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of Clustering in the Recall of Randomly Arranged Associates · W. A. Bousfield et al. The Journal of Psychology. Volume 36, – Issue 1. Bousfield, W.A. BousfieldThe occurrence of clustering in the recall of randomly arranged associates. Journal of General Psychology, 49 (), pp. Psychol., 49 (), pp. Google Scholar. Bousfield et al., W.A. Bousfield, B.H. Cohen, G.A. WhitmarshAssociative clustering in the recall of words.

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Associative clustering during recall. The semantic clustering score must be computed independently for each studied list. Suppose the simulated participant has just studied a list of n words.

However, this method becomes impractical as the number of study item grows, since the number of pairwise comparisons grows with the square of the number of study items.

Abstract The order in bousfiepd participants choose to bouefield words from a studied list of randomly selected words provides insights into how memories of the words are represented, organized, and retrieved.

We expect that these biases are related to the form of the semantic similarity distributions derived from each measure see Fig. Another measure of semantic similarity, termed the Google similarity distance Calibrasi and Vitanyi,uses the Google search engine to compute the number of web pages containing both word x and yrelative to the total number of pages containing each word individually; a similar metric relies on Wikipedia links to measure the similarities between topics Milne and Witten, We ran two batches of simulations.

The primacy, recency, and temporal clustering effects may be measured objectively by examining the relative probabilities of recalling or transitioning between items that appeared at each serial position on a studied list.

Each simulated participant encounters many word lists, and we simulate a sequence of recalls after each studied list. Weobtain a single semantic clustering score for each simulated participant by averaging the semantic clustering scores across all lists that the participant encountered.

Behavior Research Methods, Instruments and Computers. Rather, we simply found the semantic clustering score bousfielr a convenient means of quantifying semantic clustering.

See other articles in PMC that cite the published article. There is some evidence that similarities in the neural patterns evoked by thinking about a given pair of words predict the tendencies of participants to successively recall the words, given that both appeared on the studied lists Manning, We chose the two semantic similarity metrics as representative examples from the broader range of metrics discussed in the introduction.


This indicates that different semantic similarity metrics used in analyses of semantic clustering may introduce slight biases. Acquisition, storage, and retrieval in digital and biological brains. In such cases, one might use simulations analogous to those we present here to gain insights into the range of clustering scores one might expect under various models e.

However, the techniques developed here are equally applicable to arbitrary choices of n and k. Journal of General Psychology. Serial effects in recall of unorganized and sequentially organized verbal material. We order the words in the pool by their semantic similarity according to g p to i 1. Analysis Our simulations are intended to estimate the maximum expected magnitude of semantic clustering effects in free recall.

The free recall paradigm has participants study lists of items — typically words — and subsequently recall the studied items in the order they come to mind. We select the word with the highest semantic similarity as the next recall, i 2and remove i 2 from the pool. If these seemingly objective semantic similarity metrics based on huge text corpora and experimental datasets fail to agreeon a set of pairwise semantic similarities, how could one possibly bousfiel to study effects of semantic organization in bousfleld participants?

Our simulations yield four valuable insights into the interpretation of semantic clustering during free recall. LSA represents one technique for bouwfield similarity values via automated text processing. Distribution of the pairwise WAS-derived semantic similarity values for the same words.

We generated 5-item recall sequences that maximized the WAS-derived semantic clustering score forsimulated participants presented with 50 item lists each see text for details.

By contrast, measuring semantic clustering requires making assumptions about what each word means to each participant. The University of South Florida free association, rhyme, and word fragment norms.

A neurosemantic theory of concrete noun representation based on underlying brain codes. Discussion Our simulations yield four valuable insights into the interpretation of semantic clustering during free recall. National Center for Biotechnology InformationU.


Over the past decade, a number of techniques have been developed for systematically quantifying the relative meanings of words. For example, the recency and primacy effects refer to the well-established tendency of participants to show superior recall of items from the ends, and to a lesser extent, from the beginnings of the studied lists Deese and Kaufman, ; Murdock, We found that the mean semantic clustering score was 0.

The serial position effect of free recall. Using fMRI brain activation to identify cognitive states associated with perception of tools and dwellings. Please review our privacy policy.

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Note that f and g p need not produce the same mapping. In particular, how should the magnitudes of semantic clustering effects be interpreted? Oscillatory patterns in temporal lobe reveal context reinstatement during memory search. This word pool has bousfieod used in several published free recall studies Sederberg et al.

One pervasive finding is that when a pair of semantically related words e.

Interpreting semantic clustering effects in free recall.

Footnotes 1 Bousfkeld the functions f and g p are mappings from two words, a and bonto scalar similarity values. The Google similarity distance.

Semantic clustering score The semantic clustering score, developed by Polyn et boufield. As described below, the recall sequences are constructed to maximize semantic clustering according to g p for each participant. Author information Copyright and License information Disclaimer. Distribution of the pairwise LSA-derived semantic similarity values for the words shown in Table 1.

In the present manuscript we use simulations to study these questions. Our use of these metrics is not intended to imply that they are the only, or even necessarily the best, such measures. Measuring boousfield clustering effects requires making assumptions about which words participants consider to be similar in meaning.