Artificial intelligence and scientific method
Artificial intelligence and scientific method
Scientific knowledge discovery using inductive logic programming
Communications of the ACM
Inductive logic programming: issues, results and the challenge of learning language in logic
Artificial Intelligence - Special issue on applications of artificial intelligence
Semantic integration of heterogeneous information sources
Data & Knowledge Engineering - Special issue on heterogeneous information resources need semantic access
Logical fusion rules for merging structured news reports
Data & Knowledge Engineering
Arbitration (or How to Merge Knowledge Bases)
IEEE Transactions on Knowledge and Data Engineering
Information Fusion in Logic: A Brief Overview
ECSQARU/FAPR '97 Proceedings of the First International Joint Conference on Qualitative and Quantitative Practical Reasoning
Measuring inconsistency in knowledge via quasi-classical models
Eighteenth national conference on Artificial intelligence
Source Integration in Data Warehousing
DEXA '98 Proceedings of the 9th International Workshop on Database and Expert Systems Applications
Man bites dog: looking for interesting inconsistencies in structured news reports
Data & Knowledge Engineering
Reo: a channel-based coordination model for component composition
Mathematical Structures in Computer Science
Quantifying information and contradiction in propositional logic through test actions
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Evaluating significance of inconsistencies
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Approaches to measuring inconsistent information
Inconsistency Tolerance
How to act on inconsistent news: ignore, resolve, or reject
Data & Knowledge Engineering
Obtaining the consensus and inconsistency among a set of assertions on a qualitative attribute
Expert Systems with Applications: An International Journal
The centroid or consensus of a set of objects with qualitative attributes
Expert Systems with Applications: An International Journal
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Much useful new information (e.g. information in news reports) is often that which is surprising or unexpected. In other words, we harbour many expectations about the world, and when any of these expectations are violated (i.e. made inconsistent) by new information, we have a strong indicator that the information is interesting for us. An expectation can be compared with an integrity constraint. Both an expectation and integrity constraint can be represented by an implicational formula in classical logic, and every time we get new information, we compare it with the implicational formula. However, with an integrity constraint, we are primarily seeking information that is consistent with the implicational formula. In constrast, with an expectation, we are primarily seeking information that is inconsistent with the implicational formula. In this paper, we present a framework for representing and analysing expectations. We consider for an application language the syntax of expectations, the accuracy and validity of expectations, and we explore relationships between these issues. We also consider representing and reasoning with expectations as part of an application in merging information.