The purpose of this paper is to present two kinds of analogical representational change, both occurring early in the analogy-making process, and then, using these two kinds of change, to present a model unifying one sort of analogy-making and categorization. The proposed unification rests on three key claims: (1) a certain type of rapid representational abstraction is crucial to making the relevant analogies (this is the first kind of representational change; a computer model is presented that demonstrates this kind of (...) abstraction), (2) rapid abstractions are induced by retrieval across large psychological distances, and (3) both categorizations and analogies supply understandings of perceptual input via construing, which is a proposed type of categorization (this is the second kind of representational change). It is construing that finalizes the unification. (shrink)

Recent metaphor research has revealed that metaphor comprehension involves both categorization and comparison processes. This finding has triggered the following central question: Which property determines the choice between these two processes for metaphor comprehension? Three competing views have been proposed to answer this question: the conventionality view (Bowdle & Gentner, 2005), aptness view (Glucksberg & Haught, 2006b), and interpretive diversity view (Utsumi, 2007); these views, respectively, argue that vehicle conventionality, metaphor aptness, and interpretive diversity determine the choice between the categorization (...) and comparison processes. This article attempts to answer the question regarding which views are plausible by using cognitive modeling and computer simulation based on a semantic space model. In the simulation experiment, categorization and comparison processes are modeled in a semantic space constructed by latent semantic analysis. These two models receive word vectors for the constituent words of a metaphor and compute a vector for the metaphorical meaning. The resulting vectors can be evaluated according to the degree to which they mimic the human interpretation of the same metaphor; the maximum likelihood estimation determines which of the two models better explains the human interpretation. The result of the model selection is then predicted by three metaphor properties (i.e., vehicle conventionality, aptness, and interpretive diversity) to test the three views. The simulation experiment for Japanese metaphors demonstrates that both interpretive diversity and vehicle conventionality affect the choice between the two processes. On the other hand, it is found that metaphor aptness does not affect this choice. This result can be treated as computational evidence supporting the interpretive diversity and conventionality views. (shrink)

Human cognition is striking in its brilliance and its adaptability. How do we get that way? How do we move from the nearly helpless state of infants to the cognitive proficiency that characterizes adults? In this paper I argue, first, that analogical ability is the key factor in our prodigious capacity, and, second, that possession of a symbol system is crucial to the full expression of analogical ability.

This research addresses the kinds of matching elements that determine analogical relatedness and literal similarity. Despite theoretical agreement on the importance of relational match, the empirical evidence is neither systematic nor definitive. In 3 studies, participants performed online evaluations of relatedness of sentence pairs that varied in either the object or relational match. Results show a consistent focus on relational matches as the main determinant of analogical acceptance. In addition, analogy does not require strict overall identity of relational concepts. Semantically (...) overlapping but nonsynonymous relations were commonly accepted, but required more processing time. Finally, performance in a similarity rating task partly paralleled analogical acceptance; however, relatively more weight was given to object matches. Implications for psychological theories of analogy and similarity are addressed. (shrink)

This paper summarizes three lines of research that are motivated by the practical problem of helping users find information from external data sources, most notably computers. The application areas include information retrieval, text categorization, and question answering. A common theme in these applications is that practical information access problems can be solved by analyzing the statistical properties of words in large volumes of real world texts. The same statistical properties constrain human performance, thus we believe that solutions to practical information (...) access problems can shed light on human knowledge representation and reasoning. (shrink)