Слайд 2Topic modeling
Models of a collection of composites
Composites are documents
Parts are words (or
![Topic modeling Models of a collection of composites Composites are documents Parts](/_ipx/f_webp&q_80&fit_contain&s_1440x1080/imagesDir/jpg/954281/slide-1.jpg)
phrases, n-grams)
Two outputs:
chance of selecting a particular part when sampling a particular topic
chance of selecting a particular topic when sampling a particular document or composite
Слайд 3Assumptions
semantic information can be derived from a word-document co-occurrence matrix;
topic is a
![Assumptions semantic information can be derived from a word-document co-occurrence matrix; topic](/_ipx/f_webp&q_80&fit_contain&s_1440x1080/imagesDir/jpg/954281/slide-2.jpg)
probability distribution over words
to make a new document, one chooses a distribution over topics
for each word in that document, one chooses a topic at random according to this distribution, and draws a word from that topic.
Resulting document is a mixture of topics