Most existing inductive learning systems form concept descriptions in propositional languages from vectors of basic features. However, many concepts are characterized by the relationships of individual examples to general domain knowledge. We describe a system that constructs relational terms e~ciently to augment the description language of standard inductive systems. In our approach, examples ...

Ontologies, as knowledge engineering tools, allow information to be modelled in ways resembling to those used by the human brain, and may be very useful in the context of personal information management (PIM) and Task Information Management (TIM). This work proposes the use of ontologies as a long-term knowledge store for PIM-related information, and the use of spreading activation over ontolog...

A mining method for egocentric and polycentric queries in multi-dimensional networks is proposed. The method allows fast search for objects in sufficient proximity of other object(s) where the proximity is defined in terms of multiple relationships between objects. The method uses spreading activation technique. Other potential uses of spreading activation technique are also outlined and, in pa...

When listening to spoken language, bilinguals access words in both of their languages at the same time; this co-activation is often driven by phonological input mapping to candidates in multiple languages during online comprehension. Here, we examined whether cross-linguistic activation could occur covertly when the input does not overtly cue words in the non-target language. When asked in Engl...

We describe here the theory behind the language comprehension program Wimp. Wimp understands by first, finding paths between the open-class words in a sentence using a marker passing, or spreading-activation, technique. This paper is primarily concerned with the “meaning” (or interpretation) of such paths. We argue that they are best thought of as backbones of proofs that the terms (words) at, ...

In this paper we present a neurally plausible model of robot reaching inspired by human infant reaching that is based on embodied artificial intelligence, which emphasizes the importance of the sensory-motor interaction of an agent and the world. This model encompasses both learning sensorymotor correlations through motor babbling and also arm motion planning using spreading activation. This mo...

Two recent findings constitute a serious challenge for all existing models of interval timing. First, Hass and Hermann (2012) have shown that only variance-based processes will lead to the scalar growth of error that is characteristic of human time judgments. Secondly, a major meta-review of over one hundred studies of participants’ judgments of interval duration (Block et al., 2010) reveals a ...

To produce good utterances from non-trivial inputs a natural language generator should consider many words in parallel, which raises the question of how to handle syntax in a parallel generator. If a generator is incremental and centered on the task of word choice, then the role of syntax is merely to help evaluate the appropriateness of words. One way to do this is to represent syntactic knowl...

Question Answering (QA) systems try to find precise answers to natural language questions. QA extraction result is often an amount of text candidate answers which requires some validation and ranking criteria. This paper presents an automatic answer appreciation technique where extracted candidate answers are represented in a question dedicated associative knowledge base, a semantic network. A ...

Most word sense disambiguation (WSD) methods require large quantities of manually annotated training data and/or do not exploit fully the semantic relations of thesauri. We propose a new unsupervised WSD algorithm, which is based on generating Spreading Activation Networks (SANs) from the senses of a thesaurus and the relations between them. A new method of assigning weights to the networks’ li...