Stream Reasoning: A Survey and Further Research Directions

Data streams occur widely in various real world applications. The research on streaming data mainly focuses on the data management, query evaluation and optimization on these data, however the work on reasoning procedures for streaming knowledge bases on both the assertional and terminological levels is very limited. Typically reasoning services on large knowledge bases are very expensive, and need to be applied continuously when the data is received as a stream. Hence new techniques for optimizing this continuous process is needed for developing efficient reasoners on streaming data. In this paper, we survey the related research on reasoning that can be applied to this setting, summarize existing approaches according to a set of parameters, and point to further research directions in this area.

[1]  Larry Wos,et al.  What Is Automated Reasoning? , 1987, J. Autom. Reason..

[2]  Lukasz Golab,et al.  Issues in data stream management , 2003, SGMD.

[3]  Volker Haarslev,et al.  Exploiting Pseudo Models for TBox and ABox Reasoning in Expressive Description Logics , 2001, IJCAR.

[4]  Michael Miller,et al.  Memory, Reason, and Time: the Step-logic Approach , 1991 .

[5]  Judea Pearl,et al.  On the Logic of Iterated Belief Revision , 1994, Artif. Intell..

[6]  Donald Perlis,et al.  Active Logics: A Unified Formal Approach to Episodic Reasoning , 1999 .

[7]  Yanjing Wang,et al.  Propositional Dynamic Logic as a Logic of Belief Revision , 2008, WoLLIC.

[8]  Letizia Tanca,et al.  Logic Programming and Databases , 1990, Surveys in Computer Science.

[9]  Chitta Baral,et al.  Logic Programming and Knowledge Representation , 1994, J. Log. Program..

[10]  Alan Bundy,et al.  Towards Ontology Evolution in Physics , 2008, WoLLIC.

[11]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[12]  Bernardo Cuenca Grau,et al.  History Matters: Incremental Ontology Reasoning Using Modules , 2007, ISWC/ASWC.

[13]  E. Allen Emerson,et al.  Temporal and Modal Logic , 1991, Handbook of Theoretical Computer Science, Volume B: Formal Models and Sematics.

[14]  Armin Wolf,et al.  Constraint Programming Architectures: Review and a New Proposal , 2007, J. Univers. Comput. Sci..

[15]  Robert Paige,et al.  Symbolic Finite Differencing - Part I , 1990, ESOP.

[16]  Michael Kifer,et al.  Concurrency and Communication in Transaction Logic , 1996, JICSLP.

[17]  J. Van Leeuwen,et al.  Handbook of theoretical computer science - Part A: Algorithms and complexity; Part B: Formal models and semantics , 1990 .

[18]  Bijan Parsia,et al.  Description Logic Reasoning for Dynamic ABoxes , 2006, Description Logics.

[19]  Patrick Doherty,et al.  TAL: Temporal Action Logics Language Specification and Tutorial , 1998, Electron. Trans. Artif. Intell..

[20]  Dov M. Gabbay,et al.  Handbook of Philosophical Logic , 2002 .

[21]  Jerzy Tiuryn,et al.  Dynamic logic , 2001, SIGA.

[22]  Henning Christiansen,et al.  On Simplification of Database Integrity Constraints , 2006, Fundam. Informaticae.

[23]  Donald Perlis,et al.  Step-logic: reasoning situated in time , 1988 .

[24]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[25]  Kevin Shaw,et al.  Stream Data Management , 2005, Advances in Database Systems.

[26]  Daniele Braga,et al.  Research chapters in the area of stream reasoning , 2009 .

[27]  Luc De Raedt,et al.  Inductive Logic Programming: Theory and Methods , 1994, J. Log. Program..

[28]  R. Watson,et al.  Data Management , 1980, Bone Marrow Transplantation.