Category Learning as Schema Induction

نویسنده

  • John P. Clapper
چکیده

Categories are essential for practically all aspects of human cognition, and an enormous amount of research has been devoted to understanding how they are learned and represented in memory (see, e.g., Murphy, 2002; Smith & Medin, 1981). In this chapter, I describe a program of research on category learning that Gordon Bower and I began a number of years ago, when I was a graduate student in his laboratory at Stanford University, and which I have continued to extend and develop over the succeeding years. This research began by investigating how people use category knowledge (schemas) to guide attention and organize memory, and later focused on the basic mechanisms by which such categories are discovered and learned. Although category learning has been a traditional focus of research within cognitive psychology, we have taken a rather non-traditional approach in our own investigations of this area. My primary goal in this chapter (besides paying tribute to Gordon) will be to convince readers of the value of this non-traditional approach. It is important to note that most category learning research has been carried out within a standard conceptual framework or paradigm that describes what categories are, what they are for, and the kinds of situations in which they are normally acquired. Within this paradigm, category learning typically is regarded as a form of

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Feature- vs. Relation-Defined Categories: Probab(alistic)ly Not the Same

Relational categories underlie many uniquely human cognitive processes including analogy, problem solving, and scientific discovery. Despite their ubiquity and importance, the field of category learning has focused almost exclusively on categories based on features. Classification of featurebased categories is typically modeled by calculating similarity to stored representations, an approach th...

متن کامل

Tracking the emergence of memories: A category-learning paradigm to explore schema-driven recognition.

Previous research has shown that prior knowledge structures or schemas affect recognition memory. However, since the acquisition of schemas occurs over prolonged periods of time, few paradigms allow the direct manipulation of schema acquisition to study their effect on memory performance. Recently, a number of parallelisms in recognition memory between studies involving schemas and studies invo...

متن کامل

Making Probabilistic Relational Categories Learnable

Theories of relational concept acquisition (e.g., schema induction) based on structured intersection discovery predict that relational concepts with a probabilistic (i.e., family resemblance) structure ought to be extremely difficult to learn. We report four experiments testing this prediction by investigating conditions hypothesized to facilitate the learning of such categories. Experiment 1 s...

متن کامل

Event Schema Induction With A Probabilistic Entity-driven Model

category—that is, a schema can represent the narrative commonalities son (1977) as a generalization of recurring event knowledge. 4.2 Schema Induction Procedure. In this section Probabilistic Entity-Driven Model. In EMNLP (pp. portal we built a event type classification model for news articles using lexical Unfortunately the performance of automatic event schema generation and (2) N. Chambers. ...

متن کامل

Abstraction and Relational learning

ion and relational learning Charles Kemp & Alan Jern Department of Psychology Carnegie Mellon University {ckemp,ajern}@cmu.edu Abstract Most models of categorization learn categories defined by characteristic features but some categories are described more naturally in terms of relations. We present a generative model that helps to explain how relational categories are learned and used. Our mod...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007