Keyword not found recommendations

For issue #888.
Oh, I see. NFKD normalization converts `ä` to `a` + `"` which is, for most purposes, the exact same thing. When comparing with `hyva`, `hyva"` is considered to be closer than `hyvä`, though, because the former has all right characters plus one extra `"` while the latter has just three correct characters and one wrong. The results you get when comparing `hyva` to e.g. `hyve` seem to be same as when comparing it to `hyvä` so I don't think this is too important. Considering that it complicates the code a little and unicodedata import is problematic on Jython, it's probably better to just remove this logic altogether.

When I tested the above examples with difflib, I noticed that with cutoff 0.8 short strings need to be pretty close to each others to match:

```python
>>> get_close_matches('good', ['goed', 'god'], cutoff=0.7)
['god', 'goed']
 >>> get_close_matches('good', ['goed', 'god'], cutoff=0.8)
['god']
>>> get_close_matches('good for you', ['goed for you', 'god for you'], cutoff=0.8)
['god for you', 'goed for you']
```

It might be interesting try altering cutoff depending the length of the searched word somehow. Better to first get this pr ready otherwise, though.