Representing and reasoning about incomplete and indefinite qualitative temporal information is an essential part of many artificial intelligence tasks. An interval-based framework and a point-based framework have been proposed for representing such temporal information. In this paper, we address two fundamental reasoning tasks that arise in applications of these frameworks: Given possibly indefinite and incomplete knowledge of the relationships between some intervals or points, (i) find a scenario that is consistent with the information provided, and (ii) find the feasible relations between all pairs of intervals or points. For the point-based framework and a restricted version of the intervalbased framework, we give computationally efficient procedures for finding a consistent scenario and for finding the feasible relations. Our algorithms are marked improvements over the previously known algorithms. In particular, we develop an O(n 2 ) time algorithm for finding one co...

Temporal events are regarded here as intervals on a time line. This paper deals with problems in reasoning about such intervals when the precise topological relationship between them is unknown or only partially specified. This work unifies notions of interval algebras in artificial intelligence with those of interval orders and interval graphs in combinatorics. The satisfiability, minimal labeling, all solutions and all realizations problems are considered for temporal (interval) data. Several versions are investigated by restricting the possible interval relationships yielding different complexity results. We show that even when the temporal data comprises of subsets of relations based on intersection and precedence only, the satisfiability question is NP-complete. On the positive side, we give efficient algorithms for several restrictions of the problem. In the process, the interval graph sandwich problem is introduced, and is shown to be NP-complete. This problem is als...

. Temporal Constraint Satisfaction is an information technology useful for representing and answering queries about the times of events and the temporal relations between them. Information is represented as a Constraint Satisfaction Problem (CSP) where variables denote event times and constraints represent the possible temporal relations between them. The main tasks are two: (i) deciding consistency, and (ii) answering queries about scenarios that satisfy all constraints. This paper overviews results on several classes of Temporal CSPs: qualitative interval, qualitative point, metric point, and some of their combinations. Research has progressed along three lines: (i) identifying tractable subclasses, (ii) developing exact search algorithms, and (iii) developing polynomial-time approximation algorithms. Most available techniques are based on two principles: (i) enforcing local consistency (e.g. path-consistency), and (ii) enhancing naive backtracking search. Keywords: Temporal Constra...

this paper, we survey a wide range of research in temporal representation and reasoning, without committing ourselves to the point of view of any speci c application

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This paper organizes, for every n 1, the topologic forms of the possible relations between the Cartesian coordinates of two points of the Euclidean space of dimension n over the field of real numbers. Working out n- dimensional point algebra on the pattern of point algebra and cardinal relation algebra, it introduces the concept of convexity just as the one of preconvexity. Adapting the propagation techniques designed to solve point networks or cardinal relation networks, it shows that these concepts are preserved by the fundamental operations of composition, conversion and intersection. Finally, it proposes a set of n- dimensional point networks, the strongly preconvex n-dimensional point networks, whose consistency can be decided in polynomial time by means of the path-consistency algorithm or the weak path-consistency algorithm. Keywords: Spatial reasoning, Constraint satisfaction problems, Tractability. 1 Introduction Artificial intelligence and computer sci...

This paper organizes the topologic forms of the possible relations between generalized intervals. Working out generalized interval algebra on the pattern of point algebra and interval algebra, it introduces the concept of Horn representability just as the one of convexity. It gives the class of Horn representable relations a simple characterization based on the concept of strong preconvexity. Adapting the propagation techniques designed to solve the networks of constraints between points or between intervals, it shows that the issue of consistency of a Horn representable generalized interval network can be solved in polynomial time by means of the weak path-consistency algorithm, a new incomplete algorithm for computing a minimal set of temporal constraints. 1 INTRODUCTION It is hard to overemphasize the importance for computer science and artificial intelligence of the development of reasoning systems that are concerned with temporal information. The thing is that the natur...

Information Retrieval is in a nascent stage to provide any type of information queried by naïve user. Question Answering System is one such successful area of Information retrieval. Legal Documents (case law, statute or transactional document) are increasing day by day with the new applications (Mobile transactions, Medical Diagnosis reports, law cases etc.) in the world. Documentation of various Business and Human Resource (HR) applications involve Legal documents. Analysis and temporal reasoning of such documents is a demanding area of research. In this paper we build a novel model for timed event extraction and temporal reasoning in legal text documents. This paper mainly works on “how one can do further reasoning with the extracted temporal information”. Exploring temporal information in legal text documents is an important task to support legal practitioner lawyer, in order to determine temporal based context decisions. Legal documents are available in different natural languages; hence it uses NLP System for pre-processing steps, Temporal constraint structure for temporal expressions, associated tagger, Post-Processor with a knowledge-based sub system helps in discovering implicit information. The resultant information resolves temporal expressions and deals with issues such as granularity, vagueness, and a reasoning mechanism which models the temporal constraint satisfaction network.