There is interest in artificial intelligence for principled techniques to analyze inconsistent information. This stems from the recognition that the dichotomy between consistent and inconsistent sets of formulae that comes from classical logics is not sufficient for describing inconsistent information. We review some existing proposals and make new proposals for measures of inconsistency and me...

Inconsistencies are part of any manually annotated corpus. Automatically finding these inconsistencies and correcting them (even manually) can increase the quality of the data. Past research has focused mainly on detecting inconsistency in syntactic annotation. This work explores new approaches to detecting inconsistency in semantic annotation. Two ranking methods are presented in this paper: a...

In this paper, we study estimator inconsistency in Vision-aided Inertial Navigation Systems (VINS) from a standpoint of system observability. We postulate that a leading cause of inconsistency is the gain of spurious information along unobservable directions, resulting in smaller uncertainties, larger estimation errors, and possibly even divergence. We develop an Observability-Constrained VINS ...

This article presents a historical review of how inconsistency in assessment center ratings has been regarded among AC researchers and practitioners, then compares these perspectives to views of inconsistency found in personality psychology. Based on this review, the authors argue for a return to the study of consistency as an individual difference, rather than as simple measurement error. They...

Software design inconsistency can be hard to trace manually. Computer assistance in detecting and resolving inconsistency issues can help improve the quality of sophisticated software designs. This paper describes a rule-based (or production system) solution to the aforementioned problem. We characterize classes of inconsistency that occur in software design. We define a production system langu...

Context: Inconsistency detection and resolution is critical for context-aware applications to ensure their normal execution. Contexts, which refer to pieces of environmental information used by applications, are checked against consistency constraints for potential errors. However, not all detected inconsistencies are caused by real context problems. Instead, they might be triggered by improper...

An inconsistency measure can be used to compare the quality of different datasets and to quantify the cost of data cleaning. In traditional relational databases, inconsistency is defined in terms of constraints that use comparison operators between attributes. Inconsistency measures for traditional databases cannot be applied to spatial datasets because spatial objects are complex and the const...

To verify fixed-time constraints in Grid workflow systems, consistency and inconsistency conditions have been defined in conventional verification work. However, with a view of the run-time uncertainty of activity completion duration, we argue that, although the conventional consistency condition is feasible, the conventional inconsistency condition is too restrictive and covers several differe...

Though there is much work on how inconsistency in databases should be managed, there is good reason to believe that end users will want to bring their domain expertise and needs to bear in how to deal with inconsistencies. In this paper, we propose the concept of inconsistency management policies (IMPs). We show that IMPs are rich enough to specify many types of inconsistency management methods...

The management of inconsistency between multiple viewpoints has become a central problem in the development of large software systems. In this paper we argue that the same problem occurs in the development of the semantic web, and indeed that this is the central issue in semantic integration. A common approach is to attempt to remove inconsistencies, if necessary by discarding problematic infor...