Sentence examples for token frequency from inspiring English sources

It is known that token frequency has a strong influence on the memory representations and lexical strengths of words due to its "conserving effect".

Since CPD consists of 48 articles in total, it is not ideal for obtaining token frequency information that reflects the overall site-wide distributions of tokens in the target period.

Because these cognitive effects of token frequency are highly relevant to how well the public registers, receives, remembers, and responds to individual anti-corruption metaphors, we wanted to identify the most entrenched metaphor token in each of the four categories7.

Frequency features refer to the token frequency across 10,000 medical journal publications.

The corpus has a total type frequency of 341,771 morphemic units and a total token frequency of 287,792,797 morphemic units (cf. Tamaoka & Makioka, 2009).

Importantly, the words in each corpus occurred in their respective languages with approximately equal token frequency (Spanish mean frequency = 45.92 occurrences per million (sd = 1779.14); English mean frequency = 40.76 occurrences per million (sd = 724.160); t(38678) =.37, p =.71) further attesting to the comparability of the two corpora.

Alternatively, attributes may be an integer computed by token frequencies (TF) representing how many times each token occurs in the message.

However, technical challenges associated with the use of the Web as corpus limited our ability to obtain site-wide token frequencies of the metaphors.

This plot is coherent with statistical corpus characteristics observed for token frequencies of other corpora, showing the typical behavior that corpora have commonly an uneven distribution of word types.

The pre-stretched DE membrane with fixed edges responds to applied voltage change with a varying inner stress and, by the same token, its natural frequency and vibrational response can be tuned to suit particular frequencies of interest.

For instance, [32] developed a lexicon in which positive and negative values are associated to words, hashtags, and any sort of tokens according to the frequency with which these tokens appear in tweets containing positive and negative emoticons.