Nearly Periodic Facts in Temporal Relational Databases

Despite the huge amount of work devoted to the treatment of time within the relational context, few relevant temporal phenomena still remain to be addressed. One of them is the treatment of \u201cnearly periodic events\u201d, i.e., eventsacts that occur in intervals of time which repeat periodically (e.g., a meeting occurring twice each Monday, possibly not at regular times). Nearly periodic events are quite frequent in everyday life, and thus in many applicative contexts. Their treatment within the relational model is quite challenging, since it involves the integrated treatment of three aspects: (i) the number of repetitions, (ii) their periodicity, and (iii) temporal indeterminacy. Coping with this problem requires an in-depth extension of current temporal relational database techniques. In this paper, we introduce a new data model, and new definitions of relational algebraic operators coping with the above issues. We ascertain the properties of the new model and algebra, with emphasis on the expressiveness of our representation model, on the reducibility property, and on the correctness of the algebraic operators

Dynamic context adaptation in multimedia documents

ABSTRACT Multimedia documents are collections of media objects, synchronized by means of sets of temporal and spatial constraints. Any multimedia document definition is valid as long as the referred media objects are available and the constraints are satisfiable. Document validity depends on the context in which the document has to be presented. In this paper, we introduce a framework to characterize context adaptation, in the presence of both physical and user oriented context requirements. We define semantically equivalent presentation fragments as alternative to undeliverable ones. In the absence of equivalence, undeliverable media are replaced with candidates that minimize the loss of information/quality in the presentation

Unterstützung von Periodizität in Informationssystemen - Herausforderungen und Lösungsansätze

Die systemseitige Unterstützung von Periodizität bzw. periodischen Spezifikationen weist Anforderungen auf, die weit über die temporalen Fähigkeiten heutiger Informationssysteme hinausgehen. Im Allgemeinen charakterisieren periodische Spezifikationen Vorgänge, die aus regelmäßig wiederkehrenden Aktivitäten bestehen. Neben der Ausdrucksstärke ist die größte Herausforderung periodische Spezifikationen miteinander vergleichen zu können. Diese Vergleichbarkeit ist ein wichtiger Aspekt in einer Vielzahl von Anwendungen, etwa um vorausschauend sich eventuell ergebende potentielle Ressourcen- oder Terminkonflikte erkennen zu können. Erschwert wird dieses durch unterschiedliche (zeitliche) Granularitäten sowie Ausnahmen in entsprechenden Spezifikationen. Für den praktischen Einsatz ist es darüber hinaus unumgänglich, periodische Zusammenhänge auch im Kontext einer großen (umfangreichen) Menge periodischer Daten effizient verwalten und auswerten zu können. Der vorliegende Beitrag gibt einen Einblick in die Herausforderungen sowie einen Überblick zu in der aktuellen Literatur vorliegenden Lösungsansätzen einer systemseitigen Unterstützung von periodischen Spezifikationen

A knowledge server for reasoning about temporal constraints between classes and instances of events

An outstanding example of early Reformation dress, notice the geometric fabric design, the fur-trimmed collar of the coat, and the decorative shir

An algebraic representation of calendars.

This paper uses an algebraic approach to define temporal granularities and calendars. All the granularities in a calendar are expressed as algebraic expressions based on a single "bottom" granularity. The operations used in the algebra directly reflect the ways with which people construct new granularities from existing ones, and hence yield more natural and compact granularities definitions. Calendar is formalized on the basis of the algebraic operations, and properties of calendars are studied. As a step towards practical applications, the paper also presents algorithms for granule conversions between granularities in a calendar

Supporting Temporal Reasoning by Mapping Calendar Expressions to Minimal Periodic Sets

In the recent years several research efforts have focused on the concept of time granularity and its applications. A first stream of research investigated the mathematical models behind the notion of granularity and the algorithms to manage temporal data based on those models. A second stream of research investigated symbolic formalisms providing a set of algebraic operators to define granularities in a compact and compositional way. However, only very limited manipulation algorithms have been proposed to operate directly on the algebraic representation making it unsuitable to use the symbolic formalisms in applications that need manipulation of granularities. This paper aims at filling the gap between the results from these two streams of research, by providing an efficient conversion from the algebraic representation to the equivalent low-level representation based on the mathematical models. In addition, the conversion returns a minimal representation in terms of period length. Our results have a major practical impact: users can more easily define arbitrary granularities in terms of algebraic operators, and then access granularity reasoning and other services operating efficiently on the equivalent, minimal low-level representation. As an example, we illustrate the application to temporal constraint reasoning with multiple granularities. From a technical point of view, we propose an hybrid algorithm that interleaves the conversion of calendar subexpressions into periodical sets with the minimization of the period length. The algorithm returns set-based granularity representations having minimal period length, which is the most relevant parameter for the performance of the considered reasoning services. Extensive experimental work supports the techniques used in the algorithm, and shows the efficiency and effectiveness of the algorithm

Symbolic Representation of User-defined Time Granularities

In the recent literature on time representation, an effort has been made to characterize the notion of time granularity and the relationships between granularities, in order to have a common framework for their specification, and to allow the interoperability of systems adopting different time granularities. This paper considers the mathematical characterization of finite and periodical time granularities, and it identifies a user-friendly symbolic formalism which captures exactly that class of granularities. This is achieved by a formal analysis of the expressiveness of well-known symbolic representation formalisms. 1. Introduction There is a wide agreement in the AI and database community on the requirement for a data/knowledge representation system of supporting standard as well as user-defined time granularities. Examples of standard time granularities are days, weeks, months, while user defined granularities may include businessweeks, trading-days, working-shifts, school-terms, wi..