We use tversky s 1977 contrast model of similarity to design tests of this underlying mechanism. It is assumed that the salience of a set of attributes is given by the sum of the salience of the members of the set. Using tverskys contrast model to investigate how features. How to improve jaccards featurebased similarity measure. For alpha beta 1, the index is equal to the tanimoto coefficient. Sattath and tversky, 1977, and another that demonstrates that feelings of similarity are. For sets x and y the tversky index is a number between 0 and 1 given by. It is shown here that the extent to which mentally retarded children judge planometric figures to be alike is related positively to the number of matching cues.
A new settheoretical approach to similarity is developed in which objects are. Harvard is like yale people will usually exclude such noninformative features as tversky 1977 uses the term referent for the predicate. Semantic web 0 0 1 1 ios press tverskys featurebased. The weakening of the ocp over distance is also accounted for, as intervening material provides interference to the similarity comparison. The observed similarity of object a to object b, s a, b, is a function of their common features, those that are shared by both a and b, and their distinctive features, those that belong to one but not to the other. Similarity, confusability, and the density hypothesis. The experiments with featurebased and hierarchybased seman.
Computes the tversky index between two sequences the tversky index is an asymmetric similarity measure between two sets, one defined the prototype and the other the variant. A central assumption of the model is that the similarity of object a to object b is a function of the features common to a and b a and b, those in a but not in b symbolized ab and those in b but not in a ba. Conceptual hierarchies provide structure for a given domain, organ. Tverskys 1977 contrast model based upon a combination of two methods for measuring common and distinctive features, and two methods for measuring similarity produced statistically significant structural coefficients between the independent latent variables common and distinctive features and the dependent latent variable similarity. Click select file at right to choose the newer file version you want to compare. Indeed, the concept of similarity is ubiquitous in psychological theory. A and b represent the sets of features of a and b respectively, while a b is the set of features distinctive to a, and b a is the set distinctive to b. In a fingerprint the presence or absence of a structural fragment is represented by the presence or absence of a set bit. Members of contrast ing categories such as cars and trucks share few of these features. Features of similarity and categorybased induction evan heit department of psychology university of warwick coventry cv4 7al united kingdom e. The contrast model can account for violations of minimality and asymmetry, as well as certain other phenomena associated with proximity data, such as systematic differences between ratings of similarity and of dissimilarity and changes in similarity with context tversky, 1977.
Whenever this happens, there is a potential for asymmetry. An experimental note on tversky s fea tures of similarity article pdf available in bulletin of the psychonomic society 193. However, most human similarity judgment data violate the metric axioms of these models. An experimental note on tversky s features of simil arity article pdf available in bulletin of the psychonomic society 193. Corter teachers college, columbia university amos tversky stanford university proximity data can be represented by an extended tree, which generalizes traditional trees by including marked segments that correspond to overlapping dusters. Current approaches for the assessment of molecular similarity can generally be divided into descriptorbased and substructurebased methods. Featurebased models of similarity such as the contrast model tversky, 1977 do not seem to be quite successful. In these cases, the features of domain objects play an important role in their description, along with the underlying hierarchy which organises the concepts into more general and more speci. The implications of this proposal for similarity statements are discussed, along with implications for the psychological. However, it is also possible to combine descriptorbased and substructurebased. Tverskys feature matching method, one of the more notable methods for identifying similarities, compares two concepts and expresses similarity as a ratio, calculated between 0 and 1, of their. Two of the empirical features of similarity judgments that tversky reported are particularly striking. This can be readily seen in the kind of task tversky 1977 employed to explore putative violations of symmetry. The tversky index can be seen as a generalization of dices coefficient and tanimoto coefficient aka jaccard index.
Features of similarity amos tversky hebrew university jerusalem, israel the metric and dimensional assumptions that underlie the geometric represen tation of similarity are questioned on both theoretical and empirical grounds. Differentiation views similarity as a quantity and assumes that categories at different levels of abstraction vary in their amount of within and betweencategory similarity. The pictorial and verbal similarity of the set of faces was orthogonal so the different responses were a clue to the underlying representation. Tverskys featurebased similarity and beyond 3 of characteristics from parent classes to descendant classes. Features of similarity amos tversky similarity plays a fundamental role in theories of knowledge and behavior. A modification of amos tverskys 1977 account of similarity is proposed. These times indicated that when participants expected.
The tversky index, named after amos tversky, is an asymmetric similarity measure on sets that compares a variant to a prototype. Tverskystheory is based on a set of qualitative assumptions about the observed similarity ordering, and yields an interval similarity scales, which preserves the observed similarity order. We describe our axiomatic system in details in section 3. The theory then expresses similarity as a linear combination, or a contrast, of the measures of their common and distinctive. If similarity is used to judge likelihood, factors that are known to affect similarity should also affect judgments of likelihood. According to tversky, such changes in perceived similarity are due to changes in the diagnostic value of certain features, which implies that the salience f an attribute can change as. Features of similarity amos tversky hebrew university jerusalem, israel the metric and dimensional assumptions that underlie the geometric representation of similarity are questioned on both theoretical and empirical grounds. Tversky s 1977 contrast model, which defines similarity as a feature contrast task and equates the degree of similarity of two stimuli to a linear combination of their common and distinctive features, explains human similarity judgments much better than. Two compelling views of similarity have arisen from this research.
Tverskys 1977 contrast model and ratio model of stimulus similarity provide a rich range of possibilities for generating featural representations that have been signi. It serves as an organizing principle by which individuals classify objects, form concepts, and make generalizations. The representativeness heuristic suggests that similarity judgments provide a basis for judgments of likelihood. Using the assumption that the similarity between two stimuli is a function of their common and distinctive features, the contrast model mea. If computers band care closer substitutes, then introducing cshould hurt bproportionally more than a. In simple words, a conceptual hierarchy is a simple knowledge structure where the properties of concepts are not taken into account. From classical to complex vector psychological spaces 3 similar to b. Towards a quantum probability theory author proof of. Familiarity, priming and perception in similarity judgments. It is because features important in judgment of objectlevel similarity are not necessarily important in a problemsolving context. Semantic web 0 0 1 1 ios press how to improve jaccards. Compare pdfs, how to compare pdf files adobe acrobat dc.
Attribute similarity measurement based on information content and tversky similarity. According to this hypothesis, options that share more features compete more intensely with each other for the consumers attention. An experimental note on tversky s features of similarity. Tversky has related degree of judged similarity between among objects to the degree of overlap of matching features. Gleitman, henry gleitman, carol miller, ruth ostrin.
Our method was deliberately designed to find a point of contact between the two traditions of research in heuristics the early tradition exemplified by kahneman and tverskys work, and the later tradition exemplified by the work of gigerenzer and goldstein 1996. Tverskys contrast model 1977 systematizes this feature approach. Tverskys 1977 contrast model, which defines similarity as a feature contrast task and equates the degree of similarity of two stimuli to a linear combination of their common and distinctive features, explains human similarity judgments much better than. Moreover, tversky reported a socalled diagnosticity effect,wherethesamesimilarityjudgment could change greatly, depending on which other stimuli were present in a broadly relevant context set. Consequently, recognition, learning, and judgment presuppose an ability to categorize stimuli and classify situations by similarity.