In the NeuroGrid system I used to extract all the words from a page,
remove stopwords and then present the most frequently occuring terms to
the user as tag possibilities. More sophisticated approaches might use
TFIDF or something like that.
The main problem with this, and indeed any other approach that involves
parsing the page in question, is the time it takes to get the page and
parse it. The parsing usually won't take so long, but there will be a
few seconds delay to grab the page, and this can be a little frustrating
to users who are expecting a quick turnaround such as they currently get
with del
CHEERS> SAM
Clifford Caoile wrote:
But, how would you propose getting the recommendations in the first
place? What algorithms can succinctly summarize a home page?
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