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Group-by is a core database operation that is used extensively in OLTP, OLAP, and decision support systems. In many application scenarios, it is required to group similar but not necessarily equal values. In this paper we propose a new SQL construct that supports similarity-based group-by (SGB). SGB is not a new clustering algorithm, but rather is a practical and fast similarity grouping query operator...
Context is any information used to characterize the situation of an entity. Examples of contexts include time, location, identity, and activity of a user. This paper proposes a general context-aware DBMS, named Chameleon, that will eliminate the need for having specialized database engines, e.g., spatial DBMS, temporal DBMS, and Hippocratic DBMS, since space, time, and identity can be treated as contexts...
Privacy preservation has become an important requirement in information systems that deal with personal data. In many cases this requirement is imposed by laws that recognize the right of data owners to control whom their information is shared with and the purposes for which it can be shared. Hippocratic databases have been proposed as an answer to this privacy requirement; they extend the architecture...
We demonstrate bdbms, an extensible database engine for biological databases, bdbms started on the observation that database technology has not kept pace with the specific requirements of biological databases and that several needed key functionalities are not supported at the engine level. While bdbms aims at supporting several of these functionalities, this demo focuses on: (1) Annotation and provenance...
Space-partitioning trees, like the disk-based trie, quadtree, kd-tree and their variants, are a family of access methods that index multi-dimensional objects. In the case of indexing non-zero extent objects, e.g., line segments and rectangles, space-partitioning trees may replicate objects over multiple space partitions, e.g., PMR quadtree, expanded MX-CIF quadtree, and extended kd-tree. As a result,...
The wide spread use of cellular phones, handheld devices, and GPS-like technology enables location-aware environments where virtually all objects are aware of their locations. Such environments call for new query processing techniques that deal with the continuous movement of both spatio-temporal objects and queries. The goal of this tutorial is to: (1) Give an in-depth view on supporting location-aware...
Spatio-temporal data streams that are generated from mobile stream sources (e.g., mobile sensors) experience similar environmental conditions that result in distinct phenomena. Several research efforts are dedicated to detect and track various phenomena inside a data stream management system (DSMS). In this paper, we use the detected phenomena to reduce the demand on the DSMS resources. The main idea...
In this paper, we introduce PLACE*, a distributed spatio-temporal data stream management system for moving objects. PLACE* supports continuous spatio-temporal queries that hop among a network of regional servers. To minimize the execution cost, a new Query-Track- Participate (QTP) query processing model is proposed inside PLACE*. In the QTP model, a query is continuously answered by a querying server,...
Presenting privacy has become a crucial requirement for operating a business that manages personal data. Hippocratic databases have been proposed to answer this requirement through a database design that includes responsibility for the privacy of data as a founding tenet. We identify, study, and implement several privacy-preserving features that extend the previous work on Limiting Disclosure in Hippocratic...
Sensor devices are becoming ubiquitous, especially in measurement and monitoring applications. Because of the real-time, append-only and semi-infinite natures of the generated sensor data streams, an online incremental approach is a necessity for mining stream data types. In this paper, we propose STAGGER: a one-pass, online and incremental algorithm for mining periodic patterns in data streams. STAGGER...
A phenomenon appears in a sensor network when a group of sensors persist to generate similar behavior over a period of time. PhenomenaBases (or databases of phenomena) are equipped with phenomena detection and tracking (PDT) techniques that continuously run in the background of a sensor database system to detect new phenomena and to track already existing phenomena. The process of phenomena detection...
Abstract. An intelligent annotation-based video data model called Smart VideoText is introduced. It utilizes the conceptual graph knowledge representation formalism to capture the semantic associations among the concepts described in text annotations of video data. The aim is to achieve more effective query, retrieval, and browsing capabilities based on the semantic content of video data. Finally,...
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