Allen's Temporal Relations Research Articles

Representing and querying now-relative relational medical data

Temporal information plays a crucial role in medicine. Patients' clinical records are intrinsically temporal. Thus, in Medical Informatics there is an increasing need to store, support and query temporal data (particularly in relational databases), in order, for instance, to supplement decision-support systems. In this paper, we show that current approaches to relational data have remarkable limitations in the treatment of "now-relative" data (i.e., data holding true at the current time). This can severely compromise their applicability in general, and specifically in the medical context, where "now-relative" data are essential to assess the current status of the patients. We propose a theoretically grounded and application-independent relational approach to cope with now-relative data (which can be paired, e.g., with different decision support systems) overcoming such limitations. We propose a new temporal relational representation, which is the first relational model coping with the temporal indeterminacy intrinsic in now-relative data. We also propose new temporal algebraic operators to query them, supporting the distinction between possible and necessary time, and Allen's temporal relations between data. We exemplify the impact of our approach, and study the theoretical and computational properties of the new representation and algebra.

Fuzz-TIME: an intelligent system for managing fuzzy temporal information

PurposeTime modeling is a crucial feature in many application domains. However, temporal information often is not crisp, but is subjective and fuzzy. The purpose of this paper is to address the issue related to the modeling and handling of imperfection inherent to both temporal relations and intervals.Design/methodology/approachOn the one hand, fuzzy extensions of Allen temporal relations are investigated and, on the other hand, extended temporal relations to define the positions of two fuzzy time intervals are introduced. Then, a database system, called Fuzzy Temporal Information Management and Exploitation (Fuzz-TIME), is developed for the purpose of processing fuzzy temporal queries.FindingsTo evaluate the proposal, the authors have implemented a Fuzz-TIME system and created a fuzzy historical database for the querying purpose. Some demonstrative scenarios from history domain are proposed and discussed.Research limitations/implicationsThe authors have conducted some experiments on archaeological data to show the effectiveness of the Fuzz-TIME system. However, thorough experiments on large-scale databases are highly desirable to show the behavior of the tool with respect to the performance and time execution criteria.Practical implicationsThe tool developed (Fuzz-TIME) can have many practical applications where time information has to be dealt with. In particular, in several real-world applications like history, medicine, criminal and financial domains, where time is often perceived or expressed in an imprecise/fuzzy manner.Social implicationsThe social implications of this work can be expected, more particularly, in two domains: in the museum to manage, exploit and analysis the piece of information related to archives and historic data; and in the hospitals/medical organizations to deal with time information inherent to data about patients and diseases.Originality/valueThis paper presents the design and characterization of a novel and intelligent database system to process and manage the imperfection inherent to both temporal relations and intervals.

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.

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.

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 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.

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.

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.

Modeling spatial relationships within a fuzzy framework

In this article, we present a model for defining and representing binary topological and directional relationships between 2-dimensional objects that is used to provide a basis for fuzzy querying capabilities. The definition of the relationships is based on an extension of Allen's temporal relations (Allen, 1983) to the spatial domain. This is done by allowing each of Allen's 13 relations to represent the interaction of 2-dimensional objects in terms of an x and y relationship component. The resulting set of relationships is then used for defining topological and directional relationship terminology. A data structure called an abstract spatial graph (ASG) is defined for the binary relationships that maintains all necessary information regarding topology and direction. Abstract spatial graphs provide the basis for processing of fuzzy topological and directional queries. © 1998 John Wiley & Sons, Inc.

A qualitative temporal information system for process control

A general system is presented in this paper which supports the expression of relative temporal knowledge in process control and management. This system allows knowledge of Allen's temporal relations over time elements, which may be both intervals and points. The objectives and characteristics of two major temporal attributes, i.e. ‘transaction time’ and ‘valid time’, are described. A graphical representation for the temporal network is presented, and inference over the network may be made by means of a consistency checker in terms of the graphical representation. An illustrative example of the system as applied to process control and management is provided.