Hi Cui,
Try to read the scala version of LDAExample,
https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/mllib/LDAExample.scala
The matrix you're referring to is the corpus after vectorization.
One example, given a dict, [apple, orange, banana]
3 documents:
Apple orange
Orange banana
Apple banana
Can be represented by dense vectors:
1, 1, 0
0, 1, 1
1, 0, 1
Cheers,
Yuhao
-----Original Message-----
From: Cui xp [mailto:lifeiniao...@gmail.com]
Sent: Wednesday, May 6, 2015 4:28 PM
To: user@spark.apache.org
Subject: The explanation of input text format using LDA in Spark
Hi all,
After I read the example code using LDA in Spark, I found the input text in
the code is a matrix. the format of the text is as follows:
1 2 6 0 2 3 1 1 0 0 3
1 3 0 1 3 0 0 2 0 0 1
1 4 1 0 0 4 9 0 1 2 0
2 1 0 3 0 0 5 0 2 3 9
3 1 1 9 3 0 2 0 0 1 3
4 2 0 3 4 5 1 1 1 4 0
2 1 0 3 0 0 5 0 2 2 9
1 1 1 9 2 1 2 0 0 1 3
4 4 0 3 4 2 1 3 0 0 0
2 8 2 0 3 0 2 0 2 7 2
1 1 1 9 0 2 2 0 0 3 3
4 1 0 0 4 5 1 3 0 1 0
But I don't know the explanation of each line or each column. And if I have
several text documents, how do I process them to use LDA in Spark? Thanks.
Cui xp
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