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Maintaining knowledge about temporal intervals
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article Free Access Share on Maintaining knowledge about temporal intervals Author: James F. Allen Univ. of Rochester, Rochester, NY Univ. of Rochester, Rochester, NYView Profile Authors Info & Claims Communications of the ACMVolume 26Issue 11Nov. 1983 pp 832–843https://doi.org/10.1145/182.358434Online:01 November 1983Publication History 5,173citation11,531DownloadsMetricsTotal Citations5,173Total Downloads11,531Last 12 Months644Last 6 weeks101 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
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“Allen-relation selection on the operator output preserves the bitemporal-tuple type by closure of Allen's thirteen interval relations and the twelve-relation transitivity table that omits equality [3].”
From TOKI: A Bitemporal Operator Algebra for Contradiction Resolution in LLM-Agent Persistent Memory (2026) · cites this paper as [3]
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“Closure under Allen-relation selection follows from the transitivity table over the twelve non-equality relations [3].”
From TOKI: A Bitemporal Operator Algebra for Contradiction Resolution in LLM-Agent Persistent Memory (2026) · cites this paper as [3]
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Research works printed but not linked: 18
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Multimedia documents with elastic time
Kim, M. Y., & Song, J. (1995) · MULTIMEDIA '95 · doi:10.1145/217279.215261 · Cited by 94
“Most notably, James Allen's interval algebra [1] has received much attention for its simplicity.”
BackgroundMethodPPRS: Production skills and their relation to product, process, and resource
Pfrommer, J., Schleipen, M., & Beyerer, J. (2013) · 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA) · doi:10.1109/etfa.2013.6648114 · Cited by 93
“task A must follow directly after task B) could be expressed by the temporal relations defined by Allen [18].”
BackgroundInfluentialTowards a New Generation of Widgets for Supporting Software Plasticity: The "Comet"
Calvary, G., Coutaz, J., Dâassi, O., Balme, L., & Demeure, A. (2004) · EHCI/DS-VIS · doi:10.1007/11431879_21 · Cited by 93
“Allen’s relations [2] provide an interesting framework for comparing these two presentations according to spatio-temporal criteria.”
BackgroundAn Approach to a Content-Based Retrieval of Multimedia Data
Amato, G., Mainetto, G., & Savino, P. (1998) · Multimedia tools and applications · doi:10.1023/a:1009618102731 · Cited by 93
“Multimedia Tools and Applications, 7, 5-7 (1998) .”
Processing Disjunctions in Temporal Constraint Networks
Schwalb, E., & Dechter, R. (1997) · Artificial Intelligence · doi:10.1016/s0004-3702(97)00009-x · Cited by 93
“Deciding consistency of TCSPs is known to be intractable.”
BackgroundMethodOntology for Spatio-temporal Databases
Frank, A. (2003) · CHOROCHRONOS Approach, The · doi:10.1007/978-3-540-45081-8_2 · Cited by 93
Sim, I., Tu, S. W., Carini, S., Lehmann, H. P., Pollock, B. H., Mor Peleg, B., & Wittkowski, K. M. (2013) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2013.11.002 · Cited by 70
“, 3 weeks after end of chemotherapy), or a time-interval constraint where the time interval associated with the constrained event is compared with another time interval using Allen’s temporal-interval comparison operators [66].”
Analyzing theme, space, and time: an ontology-based approach
Perry, M., Hakimpour, F., & Sheth, A. (2006) · ACM SIGSPATIAL International Workshop on Advances in Geographic Information Systems · doi:10.1145/1183471.1183496 · Cited by 92
“The specific relations we are interested in are those of Allen’s interval algebra [3] and Ladkin’s extension of it over unions of convex time intervals [13] and also temporal distance (e.”
BackgroundINDU: An Interval and Duration Network
Pujari, A. K., Kumari, G., & Sattar, A. (1999) · Australian Joint Conference on Artificial Intelligence · doi:10.1007/3-540-46695-9_25 · Cited by 92
“Allen [ 1 ] proposed an algebraic framework named Interval Algebra (lA), for qualitative reasoning with time intervals where the binary relationship be tween a pair of intervals is represented by a subset of 13 atomic relations.”
BackgroundChen, Z.-Z., Grigni, M., & Papadimitriou, C. (1999) · JACM · doi:10.1145/506147.506148 · Cited by 92
“…[Grigni et al. 1995] No decision algorithm or .nite axiomatization is known, although the problem becomes both .nitely axiomatizable and polynomial-time decidable in any number of dimensions other than two [Allen 1983; Renz 1998], for some reasonable vocabularies of topological relations.”
BackgroundA Temporal Query System for Protocol-Directed Decision Support
Das, A. K., & Musen, M. (1994) · Methods of Information in Medicine · doi:10.1055/s-0038-1635036 · Cited by 92
“Previous research-Oers [12, 13, 15, 18] have added to this set temporal comparisons for pairs of timepoints (AT, BEFORE, AFTER) and for pairs of intervals (BEFORE, UNTIL, LEADS, STARTS, EQUALS, DURING, SPANS, FINISHES, FROM, and AFTER); the latter set is based on Allen's interval-based logic [19].”
MethodRCS: a reference model architecture for intelligent control
Albus, J. (1992) · Computer · doi:10.1109/2.144396 · Cited by 92
Coupled temporal scoping of relational facts
Talukdar, P. P., Wijaya, D., & Mitchell, T. (2012) · Proceedings of the fifth ACM international conference on Web search and data mining · doi:10.1145/2124295.2124307 · Cited by 46
“As in TIE, and instead of Allen-style intervals [1], CoTS uses a real-valued point-based temporal representation.”
MethodA new approach to cyclic ordering of 2D orientations using ternary relation algebras
Isli, A., & Cohn, A. (2000) · Artificial Intelligence · doi:10.1016/s0004-3702(00)00044-8 · Cited by 91
“These methods have been borrowed from qualitative temporal reasoning à la Allen [1], and make use of a composition table.”
BackgroundMethodInfluentialModeling of moving objects in a video database
Li, J. Z., ̈ozsu, M. T., & Szafron, D. (1997) · Proceedings of IEEE International Conference on Multimedia Computing and Systems · doi:10.1109/mmcs.1997.609625 · Cited by 91
Intelligent Information Integration for the Semantic Web
Visser, U. (2004) · Lecture Notes in Computer Science · doi:10.1007/b100348 · Cited by 90
Qualitative representation of spatial knowledge in two-dimensional space
Dimitris Papadias, C., & Sellis, T. (1994) · The VLDB Journal · doi:10.1007/bf01231605 · Cited by 130
“These 13 relations correspond to the relations between time intervals introduced by Allen (1983), and applied to 1-”
MethodPropositional Interval Neighborhood Temporal Logics
Goranko, V., Montanari, A., & Sciavicco, G. (2003) · Journal of universal computer science (Online) · doi:10.3217/jucs-009-09-1137 · Cited by 90
“They feature two modalities which correspond to Allen’s meet and met by relations [ All83 ], intuitively capturing a right neighboring interval and a left neighboring interval.”
MethodContext-dependent Semantic Parsing for Time Expressions
Lee, K., Artzi, Y., Dodge, J., & Zettlemoyer, L. (2014) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.3115/v1/p14-1135 · Cited by 80
“This line of work builds on ideas from TimeBank (Puste-jovsky et al., 2003) and a number of different formal models for temporal reasoning, e.g. Allen (1983), Moens and Steedman (1988).”
MethodRanacher, P., & Tzavella, K. (2014) · Cartography and Geographic Information Science · doi:10.1080/15230406.2014.890071 · Cited by 89
“Allen proposes a qualitative temporal logic with a complete set of 13 distinct relations between two temporal intervals (Allen 1983).”
BackgroundTrajectory databases: Data models, uncertainty and complete query languages
Kuijpers, B., & Othman, W. (2007) · Journal of computer and system sciences (Print) · doi:10.1016/j.jcss.2009.10.002 · Cited by 89
“In the terminology of Allen’s interval calculus [1,2], A and B are called co-temporal if πt(A) = πt(B) (we denote this by A =t B).”
BackgroundRobust Mining of Time Intervals with Semi-interval Partial Order Patterns
Moerchen, F., & Fradkin, D. (2010) · SDM · doi:10.1137/1.9781611972801.28 · Cited by 89
“When dealing with time interval patterns, the formulation of patterns is much more intricate, because the number of possible binary relations rises from three relations for time points (before, equals, after) to Allen’s 13 interval relations [3].”
BackgroundMethodInfluentialCombining Spatial and Temporal Logics: Expressiveness vs. Complexity
Gabelaia, D., Kontchakov, R., Kurucz, Á., Wolter, F., & Zakharyaschev, M. (2011) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1537 · Cited by 88
“There exists a wide spectrum of temporal logics (see, e.g., Allen, 1983; Clarke & Emerson, 1981; Manna & Pnueli, 1992; Gabbay, Hodkinson, & Reynolds, 1994; van Benthem, 1995).”
BackgroundOn the consistency of cardinal direction constraints
Skiadopoulos, S., & Koubarakis, M. (2005) · Artificial Intelligence · doi:10.1016/j.artint.2004.10.010 · Cited by 88
“For example, Nebel and Bürckert [30] consider this problem for the 13 interval relations of Allen [2] and van Beek [46] for the relations of point algebra.”
BackgroundContent-based video retrieval by integrating spatio-temporal and stochastic recognition of events
Petkovic, M., & Jonker, W. (2001) · Proceedings IEEE Workshop on Detection and Recognition of Events in Video · doi:10.1109/event.2001.938869 · Cited by 88
“For the definitions of these relations, as well as interval temporal relations see [22, 23].”
BackgroundInterpreting Observations of Physical Systems
Forbus, K. D. (1987) · IEEE Transactions on Systems, Man and Cybernetics · doi:10.1109/tsmc.1987.4309052 · Cited by 88
“We also assume that the temporal relationships described in [1] may be applied to intervals.”
MethodTILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs
Xiong, S., Yang, Y., Fekri, F., & Kerce, J. C. (2024) · International Conference on Learning Representations · doi:10.48550/arxiv.2402.12309 · Cited by 87
“For TR between two intervals I and I ′ , there are 13 different relations in total given by Allen’s interval algebra (Allen (1983)).”
BackgroundEfficient Algorithms for Qualitative Reasoning about Time
Gerevini, A., & Schubert, L. K. (1995) · Artificial Intelligence · doi:10.1016/0004-3702(94)00016-t · Cited by 87
“Further research in this direction might be aimed at providing approximate consistency-checking algorithms for disjunctive temporal information that operate more e ciently and accurately than current approximate techniques based on constraint propagation [2, 39].”
BackgroundMethodTemporal Specialization and Generalization
Jensen, C. S., & Snodgrass, R. (1994) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/69.334885 · Cited by 87
“Allen has demonstrated that there exist a total of thirteen possible relationships between two intervals [5].”
BackgroundSelvakumar, K., Karuppiah, M., Sairamesh, L., Islam, S., Hassan, M. M., Fortino, G., & Choo, K. (2019) · Information Sciences · doi:10.1016/j.ins.2019.05.040 · Cited by 86
Mining Temporal Patterns in Time Interval-Based Data
Chen, Y.-C., Peng, W.-C., & Lee, S.-Y. (2015) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2015.2454515 · Cited by 86
“Zakour et al. [35] introduce a sliding window approach to extract frequent interval sequences from discrete temporal sequences.”
BackgroundA temporal constraint structure for extracting temporal information from clinical narrative
Zhou, L., Melton, G., Parsons, S., & Hripcsak, G. (2006) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2005.07.002 · Cited by 86
“In essence , an STP supports metric relations among points, time points anchored in absolute time, and primitive Allen interval relationships [34]; these structures are also efficient and can be solved by polynomial time algorithms [31] [35].”
BackgroundDatabase models for infinite and indefinite temporal information
Koubarakis, M. (1994) · Information Systems · doi:10.1016/0306-4379(94)90008-6 · Cited by 86
“For example, the interval corresponding to the tenth day of January, 1990 is represented by [1990; 1; 10].”
Temporal modules: an approach toward federated temporal databases
Wang, X., Jajodia, S., & Subrahmanian, V. (1993) · Information Sciences · doi:10.1145/170035.170074 · Cited by 86
Managing concurrency in temporal planning using planner-scheduler interaction
Coles, A., Fox, M., Halsey, K., Long, D., & Smith, A. (2009) · Artificial Intelligence · doi:10.1016/j.artint.2008.08.003 · Cited by 86
“All of Allen’s interval constraints [21] can be captured using temporal constraints of the form described here, using time points representing the ends of the intervals.”
BackgroundMethodRelations between fuzzy time intervals
Ohlbach, H. (2004) · Proceedings. 11th International Symposium on Temporal Representation and Reasoning, 2004. TIME 2004. · doi:10.1109/time.2004.1314418 · Cited by 85
“As an example for an application, consider a database with, say, a cinema timetable, and you query the timetable “give me all performances ending before midnight”.”
BackgroundMethodA generalized temporal role-based access control model
Joshi, J. B. D., Bertino, E., Latif, U., & Ghafoor, A. (2005) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2005.1 · Cited by 85
“Although, overlapping intervals along the line of temporal work by Allen with regards to various entities of RBAC [2] have not been discussed, the semantics of overlapping intervals are elaborated for temporal hierarchies.”
BackgroundSketchMapia: Qualitative Representations for the Alignment of Sketch and Metric Maps
Schwering, A., Wang, J., Chipofya, M. C., Jan, S., Li, R. S., & Broelemann, K. (2014) · Spatial Cognition and Computation · doi:10.1080/13875868.2014.917378 · Cited by 79
“We apply a coarse version of the Interval Algebra (IA) by Allen (1983) to represent ordering information of landmarks and street segments along a specific route in the street network.”
Domain Ontology for Construction Knowledge
El-Diraby, T. (2013) · doi:10.1061/(asce)co.1943-7862.0000646 · Cited by 84
“Allen shows 13 different types of inter-interval relationships (Allen 1983).”
BackgroundQuerying ATSQL databases with temporal logic
Chomicki, J., Toman, D., & Böhlen, M. H. (2001) · ACM Transactions on Database Systems · doi:10.1145/383891.383892 · Cited by 84
“We have listed all possible temporal relationships [Allen 1983] between the truth periods of two formulas A and B.”
CHIMP: a framework for supporting distributed multimedia document authoring and presentation
Candan, K. S., Prabhakaran, B., & Subrahmanian, V. (1997) · MULTIMEDIA '96 · doi:10.1145/244130.244234 · Cited by 84
“J.F. Allen ( 1984) Towards a General Theo~ of Time and Action, Artificial Intelligence, 23, pp. 123-154.”
BackgroundKnowledge-based acquisition of causal relationships in text
Kaplan, R., & Berry-Rogghe, G. (1991) · Knowledge Acquistion · doi:10.1016/1042-8143(91)90009-c · Cited by 84
Quality assessment of OpenStreetMap data using trajectory mining
Basiri, A., Jackson, M., Amirian, P., Pourabdollah, A., Sester, M., Winstanley, A., Moore, T., & Zhang, L. (2016) · Geo-Spatial Information Science · doi:10.1080/10095020.2016.1151213 · Cited by 83
“Example predicates include Follows, Coincides, Parallels, and Mutates (Allen 1983; Freksa 1992; Hornsby and Egenhofer 1998).”
BackgroundCores of Countably Categorical Structures
Bodirsky, M. (2006) · Log. Methods Comput. Sci. · doi:10.2168/lmcs-3(1:2)2007 · Cited by 83
“• Allen’s interval algebra, and all its fragments [4, 23,27,31] • Problems in phylogenetic analysis [20,32] • Tree description constraints in computational linguistics [10,11,15] • Computational problems in the theory of relation algebras [16,24,30] • All CSPs in monotone monadic SNP without inequality [9, 17]”
BackgroundSpatial graph grammars for graphical user interfaces
Kong, J., Zhang, K., & Zeng, X. (2006) · TCHI · doi:10.1145/1165734.1165739 · Cited by 83
“Detecting the semantic structure underlying a Web page is a technical challenge which is addressed by the application of the SGG. Buyukkokten et al. [2001] divided a Web page into several semantic textual units with the help of HTML tags.”
BackgroundMethodSpatial object modeling in fuzzy topological spaces: with applications to land cover change
Tang, X.-M. (2004) · doi:10.3990/1.9789061642206 · Cited by 83
“Allen (1983) identified 13 topological relations between two temporal intervals. The breakthrough on topological relations between spatial objects was made by the well-known 4-intersection and 9-intersection approaches proposed by Egenhofer and Franzosa (1991). A lot of research has been done based on this aspect (Ege…”
InfluentialLARS: A Logic-based framework for Analytic Reasoning over Streams
Beck, H., Dao-Tran, M., & Eiter, T. (2018) · Artificial Intelligence · doi:10.1016/j.artint.2018.04.003 · Cited by 79
A Qualitative Trajectory Calculus and the Composition of Its Relations
van de Weghe, N., Kuijpers, B., Bogaert, P., & de Maeyer, P. (2005) · International Conference on GeoSpatial Semantics · doi:10.1007/11586180_5 · Cited by 82
“We discuss the reasoning power of QTCC and apply the important reasoning technique of composition tables, originating from the domain of temporal reasoning [1].”
BackgroundMethodEfficiently supporting temporal granularities
Dyreson, C., Evans, W. S., Lin, H., & Snodgrass, R. (2000) · doi:10.1109/69.868908 · Cited by 82
“All comparisons, including OVERLAPS , are expressed as formulas involving the Before relation (the relation on integers) and logical connectives [2].”
MethodPrinciples of Knowledge Representation and Reasoning
Nebel, B., & Helmert, M. (2008) · Elsevier eBooks · doi:10.1016/c2013-0-08308-9 · Cited by 82
Resolving Commitments among Autonomous Agents
Mallya, A. U., Yolum, P., & Singh, M. P. (2003) · Workshop on Agent Communication Languages · doi:10.1007/978-3-540-24608-4_10 · Cited by 81
“Allen [8] defines 13 possible temporal relationships between any two given time intervals.”
BackgroundOntological analysis of whole-part relationships in OO-models
Opdahl, A., Henderson-Sellers, B., & Barbier, F. (2001) · Information and Software Technology · doi:10.1016/s0950-5849(00)00175-0 · Cited by 81
Computational Properties of Qualitative Spatial Reasoning: First Results
Nebel, B. (1995) · Deutsche Jahrestagung für Künstliche Intelligenz · doi:10.1007/3-540-60343-3_40 · Cited by 81
“While the computationalproperties of qualitativetemporal reasoning [1] have been analyzed quite thoroughly [20, 19, 12], for qualitative spatial reasoning the situation appears to be completely di(cid:11)erent.”
BackgroundMedia streams: representing video for retrieval and repurposing
Davis, M. (1994) · MULTIMEDIA '94 · doi:10.1145/192593.197412 · Cited by 81
Fuzzy Sets and Possibility Theory in Approximate and Plausible Reasoning
Bouchon-Meunier, B., Dubois, D., Godo, L., & Prade, H. (1999) · doi:10.1007/978-1-4615-5243-7_2 · Cited by 81
Artikis, A., Skarlatidis, A., Portet, F., & Παλιούρας, Γ. (2012) · The Knowledge Engineering Review · doi:10.1017/s0269888912000264 · Cited by 81
“(2007) and Álvarez et al. (2010). Most of the approaches adopting this technique rely on an extended version of the Apriori algorithm (Mannila et al., 1997) to discover frequent sequences of events—the temporal distance between the events of a frequent sequence is computed using lower and higher frequency thresholds.…”
BackgroundMethodInfluentialAllen, J. F., & Schubert, L. K. (1991) · doi:10.21236/ada247447 · Cited by 80
Self-citationElson, D. K. (2012) · doi:10.7916/d8cr61fj · Cited by 63
Zhang, Y., Zhang, Y., Swears, E., Larios, N., Wang, Z., & Ji, Q. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.33 · Cited by 66
“An interval algebra network (IAN) [39] can be used to represent the temporal relationships among a set of events in an activity, where the nodes represent events and the directed links represent the temporal relationships among the events.”
BackgroundMethodInfluentialPreferred and Alternative Mental Models in Spatial Reasoning
Rauh, R., Hagen, C., Knauff, M., Kuss, T., Schlieder, C., & Strube, G. (2005) · Spatial Cogn. Comput. · doi:10.1080/13875868.2005.9683805 · Cited by 79
“…reasoning has developed several sets of spatial relations (e.g., Cohn & Hazarika, 2001), and we chose the set of thirteen interval relations by Allen (1983) for the following reasons: The calculus is well investigated from a formal point of view (Ligozat, 1990) and has some interesting…”
BackgroundInfluentialRelation Algebras and their Application in Temporal and Spatial Reasoning
Düntsch, I. (2005) · Artificial Intelligence Review · doi:10.1007/s10462-004-5899-8 · Cited by 79
“3 The interval algebra The most widely investigated relation algebra in the temporal context was given by Allen [1].”
BackgroundMethodInfluentialRepresenting Temporal Knowledge for Case-Based Prediction
Jære, M. D., Aamodt, A., & Skalle, P. (2002) · European Conference on Case-Based Reasoning · doi:10.1007/3-540-46119-1_14 · Cited by 79
“Allen’s approach is simple, transparent and easy to implement.”
BackgroundInfluentialMERGING SEPARATELY GENERATED PLANS WITH RESTRICTED INTERACTIONS
Yang, Q., Nau, D. S., & Hendler, J. (1992) · International Conference on Climate Informatics · doi:10.1111/j.1467-8640.1992.tb00383.x · Cited by 79
“The additional information requires time points or intervals in action de(cid:12)nitions [Allen, 1983], or other such temporal representations.”
M-HTP: A system for monitoring heart transplant patients
Larizza, C., Moglia, A., & Stefanelli, M. (1992) · Artif. Intell. Medicine · doi:10.1016/0933-3657(92)90049-u · Cited by 79
Temporal Reasoning via Audio Question Answering
Fayek, H. M., & Johnson, J. (2020) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2020.3010650 · Cited by 57
“Systems that interact with the world must therefore be adept at temporal reasoning [8]–[10].”
BackgroundFusing uncertain knowledge and evidence for maritime situational awareness via Markov Logic Networks
Snidaro, L., Visentini, I., & Bryan, K. (2015) · Information Fusion · doi:10.1016/j.inffus.2013.03.004 · Cited by 78
“To describe complex events, which often imply a temporal sequence of facts, we employ Allen’s temporal logic [41].”
MethodSexTant: Visualizing Time-Evolving Linked Geospatial Data
Nikolaou, C., Dogani, K., Bereta, K., Garbis, G., Karpathiotakis, M., Kyzirakos, K., & Koubarakis, M. (2013) · International Workshop on the Semantic Web · doi:10.2139/ssrn.3199201 · Cited by 78
“ing to the thirteen temporal relations of Allen’s interval algebra [32], the temporal aggregate functions, or the extension functions for constructing new temporal elements.”
BackgroundProbabilistic Event Calculus for Event Recognition
Skarlatidis, A., Paliouras, G., Artikis, A., & Vouros, G. (2012) · ACM Transactions on Computational Logic · doi:10.1145/2699916 · Cited by 78
The MurMur project: Modeling and querying multi-representation spatio-temporal databases
Parent, C., Spaccapietra, S., & Zimányi, E. (2006) · Information Systems · doi:10.1016/j.is.2005.01.004 · Cited by 78
“, topological in time) relationships (before, equal, meets, overlaps, during, starts, finishes) [11].”
Oatley, G., Ewart, B. W., & Zeleznikow, J. (2006) · Artificial Intelligence and Law · doi:10.1007/s10506-006-9023-z · Cited by 65
From symbol to form: a framework for conceptual design
Gorti, S. R., & Sriram, R. D. (1996) · Comput. Aided Des. · doi:10.1016/0010-4485(95)00088-7 · Cited by 78
Query processing algorithms for temporal intersection joins
Gunadhi, H., & Segev, A. (1991) · [1991] Proceedings. Seventh International Conference on Data Engineering · doi:10.1109/icde.1991.131481 · Cited by 78
ETALIS: Rule-Based Reasoning in Event Processing
Anicic, D., Fodor, P., Rudolph, S., Stühmer, R., Stojanović, N., & Studer, R. (2011) · doi:10.1007/978-3-642-19724-6_5 · Cited by 78
“It is worth noting that the defined pattern language captures the set of all possible 13 relations on two temporal intervals as defined in [ 4 ].”
BackgroundA generalisation approach to temporal data models and their implementations
Steiner, A. (1998) · doi:10.3929/ethz-a-001923958 · Cited by 78
Rule-based composite event queries: the language XChangeEQ and its semantics
Bry, F., & Eckert, M. (2007) · Knowledge and Information Systems · doi:10.1007/s10115-010-0334-8 · Cited by 77
“– Allen’s 13 relations for time intervals [5] such as before, after, during, contains, overlaps.”
BackgroundA Cognitive Substrate for Achieving Human-Level Intelligence
Cassimatis, N. L. (2006) · The AI Magazine · doi:10.1609/aimag.v27i2.1879 · Cited by 77
Bloch, I., & Ralescu, A. (2003) · Pattern Recognition · doi:10.1016/s0031-3203(02)00263-7 · Cited by 77
“Most non-fuzzy approaches are based on a set of basic relations, based on Allen’s interval relations [2], for instance Ref.”
MethodSQLST: A Spatio-Temporal Data Model and Query Language
Chen, C. X., & Zaniolo, C. (2000) · International Conference on Conceptual Modeling · doi:10.1007/3-540-45393-8_8 · Cited by 77
“As has been discussed in [7,15], an important requirement of all temporal languages is to support Allen’s interval operators such as overlap, precede, contain, equal, meet, and intersect [ 1 ].”
BackgroundProgress in computational methods for representing geographical concepts
Egenhofer, M., Glasgow, J., Günther, O., Herring, J., & Peuquet, D. (1999) · International Journal of Geographical Information Science · doi:10.1080/136588199241012 · Cited by 77
“Temporal databases (Snodgrass 1992) and temporal reasoning (Allen 1983) have a long tradition in computer science, but the integration with spatial databases (http://www.dbnet.ece.ntua.gr/~choros/) and spatial reasoning (Egenhofer and Golledge 1998) is only in its infancy.”
BackgroundTsotsos, J. K. (1985) · International Conference on Climate Informatics · doi:10.1111/j.1467-8640.1985.tb00056.x · Cited by 77
An ontological framework for knowledge modeling and decision support in cyber-physical systems
Petnga, L., & Austin, M. A. (2016) · Advanced Engineering Informatics · doi:10.1016/j.aei.2015.12.003 · Cited by 80
“This will result in a safe crossing of the intersection as shown by The mechanics behind this reasoning process is rendered possible by the critical role of temporal semantics and Allen’s temporal intervals [55] as we demonstrated in [44].”
Intelligent fuzzy rule-based approach with outlier detection for secured routing in WSN
Thangaramya, K., Kulothungan, K., Gandhi, S., Selvi, M., Kumar, S. V. N. S., & Arputharaj, K. (2020) · Soft Computing - A Fusion of Foundations, Methodologies and Applications · doi:10.1007/s00500-020-04955-z · Cited by 76
“For this purpose, Allen (1983) proposed an interval algebra that analyses the dependencies between time intervals and provides operators for performing temporal reasoning through explanation-based learning and predictive analysis (Russell and Norvig 1994).”
RetractedFern, A., Givan, R. L., & Siskind, J. M. (2002) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1050 · Cited by 59
“These include standard firstorder logic, Allen’s interval calculus (Allen 1983), and various temporal logics (Clarke, Emerson, & Sistla 1983; Allen & Ferguson 1994; Bacchus & Kabanza 2000).”
InfluentialWebPersona: a lifelike presentation agent for the World-Wide Web
André, E., Rist, T., & Müller, J. M. (1998) · Knowledge-Based Systems · doi:10.1016/s0950-7051(98)00057-4 · Cited by 73
Equivalence Constraint Satisfaction Problems
Bodirsky, M., & Wrona, M. (2012) · Annual Conference for Computer Science Logic · doi:10.4230/lipics.csl.2012.122 · Cited by 76
Spatiotemporal Reasoning for Smart Homes
Gottfried, B., Guesgen, H., & Hübner, S. (2006) · Designing Smart Homes · doi:10.1007/11788485_2 · Cited by 76
“Having their seeds in Allen’s approach [ 5 ], in the last fifteen years a number of calculi have been proposed from which many still rely on the same reasoning mechanisms as Allen’s algorithm (see section 3.1).”
BackgroundInfluentialtOWL: A Temporal Web Ontology Language
Milea, V., Frasincar, F., & Kaymak, U. (2012) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2011.2162582 · Cited by 75
“As known from [30], all 13 Allen’s interval relations may be translated in terms of equivalent relations on the intervals’ endpoints.”
BackgroundMethodExploiting time in electronic health record correlations
Hripcsak, G. M., Albers, D. J., & Perotte, R. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000463 · Cited by 70
“Sacchi and coauthors 4 described a method for inferring relationships based on encoding the time series as a sequence of trends and discovering the relationships among them in terms of Allen ’ s intervals, 5 quantifying the evidence by con fi dence and support.”
MethodMonitoring Activities of Daily Living (ADLs) of Elderly Based on 3D Key Human Postures
Zouba, N., Boulay, B., Brémond, F., & Thonnat, M. (2009) · International Cognitive Vision Workshop · doi:10.1007/978-3-540-92781-5_4 · Cited by 75
“person, equipment, zones of interest), ”components” corresponding to the sub-events composing the event, ”forbidden components” corresponding to the events which should not occur during the main event, ”constraints” are conditions between the physical objects and/or the components (including symbolic, logical, spatial…”
BackgroundTemporal reasoning about fuzzy intervals
Schockaert, S., & Cock, M. D. (2008) · Artificial Intelligence · doi:10.1016/j.artint.2008.01.001 · Cited by 75
“An atomic linear constraint over a set of variables X is an expression of the form a1x1+a2x2+· · ·+anxn b where a1, a2, . . . , an, b ∈ R, x1, x2, . . . , xn ∈ X, and is <,≤, >,≥, = or =.”
BackgroundThe algebra IAfuz: a framework for qualitative fuzzy temporal reasoning
Badaloni, S., & Giacomin, M. (2006) · Artificial Intelligence · doi:10.1016/j.artint.2006.04.001 · Cited by 75
“As it has been shown in Section 3, FOSOL is a generalization to IA fuz of the classical problem of finding a solution of an IA-network: accordingly, classical backtracking algorithm with incremental path-consistency [1,40] can be generalized to a Branch & Bound algorithm, which searches through the possible singleton…”
InfluentialSharpening the Undecidability of Interval Temporal Logic
Lodaya, K. (2000) · Asian Computing Science Conference · doi:10.1007/3-540-44464-5_21 · Cited by 75
“Interval temporal logics (ITLs) were introduced in the philosophy of time (see [Ben95] for a survey) but have proved useful in artificial intelligence and computer science [ All83 , HMM83, HS91, ZHR91].”
A Framework for the Combination and Characterization of Output Modalities
Vernier, F., & Nigay, L. (2000) · International Workshop on Design, Specification, and Verification of Interactive Systems · doi:10.1007/3-540-44675-3_3 · Cited by 75
“These schemas use the five Allen relationships [1] to provide a means of combining multiple modalities into a composite modality.”
MethodTemporal Synchronization Models for Multimedia Data
Bertino, E., & Ferrari, E. (1998) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/69.706060 · Cited by 75
“chronization constraints are the ones based on Allen’s binary relations between intervals [ 2 ], or on the relationships between instants defined in [62].”
BackgroundContent oriented visual interface using video icons for visual database systems
Tonomura, Y., & Abe, S. (1989) · [Proceedings] 1989 IEEE Workshop on Visual Languages · doi:10.1109/wvl.1989.77044 · Cited by 75
Default reasoning in semantic networks: A formalization of recognition and inheritance
Shastri, L. (1989) · Artificial Intelligence · doi:10.1016/0004-3702(89)90016-7 · Cited by 57
Big Macs and Eigenfactor scores: Don't let correlation coefficients fool you
Eschenfelder, K. R. (2010) · doi:10.1002/asi.v61:9 · Cited by 74
An ontology-based hierarchical semantic modeling approach to clinical pathway workflows
Ye, Y., Jiang, Z.-B., Diao, X.-D., Yang, D., & Du, G. (2009) · Comput. Biol. Medicine · doi:10.1016/j.compbiomed.2009.05.005 · Cited by 74
“They can correspond to Allen's relations between two intervals [35] if the execution of an intervention is viewed as an interval.”
BackgroundA Modeling Framework for Product Development Process Considering its Characteristics
Jun, H., & Suh, H. (2008) · IEEE transactions on engineering management · doi:10.1109/tem.2007.912808 · Cited by 74
“3) Time Dependency: In the time perspective, the relation can be classified into “α before β,” “α meets β,” “α equals β,” “α overlaps β,” “α during β,” “α starts β,” and “α finishes β.” These are seven relations among Allen’s [58] 13 relations, a well-known classification of time-dependent relations between two activi…”
BackgroundParadigms for Spatial and Spatio-Temporal Data Mining
Roddick, J., & Lees, B. (2001) · doi:10.4324/9780203468029_chapter_2 · Cited by 74
Metadata
- Authors
- Allen, J. F.
- Affiliations
- University of Rochester (US)
- Corresponding author
- Allen, James F.
- ORCID
- Allen, James F.
- Venue
- Communications of the ACM
- Published
- 1983-11
- Volume
- 26
- Issue
- 11
- Pages
- 832-843
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2161484642
- Cited by
- 7,593
- References
- 0
- Citations by year
- 2026: 79 · 2025: 88 · 2024: 133 · 2023: 126 · 2022: 115 · 2021: 159 · 2020: 194 · 2019: 175 · 2018: 212 · 2017: 246 · 2016: 291 · 2015: 267 · 2014: 279 · 2013: 326 · 2012: 322
- FWCI
- 27.16
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Communications of the ACM (publishedVersion)
- Funders
- National Science Foundation (8210564)
- Office of Naval Research (N00014)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Physical Sciences › Computer Science › Artificial Intelligence › Constraint Satisfaction and Optimization
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Keywords
- temporal reasoning, time intervals, interval arithmetic, knowledge representation, temporal logic, Allen's interval algebra
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