How many hash functions does my bloom filter need?

Question

Wikipedia says:

An empty Bloom filter is a bit array of m bits, all set to 0. There must also be k different hash functions defined, each of which maps or hashes some set element to one of the m array positions with a uniform random distribution.

I read the article, but what I don't understand is how k is determined. Is it a function of the table size?

Also, in hash tables I've written I used a simple but effective algorithm for automatically growing the hash's size. Basically, if ever more than 50% of the buckets in the table were filled, I would double the size of the table. I suspect you might still want to do this with a bloom filter to reduce false positives. Correct?

Answer 1

And to have it laid out in a neat little table:

http://pages.cs.wisc.edu/~cao/papers/summary-cache/node8.html