management techniques inapplicable. This paper presents a threefold contribution to integrity constraint checking in federated databases: (1) The problem of constraint checking in a federated database environment is clearly formulated. (2) A family of protocols for constraint checking is presented. (3) The differences across protocols in the family are analyzed with respect to system requirements, properties guaranteed by the protocols, and processing and communication costs. Thus, our work yields a suite of options from which a protocol can be chosen to suit the system capabilities and integrity requirements of a particular federated database environment

PARNT: A statistic based approach to extract non-taxonomic relationships of ontologies from text

Learning Non-Taxonomic Relationships is a subfield of Ontology learning that aims at automating the extraction of these relationships from text. This article proposes PARNT, a novel approach that supports ontology engineers in extracting these elements from corpora of plain English. PARNT is parametrized, extensible and uses original solutions that help to achieve better results when compared to other techniques for extracting non-taxonomic relationships from ontology concepts and English text. To evaluate the PARNT effectiveness, a comparative experiment with another state of the art technique was conducted.This work is supported by CNPq and CAPES, research funding agencies of the Brazilian government

On the Nature and Types of Anomalies: A Review

Anomalies are occurrences in a dataset that are in some way unusual and do not fit the general patterns. The concept of the anomaly is generally ill-defined and perceived as vague and domain-dependent. Moreover, despite some 250 years of publications on the topic, no comprehensive and concrete overviews of the different types of anomalies have hitherto been published. By means of an extensive literature review this study therefore offers the first theoretically principled and domain-independent typology of data anomalies, and presents a full overview of anomaly types and subtypes. To concretely define the concept of the anomaly and its different manifestations, the typology employs five dimensions: data type, cardinality of relationship, anomaly level, data structure and data distribution. These fundamental and data-centric dimensions naturally yield 3 broad groups, 9 basic types and 61 subtypes of anomalies. The typology facilitates the evaluation of the functional capabilities of anomaly detection algorithms, contributes to explainable data science, and provides insights into relevant topics such as local versus global anomalies.Comment: 38 pages (30 pages content), 10 figures, 3 tables. Preprint; review comments will be appreciated. Improvements in version 2: Explicit mention of fifth anomaly dimension; Added section on explainable anomaly detection; Added section on variations on the anomaly concept; Various minor additions and improvement

Flexible Relations - Operational Support of Variant Relational Struetures

The relational model is accepted for its simplicity and eIegance. At the other side the simplicity causes the problem, that most semantic type constructs are not representable as a simple relation. Variant and heterogeneous structures belong to those constructs not adequatly supported by the simple relational model. In this paper we give an overview of the model of flexible relations that allows to model and process arbitrary heterogeneous structures, while preserving the relational philosophy of operating with a single constructor. As flexible relations support both the modeling and the operational aspect of variant structures seamlessly, our model truly helps to further bridge the gap between semantic and operational data models. We discuss the structural part of the moQ.el and introduce an algebra for flexible relations. Further we examine a subdass of flexible relations, that can be processed as efficiently as the simple relational model, and show that this subdass possesses desirable structural normal form properties. In addition, we point out that our approach exceeds the objectoriented paradigm in modeling power, typing precision, and query optimization potential

Video browsing interfaces and applications: a review

We present a comprehensive review of the state of the art in video browsing and retrieval systems, with special emphasis on interfaces and applications. There has been a significant increase in activity (e.g., storage, retrieval, and sharing) employing video data in the past decade, both for personal and professional use. The ever-growing amount of video content available for human consumption and the inherent characteristics of video data—which, if presented in its raw format, is rather unwieldy and costly—have become driving forces for the development of more effective solutions to present video contents and allow rich user interaction. As a result, there are many contemporary research efforts toward developing better video browsing solutions, which we summarize. We review more than 40 different video browsing and retrieval interfaces and classify them into three groups: applications that use video-player-like interaction, video retrieval applications, and browsing solutions based on video surrogates. For each category, we present a summary of existing work, highlight the technical aspects of each solution, and compare them against each other