Structural Semantics and “Cognitive” Semantics
Extracting prototypes from exemplars - What can corpus data tell us about concept representation?
A conceptual space is a geometric structure that represents a number of quality dimensions, which denote basic features by which concepts and objects can be compared, such as weight, color, taste, temperature, pitch, and the three ordinary spatial dimensions. In a conceptual space, points denote objects, and regions denote concepts. The theory of conceptual spaces is a theory about concept learning first proposed by Peter Gärdenfors. It is motivated by notions such as conceptual similarity and prototype theory.
an axiomatic yet reducible set of theorems as the basis of human understanding. they can be used to derive all other concepts – that every possible idea we can think of is (arguably) made up of some combination of these – but reducible in the sense that we can perform introspection on them and break them down.
in order to describe an N-dimensional vector space, we are going to need a basis with N different vectors, and none of those vectors must be entirely constructable as a combination of any of the others. for any vector space, our choice of basis is arbitrary, and serves to describe any location in the entire space.
word2vec does this: given a large-enough corpus of text, builds a vector space that encodes the relationships between words.
In other words, this software mathemagically can determine that removing the idea of [man*]* from [king] leaves some sort of abstract notion of [royalty], such that we can add it to [woman] and get [queen].
thinking about the word-space as created by word2vec is cool and all, it seems to me like we should be able to do better. Word-space is descriptive – which is to say it is generated BY the ideas we currently have – rather than prescriptive, which would ideally allow us to postulate entirely new concepts by just adding constituent vectors together.
a key question in neuroscience is whether its spatial coding principles also provide a universal metric for the organization of non-spatial, conceptual information
How are neural representations of conceptual knowledge organized, such that humans are able to infer never experienced relations or categorize new exemplars?
Deep Meta-Learning: Learning to Learn in the Concept Space
Semantic Communication with Conceptual Spaces
Space, Instance Space, Concept Space and Hypothesis Space
Development of the Concept of Space up to Newton
Abstract - Dec 2012
The widespread prevalence and persistence of misinformation in contemporary societies, such as the false belief that there is a link between childhood vaccinations and autism, is a matter of public concern. For example, the myths surrounding vaccinations, which prompted some parents to withhold immunization from their children, have led to a marked increase in vaccine-preventable disease, as well as unnecessary public expenditure on research and public-information campaigns aimed at rectifying the situation.We first examine the mechanisms by which such misinformation is disseminated in society, both inadvertently and purposely. Misinformation can originate from rumors but also from works of fiction, governments and politicians, and vested interests. Moreover, changes in the media landscape, including the arrival of the Internet, have fundamentally influenced the ways in which information is communicated and misinformation is spread.We next move to misinformation at the level of the individual, and review the cognitive factors that often render misinformation resistant to correction. We consider how people assess the truth of statements and what makes people believe certain things but not others. We look at people’s memory for misinformation and answer the questions of why retractions of misinformation are so ineffective in memory updating and why efforts to retract misinformation can even backfire and, ironically, increase misbelief. Though ideology and personal worldviews can be major obstacles for debiasing, there nonetheless are a number of effective techniques for reducing the impact of misinformation, and we pay special attention to these factors that aid in debiasing.We conclude by providing specific recommendations for the debunking of misinformation. These recommendations pertain to the ways in which corrections should be designed, structured, and applied in order to maximize their impact. Grounded in cognitive psychological theory, these recommendations may help practitioners-including journalists, health professionals, educators, and science communicators-design effective misinformation retractions, educational tools, and public-information campaigns
Misinformation and its correction: continued influence and successful debiasing