python中向量长度_Word2vec向量的长度有什么意义？

For given term frequency,

the vector length is seen to take values only in a

narrow interval. That interval initially shifts upwards

with increasing frequency. Around a frequency

of about 30, that trend reverses and the interval

shifts downwards.

...

Both forces determining the length of a word

vector are seen at work here. Small-frequency

words tend to be used consistently, so that the

more frequently such words appear, the longer

their vectors. This tendency is reflected by the upwards

trend in Fig. 3 at low frequencies. High-frequency

words, on the other hand, tend to be

used in many different contexts, the more so, the

more frequently they occur. The averaging over

an increasing number of different contexts shortens

the vectors representing such words. This tendency

is clearly reflected by the downwards trend

in Fig. 3 at high frequencies, culminating in punctuation

marks and stop words with short vectors at

the very end.

...

Figure 3: Word vector length v versus term frequency

tf of all words in the hep-th vocabulary.

Note the logarithmic scale used on the frequency

axis. The dark symbols denote bin means with the

kth bin containing the frequencies in the interval

[2k−1, 2k − 1] with k = 1, 2, 3, . . .. These means

are included as a guide to the eye. The horizontal

line indicates the length v = 1.37 of the mean

vector