Python: clustering search engine keyword
Hi, I have CSV up to 20,000 rows (I each site Keywords in the search engine for a website, and many visits in the search engine.)
Am I clustering these keywords into groups of "same meaning", and create a hierarchy of groups (Structured according to the total number of searches per cluster).
An example cluster - "Women's Clothing" - Ideally there are keywords with these lines: Women's clothing, 1000 women's clothes, 300 women's clothing, 50 women's clothes, 6 women wear, 2
I can use something like the Python Natural Language Toolkit: and WordNet, but, I'm guessing that there will be reference keywords / phrases for some websites that WordNet knows nothing at all. For example If the website is a celebrity website, then Wordnet is unlikely to know anything about "Lady Gaga", worse if the website is a news website.
Therefore, I am also convincing that the solution should be one that is just going to use source data.
Similar to any one taken in my query, only I'm looking to start somewhere, but I'm using Python instead of Java.
I also wonder if Google may have any prediction and / or Google use of sophisticated.
However, any ideas / suggestions are most welcome,
thanks, / P>
I like the wow. I'm a pure dragon search engine which provides functionality of that kind of functionality, among other things see this.
The feature you are looking for calls "faceted search results"
Hernan / Div>
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