Allen's Relations Research Articles

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen’s temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

A complete classification of the expressiveness of interval logics of Allen’s relations: the general and the dense cases

Interval temporal logics take time intervals, instead of time points, as their primitive temporal entities. One of the most studied interval temporal logics is Halpern and Shoham's modal logic of time intervals HS, which associates a modal operator with each binary relation between intervals over a linear order (the so-called Allen's interval relations). In this paper, we compare and classify the expressiveness of all fragments of HS on the class of all linear orders and on the subclass of all dense linear orders. For each of these classes, we identify a complete set of definabilities between HS modalities, valid in that class, thus obtaining a complete classification of the family of all 4096 fragments of HS with respect to their expressiveness. We show that on the class of all linear orders there are exactly 1347 expressively different fragments of HS, while on the class of dense linear orders there are exactly 966 such expressively different fragments.

Fast time intervals mining using the transitivity of temporal relations

We introduce an algorithm, called KarmaLego, for the discovery of frequent symbolic time interval-related patterns (TIRPs). The mined symbolic time intervals can be part of the input, or can be generated by a temporal-abstraction process from raw time-stamped data. The algorithm includes a data structure for TIRP-candidate generation and a novel method for efficient candidate-TIRP generation, by exploiting the transitivity property of Allen's temporal relations. Additionally, since the non-ambiguous definition of TIRPs does not specify the duration of the time intervals, we propose to pre-cluster the time intervals based on their duration to decrease the variance of the supporting instances. Our experimental comparison of the KarmaLego algorithm's runtime performance with several existing state of the art time intervals pattern mining methods demonstrated a significant speed-up, especially with large datasets and low levels of minimal vertical support. Furthermore, pre-clustering by time interval duration led to an increase in the homogeneity of the duration of the discovered TIRP's supporting instances' time intervals components, accompanied, however, by a corresponding decrease in the number of discovered TIRPs.

Interval-based temporal functional dependencies: specification and verification

In the temporal database literature, every fact stored in a database may be equipped with two temporal dimensions: the valid time, which describes the time when the fact is true in the modeled reality, and the transaction time, which describes the time when the fact is current in the database and can be retrieved. Temporal functional dependencies (TFDs) add valid time to classical functional dependencies (FDs) in order to express database integrity constraints over the flow of time. Currently, proposals dealing with TFDs adopt a point-based approach, where tuples hold at specific time points, to express integrity constraints such as "for each month, the salary of an employee depends only on his role". To the best of our knowledge, there are no proposals dealing with interval-based temporal functional dependencies (ITFDs), where the associated valid time is represented by an interval and there is the need of representing both point-based and interval-based data dependencies. In this paper, we propose ITFDs based on Allen's interval relations and discuss their expressive power with respect to other TFDs proposed in the literature: ITFDs allow us to express interval-based data dependencies, which cannot be expressed through the existing point-based TFDs. ITFDs allow one to express constraints such as "employees starting to work the same day with the same role get the same salary" or "employees with a given role working on a project cannot start to work with the same role on another project that will end before the first one". Furthermore, we propose new algorithms based on B-trees to efficiently verify the satisfaction of ITFDs in a temporal database. These algorithms guarantee that, starting from a relation satisfying a set of ITFDs, the updated relation still satisfies the given ITFDs.

Procedural Steps for Knowledge Mining in Time Series

intervals which form temporal patterns are usually formulated through Allen's interval relations that originate in temporal reasoning. But this representation is not advantages for knowledge discovery. The Hierarchical Time series Knowledge Representation (HTKR) is the hierarchical language which expresses the temporal aspects of coincidence and partial order, for interval patterns. We present mining procedural steps which are more efficient, effective and based on item set techniques. Pruning of the search space minimizes the mining result size considerably, thereby speeding up the procedural steps and easing the interpretations. When applied on the real data set, HTKR can provide the explanation of underlying temporal phenomena, but whereas the numerous Allen's relation patterns only explains fragmented data.

Automatic Learning of Temporal Relations Under the Closed World Assumption

Time plays an important role in the vast majority of problems and, as such, it is a vital issue to be considered when developing computer systems for solving problems. In the literature, one of the most influential formalisms for representing time is known as Allen's Temporal Algebra based on a set of 13 relations basic and reversed that may hold between two time intervals. In spite of having a few drawbacks and limitations, Allen's formalism is still a convenient representation due to its simplicity and implementability and also, due to the fact that it has been the basis of several extensions. This paper explores the automatic learning of Allen's temporal relations by the inductive logic programming system FOIL, taking into account two possible representations for a time interval: i as a primitive concept and ii as a concept defined by the primitive concept of time point. The goals of the experiments described in the paper are 1 to explore the viability of both representations for use in automatic learning; 2 compare the facility and interpretability of the results; 3 evaluate the impact of the given examples for inducing a proper representation of the relations and 4 experiment with both representations under the assumption of a closed world CWA, which would ease continuous learning using FOIL. Experimental results are presented and discussed as evidence that the CWA can be a convenient strategy when learning Allen's temporal relations.

ON BEGINS, MEETS AND BEFORE

Interval temporal logics (ITLs) are logics for reasoning about temporal statements expressed over intervals, i.e., periods of time. The most famous temporal logic for intervals studied so far is probably Halpern and Shoham's HS, which is the logic of the thirteen Allen's interval relations. Unfortunately, HS and most of its fragments are undecidable. This discouraged the research in this area until recently, when a number non-trivial decidable ITLs have been discovered. This paper is a contribution towards the complete classification of all different fragments of HS. We consider here different combinations of the interval relations begins (B), meets (A), later (L) and their inverses [Formula: see text], [Formula: see text] and [Formula: see text]. We know from previous work that the combination [Formula: see text] is decidable only when finite domains are considered (and undecidable elsewhere), and that [Formula: see text] is decidable over the natural numbers. In the present paper we show that, over strongly discrete linear models (e.g. finite orders, the naturals, the integers), decidability of [Formula: see text] can be further extended to capture the language [Formula: see text], which lies strictly in between [Formula: see text] and [Formula: see text]. The logic [Formula: see text] turns out to be maximal w.r.t decidability over the considered classes, and its satisfiability problem is EXPSPACE-complete. In this paper we also provide an optimal non-deterministic decision procedure, and we show that the language is powerful enough to polynomially encode metric constraints on the length of the current interval.

Crossing the Undecidability Border with Extensions of Propositional Neighborhood Logic over Natural Numbers

Propositional Neighborhood Logic (PNL) is an interval temporal logic featuring two modalities corresponding to the relations of right and left neighborhood between two intervals on a linear order (in terms of Allen's relations, meets and met by). Recently, it has been shown that PNL interpreted over several classes of linear orders, including natural numbers, is decid- able (NEXPTIME-complete) and that some of its natural extensions preserve decidability. Most notably, this is the case with PNL over natural numbers extended with a limited form of metric constraints and with the future fragment of PNL extended with modal operators corresponding to Allen's relations begins, begun by, and before. This paper aims at demonstrating that PNL and its metric version MPNL, interpreted over natural numbers, are indeed very close to the border with undecidability, and even relatively weak extensions of them become undecidable. In particular, we show that (i) the addition of binders on integer variables ranging over interval lengths makes the resulting hybrid extension of MPNL undecidable, and (ii) a very weak first-order extension of the future fragment of PNL, obtained by replacing proposition letters by a restricted subclass of first-order formulae where only one variable is allowed, is undecidable (in contrast with the decidability of similar first-order extensions of point-based temporal logics).

On the improvement of combined fuzzy topological and directional relations information

Concept of combined extraction of topological and directional relations information developed by Zahzah et al. [1] by employing the Allen's temporal relations in 1D spatial domain was improved by Matsakis and Nikitenko [2]. This latter algorithm has high computational complexity due to its limitations of object approximation and segment fuzzification. In this paper, fuzzy Allen relations are used to define the fuzzy topological and directional relations information between different objects. Some extended results of Salamat and Zahzah [3] are discussed. Polygonal object approximation allows us to use fuzzy operators and this approach reduces computational complexity of the method for computing the combined topological and directional relations. To validate the method, some experiments are tested giving satisfactory and promising results. Affine transformation are depicted, these properties will be helpful for using the method in other areas of image analysis such as object tracking.

Begin, After, and Later: a Maximal Decidable Interval Temporal Logic

Interval temporal logics (ITLs) are logics for reasoning about temporal statements expressed over intervals, i.e., periods of time. The most famous ITL studied so far is Halpern and Shoham's HS, which is the logic of the thirteen Allen's interval relations. Unfortunately, HS and most of its fragments have an undecidable satisfiability problem. This discouraged the research in this area until recently, when a number non-trivial decidable ITLs have been discovered. This paper is a contribution towards the complete classification of all different fragments of HS. We consider different combinations of the interval relations Begins, After, Later and their inverses Abar, Bbar, and Lbar. We know from previous works that the combination ABBbarAbar is decidable only when finite domains are considered (and undecidable elsewhere), and that ABBbar is decidable over the natural numbers. We extend these results by showing that decidability of ABBar can be further extended to capture the language ABBbarLbar, which lays in between ABBar and ABBbarAbar, and that turns out to be maximal w.r.t decidability over strongly discrete linear orders (e.g. finite orders, the naturals, the integers). We also prove that the proposed decision procedure is optimal with respect to the complexity class.

Undecidability of the Logic of Overlap Relation over Discrete Linear Orderings

The validity/satisfiability problem for most propositional interval temporal logics is (highly) undecidable, under very weak assumptions on the class of interval structures in which they are interpreted. That, in particular, holds for most fragments of Halpern and Shoham's interval modal logic HS. Still, decidability is the rule for the fragments of HS with only one modal operator, based on an Allen's relation. In this paper, we show that the logic O of the Overlap relation, when interpreted over discrete linear orderings, is an exception. The proof is based on a reduction from the undecidable octant tiling problem. This is one of the sharpest undecidability result for fragments of HS.

Relative positions in words: a system that builds descriptions around Allen relations

In this paper, we introduce a system able to generate an intuitive, human‐like linguistic description of the topological relationships between two objects. The description includes approximate terms commonly found in daily communications. It attempts to capture the essential characteristics of the relationships, while leaving out superfluous and possibly overwhelming detail. The objects are 2‐D image objects. They need not be convex, nor connected, and they may have holes in them. Each description is built around Allen relations, based on information extracted from F‐histograms. It consists of a topological component that indicates the primary topological relationships, directional estimates of where these relationships are most prominent, and a self‐assessment component which reflects the complexity of the situation. Experiments on synthetic and real data validate the approach.

Hierarchical model for web multimedia documents retrieval and periodical updates

PurposeThe purpose of this paper is to propose a four‐level hierarchy model for multimedia documents representation to be used during the dynamic scheduling and altering of multimedia contents.Design/methodology/approachThe four‐level hierarchy model (object, operation, timing, and precedence), offers a fine‐grain representation of multimedia contents and is embedded within a research tool, which is called WEBCAP. WEBCAP utilizes the four‐level hierarchy to synchronize the retrieval of objects in the multimedia document employing Allen's temporal relations, and then applies the Bellman‐Ford's algorithm on the precedence graph to schedule all operations (fetch, transmit, process, and render), while satisfying the in‐time updating and all web workload's resources constraints.FindingsThe experimental results demonstrate the effectiveness of the model in scheduling the periodical updating multimedia documents while considering a variety of workloads on web/TCP.Research limitations/implicationsWEBCAP should be enhanced to automatically measure and/or approximate the available bandwidth of the system using sophisticated measurement of end‐to‐end connectivity. In addition, WEBCAP should be expanded and enhanced to examine system infrastructure for more real‐time applications, such as tele‐medicine and e‐learning.Practical implicationsWEBCAP can be used as an XML markup language for describing multimedia presentations. It can be used to create online presentations similar to PowerPoint on desktop environment, or used as an interactive e‐learning tool. An HTML browser may use a WEBCAP plug‐in to display a WEBCAP document embedded in an HTML/XML page.Originality/valueThis paper proposed a dynamic scheduling of multimedia documents with frequent updates taking into consideration the network's workload to reduce the packet lost ratio in the TCP flow, especially in the early stages. WEBCAP can be used to guide distributed systems designers/managers to schedule or tune their resources for optimal or near optimal performance, subject to minimizing the cost of document retrieval while satisfying the in time constraints.

Fuzzifying Allen's Temporal Interval Relations

When the time span of an event is imprecise, it can be represented by a fuzzy set, called a fuzzy time interval. In this paper, we propose a framework to represent, compute, and reason about temporal relationships between such events. Since our model is based on fuzzy orderings of time points, it is not only suitable to express precise relationships between imprecise events (ldquoRoosevelt died before the beginning of the Cold Warrdquo) but also imprecise relationships (ldquoRoosevelt died just before the beginning of the Cold Warrdquo). We show that, unlike previous models, our model is a generalization that preserves many of the properties of the 13 relations Allen introduced for crisp time intervals. Furthermore, we show how our model can be used for efficient fuzzy temporal reasoning by means of a transitivity table. Finally, we illustrate its use in the context of question answering systems.

Genepi: a blackboard framework for genome annotation

BackgroundGenome annotation can be viewed as an incremental, cooperative, data-driven, knowledge-based process that involves multiple methods to predict gene locations and structures. This process might have to be executed more than once and might be subjected to several revisions as the biological (new data) or methodological (new methods) knowledge evolves. In this context, although a lot of annotation platforms already exist, there is still a strong need for computer systems which take in charge, not only the primary annotation, but also the update and advance of the associated knowledge. In this paper, we propose to adopt a blackboard architecture for designing such a systemResultsWe have implemented a blackboard framework (called Genepi) for developing automatic annotation systems. The system is not bound to any specific annotation strategy. Instead, the user will specify a blackboard structure in a configuration file and the system will instantiate and run this particular annotation strategy. The characteristics of this framework are presented and discussed. Specific adaptations to the classical blackboard architecture have been required, such as the description of the activation patterns of the knowledge sources by using an extended set of Allen's temporal relations. Although the system is robust enough to be used on real-size applications, it is of primary use to bioinformatics researchers who want to experiment with blackboard architectures.ConclusionIn the context of genome annotation, blackboards have several interesting features related to the way methodological and biological knowledge can be updated. They can readily handle the cooperative (several methods are implied) and opportunistic (the flow of execution depends on the state of our knowledge) aspects of the annotation process.

Modal Logics of Topological Relations

Logical formalisms for reasoning about relations between spatial regions play a fundamental role in geographical information systems, spatial and constraint databases, and spatial reasoning in AI. In analogy with Halpern and Shoham's modal logic of time intervals based on the Allen relations, we introduce a family of modal logics equipped with eight modal operators that are interpreted by the Egenhofer-Franzosa (or RCC8) relations between regions in topological spaces such as the real plane. We investigate the expressive power and computational complexity of logics obtained in this way. It turns out that our modal logics have the same expressive power as the two-variable fragment of first-order logic, but are exponentially less succinct. The complexity ranges from (undecidable and) recursively enumerable to highly undecidable, where the recursively enumerable logics are obtained by considering substructures of structures induced by topological spaces. As our undecidability results also capture logics based on the real line, they improve upon undecidability results for interval temporal logics by Halpern and Shoham. We also analyze modal logics based on the five RCC5 relations, with similar results regarding the expressive power, but weaker results regarding the complexity.

The algebra [formula omitted]: a framework for qualitative fuzzy temporal reasoning

The aim of this work is to integrate the ideas of flexibility and uncertainty into Allen's interval-based temporal framework, defining a new formalism, called IA fuz , which extends classical Interval Algebra (IA), in order to express qualitative fuzzy constraints between intervals. We generalize the classical operations between IA-relations to IA fuz -relations, as well as the concepts of minimality and local consistency, referring to the framework of Fuzzy Constraint Satisfaction Problem. We analyze the most interesting reasoning tasks in our framework, which generalize the classical problems of checking consistency, finding a solution and computing the minimal network in the context of IA. In order to solve these tasks, we devise two constraint propagation algorithms and a Branch & Bound algorithm. Since these tasks are NP-difficult, we address the problem of finding tractable sub-algebras of IA fuz , by extending to our fuzzy framework the classical pointizable sub-algebras SA c and SA, as well as the maximal tractable subalgebra H introduced by Nebel. In particular, we prove that the fuzzy extension of the latter, called H fuz , shares with its classical counterpart a maximality property, in that it is the unique maximal subalgebra of IA fuz which contains the fuzzy extensions of Allen's atomic relations.

Speaking with spatial relations

Natural language descriptions are an important step in bridging the gap between numerical representations of spatial data and the human user. In this work, we present a system for generating linguistic descriptions of the spatial relationships between two-dimensional objects. The most pertinent relations for the description are chosen based on a fuzzification of the set relations DISJOINT, OVERLAP, SUBSET, SUBSETi and EQUAL. A handful of relevant Allen relations is then selected and their Allen F-histograms are analysed to extract further topological and directional information. The approach is validated using several sets of real and synthetic data.

Applying Generic Timing Tests for Distributed Multimedia Software Systems

With recent advances in network technologies and computing power, multimedia systems have become a popular means for information delivery. However, testing of these systems is difficult. Due to incomplete control of their runtime and communication environment, precise temporal properties of multimedia systems are nonreproducible. Traditional software testing, which mainly deals with functional correctness, cannot be directly applied to testing temporal properties. Furthermore, time points are hard to be measured exactly, and in this sense are nondeterministic and nonreproducible. To address this problem, we propose a framework for testing the generic temporal properties of media objects in distributed multimedia software systems (DMSS). The timing properties are based on Allen's basic binary temporal relations between two objects, which can be extended to cover multiple objects. We have developed techniques for test case generation, and test result analysis based on a distributed tester architecture. Test templates are used in test case generation to reduce the possibility of human error, and the entire testing procedure can be automated. A prototype system has been built to test a DEC HPAS multimedia presentation system, which is a multimedia system supporting W3C's SMIL standard. Detailed discussions on practical issues illustrated with a number of actual tests are given. Experimental results have shown that our framework is effective in detecting errors in temporal properties. Furthermore, ways to reduce the test effort have been discussed, and guidelines for coming up with criteria for verdict computation based on the real-time requirements of the applications have been suggested.

Temporalisation d'un document XML

This article describes a new tool for marking up the temporal structure of an XML document in which this temporal structure is only implicit either through the order in which temporal elements (event representing elements) appear or through temporal attributes (times, days or durations) or through temporal expressions in the text of the document. This temporal marking up that we call « temporalization » consists in two steps. During the first step the user localizes temporal elements in the source document by XPath expressions and describes the Allen relations between these elements. The result is a temporal sheet. The second step consists in automatically generating the temporalized document from the source document together with its temporal sheet using an XSLT program. This temporalized document can be manipulated by XSLT or XQuery in order to exploit concurrently the logical structure of the source document and the marking up temporal structure.