Lecture 2. Tokenization and word counts: различия между версиями
Polidson (обсуждение | вклад) |
Polidson (обсуждение | вклад) |
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== Heaps' law == | == Heaps' law == | ||
Heaps' law ([Gelbukh, Sidorov, 2001]) | |||
The number of different types in a text is roughly proportional to an exponent of its size: | |||
<math> |V| = K * N^b </math> | |||
''N'' = number of tokens; | |||
|V| = size of vocabulary (i.e. number of types); | |||
''K'', ''b'' — free parameters, <math> K ;&cap [10; 100]; b ;&cap [0.4; 0.6] </math> | |||
== Why tokenization is difficult? == | == Why tokenization is difficult? == | ||
Версия от 21:19, 23 августа 2015
How many words?
"The rain in Spain stays mainly in the plain." 9 tokens: The, rain, in, Spain, stays, mainly, in, the, plain 7 (or 8) types: T = the rain, in, Spain, stays, mainly, plain
Type and token
Type is an element of the vocabulary.
Token is an instance of that type in the text.
N = number of tokens;
V - vocabulary (i.e. all types);
|V| = size of vocabulary (i.e. number of types).
How are N and |V| related?
Zipf's law
Zipf's law ([Gelbukh, Sidorov, 2001])
In any large enough text, the frequency ranks (starting from the highest) of types are inversely proportional to the corresponding frequencies:
f = 1/r
f — frequency of a type;
r — rank of a type (its position in the list of all types in order of their frequency of occurrence).
Heaps' law
Heaps' law ([Gelbukh, Sidorov, 2001])
The number of different types in a text is roughly proportional to an exponent of its size: <math> |V| = K * N^b </math>
N = number of tokens;
|V| = size of vocabulary (i.e. number of types);
K, b — free parameters, <math> K ;&cap [10; 100]; b ;&cap [0.4; 0.6] </math>