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Arataur Two measures of semantic similarity A. LSA represents one technique for deriving similarity values via automated text processing. Open in a separate window. We order the words in the pool by their semantic similarity according to g p to i 1.

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See other articles in PMC that cite the published article. Abstract The order in which participants choose to recall words from a studied list of randomly selected words provides insights into how memories of the words are represented, organized, and retrieved.

One pervasive finding is that when a pair of semantically related words e. This tendency to successively recall semantically related words is termed semantic clustering Bousfield and Sedgewick, ; Bousfield, ; Cofer et al. Measuring semantic clustering effects requires making assumptions about which words participants consider to be similar in meaning. Our results provide a number of useful insights into the interpretation of semantic clustering effects in free recall.

Introduction 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. Because the participants are instructed to recall the items in the order they come to mind, the recall sequence reflects how the items are stored and retrieved from memory. By analyzing recall sequences during free recall, researchers have uncovered a number of trends that many participants exhibit.

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, In addition to ordering recalls by the study positions of the items, participants also exhibit striking effects of semantic clustering Bousfield and Sedgewick, ; Jenkins and Russell, ; Bousfield, ; Cofer et al.

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. By contrast, measuring semantic clustering requires making assumptions about what each word means to each participant.

Over the past decade, a number of techniques have been developed for systematically quantifying the relative meanings of words. Latent semantic analysis LSA; Landauer and Dumais, derives a set of pairwise similarity values by examining the co-occurrences of words in a large text corpus.

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 y, relative 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, Although the similarity values produced by each of these myriad similarity metrics are somewhat related, the pairwise correlations between the measures tend to be surprisingly low.

The full distributions of similarity values derived from the two metrics are shown in Figure 1 , Panels A and B. 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 expect to study effects of semantic organization in individual participants? In particular, how should the magnitudes of semantic clustering effects be interpreted?

In the present manuscript we use simulations to study these questions.

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Interpreting semantic clustering effects in free recall

See other articles in PMC that cite the published article. Abstract The order in which participants choose to recall words from a studied list of randomly selected words provides insights into how memories of the words are represented, organized, and retrieved. One pervasive finding is that when a pair of semantically related words e. This tendency to successively recall semantically related words is termed semantic clustering Bousfield and Sedgewick, ; Bousfield, ; Cofer et al. Measuring semantic clustering effects requires making assumptions about which words participants consider to be similar in meaning.

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Nijinn Interpreting semantic clustering effects in free recall The content is solely the responsibility of the authors and does not necessarily represent the official views of our supporting organizations. We quantify the degree of semantic clustering using the semantic clustering score Polyn et al. Although the similarity values produced by each of these myriad similarity metrics are somewhat related, the pairwise correlations between the measures tend to be surprisingly low. Each dot corresponds to a single comparison between two words. The primacy, recency, and temporal clustering effects may be measured objectively by examining the relative probabilities of bkusfield or transitioning between items that appeared at each serial position on a studied list. Because this procedure ensures that each recall will be followed by the most similar word that is yet to be recalled, by definition it will maximize the semantic bousfild score according to g p.

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