Abstract
The metric and dimensional assumptions that underlie the geometric representation of similarity are questioned on both theoretical and empirical grounds. A new set-theoretical approach to similarity is developed in which objects are represented as collections of features, and similarity is described as a feature-matching process. Specifically, a set of qualitative assumptions is shown to imply the contrast model, which expresses the similarity between objects as a linear combination of the measures of their common and distinctive features. Several predictions of the contrast model are tested in studies of similarity with both semantic and perceptual stimuli. The model is used to uncover, analyze, and explain a variety of empirical phenomena such as the role of common and distinctive features, the relations between judgments of similarity and difference, the presence of asymmetric similarities, and the effects of context on judgments of similarity. The contrast model generalizes standard representations of similarity data in terms of clusters and trees. It is also used to analyze the relations of prototypicality and family resemblance
Keywords
Affiliated Institutions
Related Publications
Studies of Similarity
Any event in the history of the organism is, in a sense, unique. Consequently, recognition, learning, and judgment presuppose an ability to categorize stimuli and classify situa...
Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics
In this paper we describe two new objective automatic evaluation methods for machine translation. The first method is based on longest common subsequence between a candidate tra...
Additive Similarity Trees
Similarity data can be represented by additive trees. In this model, objects are represented by the external nodes of a tree, and the dissimilarity between objects is the length...
Representations of perceptions of risks.
Abstract : The perceptions of risks (e.g., diseases, accidents, natural hazards) is investigated using a multi-task, multi-model approach. We studied the proximities among 18 ri...
BERTScore: Evaluating Text Generation with BERT
We propose BERTScore, an automatic evaluation metric for text generation. Analogously to common metrics, BERTScore computes a similarity score for each token in the candidate se...
Publication Info
- Year
- 1977
- Type
- article
- Volume
- 84
- Issue
- 4
- Pages
- 327-352
- Citations
- 7176
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1037/0033-295x.84.4.327