8 research outputs found

    Semantic Inference on Heterogeneous E-Marketplace Activities

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    An electronic marketplace (e-marketplace) is a common business information space populated with many entities of different system types. Each of them has its own context of how to process activities. This leads to heterogeneous e-marketplace activities, which are difficult to make interoperable and inferred from one entity to another. This study solves this problem by proposing a concept of separation strategy and implementing it through providing a semantic inference engine with a novel inference algorithm. The solution, called the RuleXPM approach, enables one to semantically infer a next e-marketplace activity across multiple contexts/domains. Experiments show that the cross-context/cross-domain semantic inference is achievable. This paper is an understanding of many aspects related to heterogeneous activity inference

    Fast subsumption checks using anti-links

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    The concept of "anti-link" is defined, and useful equivalence-preserving operations based on anti-links are introduced.These operations eliminate a potentially large number of subsumed paths in a negation normal form formula.Those anti-links that directly indicate the presence of subsumed paths are characterized. The operations have linear time complexity in the size of that part of the formula containing the anti-link. The problem of removing all subsumed paths in an NNF formula is shown to be NP-hard, even though such formulas may be small relative to the size of their path sets. The general problem of determining whether there exists a pair of subsumed paths associated with an arbitrary anti-link is shown to be NP-complete. Additional techniques based on "strictly pure full blocks" are introduced and are also shown to eliminate redundant subsumption checks. The effectiveness of these techniques is examined with respect to some benchmark examples from the literature

    Animation strukturierter Beweise in der universitären Ausbildung [online]

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    Algorithms for computational argumentation in artificial intelligence

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    Argumentation is a vital aspect of intelligent behaviour by humans. It provides the means for comparing information by analysing pros and cons when trying to make a decision. Formalising argumentation in computational environment has become a topic of increasing interest in artificial intelligence research over the last decade. Computational argumentation involves reasoning with uncertainty by making use of logic in order to formalize the presentation of arguments and counterarguments and deal with conflicting information. A common assumption for logic-based argumentation is that an argument is a pair where Φ is a consistent set which is minimal for entailing a claim α. Different logics provide different definitions for consistency and entailment and hence give different options for formalising arguments and counterarguments. The expressivity of classical propositional logic allows for complicated knowledge to be represented but its computational cost is an issue. This thesis is based on monological argumentation using classical propositional logic [12] and aims in developing algorithms that are viable despite the computational cost. The proposed solution adapts well established techniques for automated theorem proving, based on resolution and connection graphs. A connection graph is a graph where each node is a clause and each arc denotes there exist complementary disjuncts between nodes. A connection graph allows for a substantially reduced search space to be used when seeking all the arguments for a claim from a given knowledgebase. In addition, its structure provides information on how its nodes can be linked with each other by resolution, providing this way the basis for applying algorithms which search for arguments by traversing the graph. The correctness of this approach is supported by theoretical results, while experimental evaluation demonstrates the viability of the algorithms developed. In addition, an extension of the theoretical work for propositional logic to first-order logic is introduced

    Hierarchical contextual reasoning

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    Computer supported development of proofs requires user interaction even for theorems that are simple by human standards. In this thesis we define a communication infrastructure as a mediator between the user and the automatic reasoning procedures. It is based on a new uniform meta proof theory for contextual reasoning and encompasses most aspects of communication from the presentation of the proof state, via the supply of relevant contextual information about possible proof continuations, to the support for a hierarchical proof development. The proof theory is uniform for a variety of logics. It exploits proof theoretic annotations in formulas for a contextual reasoning style that is as far as possible intuitive for the user while at the same time still adequate for automatic reasoning procedures. Furthermore, concepts are defined to accomodate both the use and the explicit representation of hierarchies that are inherent in problem solving in general.Das computergestuetzte Beweisen von Theoremen erfordert den Eingriff des menschlichen Benutzers selbst fuer nach menschlichen Maßstaeben einfache Theoreme. Diese Arbeit definiert eine Kommunikationsplattform, die eine synergetische Kooperationsform des Benutzers mit dem Beweisverfahren ermöglicht
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