Applying GAC on conjunctions of constraints can lead to more powerful pruning [1]. We show that there exists a simple heuristic for deciding which constraints might be useful to conjoin. The result is a useful automatic way of improving a CSP model for GAC solving.

Selective Tuning (ST) [1] presents a framework for modeling attention and in this paper we show how it performs in visual search tasks. Two types of tasks are presented, a motion search task and an object search task. Both tasks are successfully tested with different feature and conjunction visual searches.

We present an eecient algorithm to detect if the conjunction of two nonlocal predicates is possibly true in a distributed computation. For ooine detection of such global predicates, our algorithm is signiicantly more eecient than the previous algorithms

The recognition of named entities is now a welldeveloped area, with a range of symbolic and machine learning techniques that deliver high accuracy identification and categorisation of a variety of entity types. However, there are still some named entity phenomena that present problems for existing techniques; in particular, relatively little work has explored the disambiguation of conjunctions ...

Named entity recognition consists of identifying ‘mentions’ — strings in a text that correspond to named entities — and then classifying each such mention as corresponding to a specific type of named entity, with typical categories being Company, Person and Location. The full range of named entity categories to be identified is usually application dependent. Introduced for the first time as a s...

In this paper we present a functional representation of human expert reasoning throughout its statements when assessing the condition of a given object. The human expert statements are represented as conjunctions of elementary propositions. We demonstrate that the conjunctions of elementary propositions can be represented as qualitative additions of qualitative functions in the Q-algebra (Q, ≈,...

We show that adding role conjunctions to the Description Logics (DLs) SHI and SHOIF causes a jump in the computational complexity of the standard reasoning tasks from ExpTime-complete to 2ExpTime-complete and from NExpTime-complete to N2ExpTime-hard respectively. We further show that this increase is due to a subtle interaction between inverse roles, role hierarchies, and role transitivity in t...