ACLP: Abductive Constraint Logic Programming

Kakas, Antonis C.; Michael, Aimilios; Mourlas, Constantinos

doi:10.1016/s0743-1066(99)00075-8

Cited by 85 publications

(61 citation statements)

References 24 publications

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“…In contrast, known metainterpreter based implementations of abduction incur heavy computational overhead (for instance, [18,20] has the overhead of alternating abductive steps with resolution steps, the latter also simulated by metainterpretation). An important advantage over other known abduction systems is that the full collection of Prolog's built-in facilities (logical as well as impure) are available, including all available libraries and constraint solvers.…”

Section: Conclusion and Related Workmentioning

confidence: 99%

HYPROLOG: A New Logic Programming Language with Assumptions and Abduction

Christiansen

Dahl

2005

Logic Programming

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Abstract. We present HYPROLOG, a novel integration of Prolog with assumptions and abduction which is implemented in and partly borrows syntax from Constraint Handling Rules (CHR) for integrity constraints. Assumptions are a mechanism inspired by linear logic and taken over from Assumption Grammars. The language shows a novel flexibility in the interaction between the different paradigms, including all additional built-in predicates and constraints solvers that may be available. Assumptions and abduction are especially useful for language processing, and we can show how HYPROLOG works seamlessly together with the grammar notation provided by the underlying Prolog system. An operational semantics is given which complies with standard declarative semantics for the "pure" sublanguages, while for the full HYPROLOG language, it must be taken as definition. The implementation is straightforward and seems to provide for abduction, the most efficient of known implementations; the price, however, is a limited use of negations. The main difference wrt. previous implementations of abduction is that we avoid any level of metainterpretation by having Prolog execute the deductive steps directly and by treating abducibles (and assumptions as well) as CHR constraints.

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Section: Conclusion and Related Workmentioning

confidence: 99%

HYPROLOG: A New Logic Programming Language with Assumptions and Abduction

Christiansen

Dahl

2005

Logic Programming

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“…The mediation is performed by a procedure, which infers from the query and the knowledge base a reformulation of the initial query in the terms of the component sources. The procedure itself is inspired by the abductive logic programming framework [27]. One of the main advantages of the abductive logic-programming framework is the simplicity in which it can be used to formally combine and to implement features of query processing, semantic query optimization, and constraint programming.…”

Section: The Context Interchange (Coin) Approachmentioning

confidence: 99%

Financial Information Mediation: A Case Study of Standards Integration for Electronic Bill Presentment and Payment Using the COIN Mediation Technology

Jayasena

Bressan

Madnick

2005

Technologies for E-Services

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-Each player in the financial industry, each bank, stock exchange, government agency, or insurance company operates its own financial information system or systems. 1 By its very nature, financial information, like the money that it represents, changes hands. Therefore the interoperation of financial information systems is the cornerstone of the financial services they support. E-services frameworks such as web services are an unprecedented opportunity for the flexible interoperation of financial systems. Naturally the critical economic role and the complexity of financial information led to the development of various standards. Yet standards alone are not the panacea: different groups of players use different standards or different interpretations of the same standard.We believe that the solution lies in the convergence of flexible E-services such as web-services and semantically rich meta-data as promised by the semantic Web; then a mediation architecture can be used for the documentation, identification, and resolution of semantic conflicts arising from the interoperation of heterogeneous financial services.In this paper we illustrate the nature of the problem in the Electronic Bill Presentment and Payment (EBPP) industry and the viability of the solution we propose. We describe and analyze the integration of services using four different formats: the IFX, OFX and SWIFT standards, and an example proprietary format. To accomplish this integration we use the COntext INterchange (COIN) framework. The COIN architecture leverages a model of sources and receivers' contexts in reference to a rich domain model or ontology for the description and resolution of semantic heterogeneity.

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“…No global or exhaustive pair-wise definition of the conflict resolution procedures is needed. The mediator is implemented using abductive constraint logic programming (ACLP) [12], which not only rewrites queries to reconcile semantic differences, but also performs semantic query optimization. …”

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confidence: 99%

Addressing the Challenges of Aggregational and Temporal Ontological Heterogeneity

Zhu

Madnick

2005

SSRN Journal

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-In this paper, we first identify semantic heterogeneities that, when not resolved, often cause serious data quality problems. We discuss the especially challenging problems of temporal and aggregational ontological heterogeneity, which concerns how complex entities and their relationships are aggregated and reinterpreted over time. Then we illustrate how the COntext INterchange (COIN) technology can be used to capture data semantics and reconcile semantic heterogeneities in a scalable manner, thereby improving data quality.Index Terms -Data Semantics, Semantic Heterogeneity, Aggregation, Temporal, Ontology, Context. I. INTRODUCTIONN our research, we have discovered that many problems arise due to confusion regarding data semantics. To illustrate how complex this can become, consider Fig. 1. This data summarizes the P/E ratio for DaimlerChrysler obtained from four different financial information sources -all obtained on the same day within minutes of each other. Note that the four sources gave radically different values for P/E ratio. are all correct! The issue is, what do you really mean by "P/E ratio" 1 . The answer lies in the multiple interpretations and uses of the term "P/E ratio" in financial circles. The earnings are for the entire year in some sources but in one source are only for the last quarter. Even when earnings are for a full year, are they:-the last 12 months? -the last calendar year? -the last fiscal year? or -the last three historical quarters and the estimated current quarter -a popular usage? Such information, which we call context, is often not explicitly captured in a form that can be used by the query answering system to reconcile semantic differences in data from different sources. Serious consequences can result from not being aware of the differences in contexts and data semantics. Consider a financial trader that used DBC to get P/E ratio information yesterday and got 19.19. Today he used Bloomberg and got 5.57 (low P/E's usually indicate good bargains) -thinking that something wonderful had happened he might decide to buy many shares of DaimlerChrysler today. In fact, nothing had actually changed, except for changing the source that he used. It would be natural for this trader (after possibly losing a significant amount of money due to this decision) to feel that he had encountered a data quality problem.We would argue that what appeared to be a data quality problem is actually a data misinterpretation problem. The data source did not have any "error," the data that it provided was exactly the data that it intended to provideit just did not have the meaning that the receiver expected. In other words, the issue is not what is right or wrong, it is about how data in one context can be used in a different context.Before going any further, it should be noted that if all sources and all receivers of data always had the exact same meanings, this problem would not occur. This is a desirable goal -one frequently sought through 1 Some of these sites even provide a glossary which give...

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ACLP: Abductive Constraint Logic Programming

Cited by 85 publications

References 24 publications

HYPROLOG: A New Logic Programming Language with Assumptions and Abduction

HYPROLOG: A New Logic Programming Language with Assumptions and Abduction

Financial Information Mediation: A Case Study of Standards Integration for Electronic Bill Presentment and Payment Using the COIN Mediation Technology

Addressing the Challenges of Aggregational and Temporal Ontological Heterogeneity

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