I have 1,000,000 strings that I want to categorize. The way I do this is to bucket it if it contains a set of words or phrases. The set of words is about 10,000. Ideally I would be able to support regular expressions, but I am focused on making it run fast right now. Example phrases:
ford, porsche, mazda...
I really dont want to match each word against the strings one by one, so I decided to use regular expressions. Unfortunately, I am running into a regular expression issue:
Regexp.new("(a)"*253)
=> /(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)...
Regexp.new("(a)"*254)
RegexpError: regular expression too big: /(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)(a)...
where a would be one of my words or phrases. Right now, I am planning on running 10,000 / 253 matches. I read that the length of the regex heavily impacts performance, but my regex match is really simple and the regexp is created very quickly. I would like to get around the limitation somehow, or use a better solution if anyone has any ideas. Thanks.
You might consider other mechanisms for recognizing 10k words.
Trie: Sometimes called a prefix tree, it is often used by spell checkers for doing word lookups. See Trie on wikipedia
DFA (deterministic finite automata): A DFA is often created by the lexer in a compiler for recognizing the tokens of the language. A DFA runs very quickly. Simple regexes are often compiled into DFAs. See DFA on wikipedia
Related
I have some unique codes that are generated from strings (ex: website host names) in various independent components of my application.
These codes are meant to be used by machines only so i would like to keep them as short as possible.
The below algorithm would be applied to every word in the string. The output words would be concatenated with a dash to generate the unique code.
The current algorithm I have used:
- Skip word if length is less than 6
- Leave first character as is
- Remove every wowel in the word from the second character onwards
architectural digest eu => archtctrl-dgst-eu
arizona foothills magazine => arzn-fthlls-mgzn
Is there a better way to shorten an English word leaving it as recognisable as possible to a human reader?
The output should be deterministic and produce the same shortened version whenever it is run on the same input.
A good algorithm should also minimise the number of clashes for similarly spelt words.
I have some unique codes that are generated from strings
I am afraid that is not true. There are many English words that will reduce to the same 'code word' when stripped of their vowels. For example, 'leaving' -> 'living' Given, this is fairly rare, it could still cause issues.
How important is it that these 'code words' remain human-readable if as you say, they are meant to be used by machines only? If its not that important, I'd suggest looking into some simpler compression algorithms like Huffman Coding or LZW Compression. Then if the user needs to see the translation of the code word, just uncompress it.
If you must keep it human-readable, I'm not sure that there is much more you can do to shorten it. You could take a look at specific latin + greek roots, and determine if you can shorten those any more by hand, and then just substitute those out automatically.
Alternatively, you could turn to a phonetic approach. Automatically search the pronunciation of the word, and then see if that is any shorter (or itself can be compressed, taking 'cee' to 'C', or 'kay' to 'K'). This would be much more time and CPU intensive, but its still an option if you really, really need short but yet readable codes.
What you're generating sounds like what's called a "slug". There are many libraries to handle this for blogs or site generators that should suit your purposes. Here's a usage example from a Python library called slugify:
txt = "___This is a test ---"
r = slugify(txt)
self.assertEqual(r, "this-is-a-test")
Slug libraries generally work like this:
replacing non-ascii linguistic characters via a mapping (ex: 影師嗎 -> ying-shi-ma)
replace accented latin letters with ascii equivalents via a mapping (ex: C'est déjà l'été. -> c-est-deja-l-ete)
remove beginning and trailing spaces/punctuation
convert remaining spaces and punctuation to dashes, collapsing multiple dashes in a row to a single dash
If you want to make slugs shorter you could remove vowels or, more simply, use a maximum length.
I have some text generated by some lousy OCR software.
The output contains mixture of words and space-separated characters, which should have been grouped into words. For example,
Expr e s s i o n Syntax
S u m m a r y o f T e r minology
should have been
Expression Syntax
Summary of Terminology
What algorithms can group characters into words?
If I program in Python, C#, Java, C or C++, what libraries provide the implementation of the algorithms?
Thanks.
Minimal approach:
In your input, remove the space before any single letter words. Mark the final words created as part of this somehow (prefix them with a symbol not in the input, for example).
Get a dictionary of English words, sorted longest to shortest.
For each marked word in your input, find the longest match and break that off as a word. Repeat on the characters left over in the original "word" until there's nothing left over. (In the case where there's no match just leave it alone.)
More sophisticated, overkill approach:
The problem of splitting words without spaces is a real-world problem in languages commonly written without spaces, such as Chinese and Japanese. I'm familiar with Japanese so I'll mainly speak with reference to that.
Typical approaches use a dictionary and a sequence model. The model is trained to learn transition properties between labels - part of speech tagging, combined with the dictionary, is used to figure out the relative likelihood of different potential places to split words. Then the most likely sequence of splits for a whole sentence is solved for using (for example) the Viterbi algorithm.
Creating a system like this is almost certainly overkill if you're just cleaning OCR data, but if you're interested it may be worth looking into.
A sample case where the more sophisticated approach will work and the simple one won't:
input: Playforthefunofit
simple output: Play forth efunofit (forth is longer than for)
sophistiated output: Play for the fun of it (forth efunofit is a low-frequency - that is, unnatural - transition, while for the is not)
You can work around the issue with the simple approach to some extent by adding common short-word sequences to your dictionary as units. For example, add forthe as a dictionary word, and split it in a post processing step.
Hope that helps - good luck!
I'm wondering whether there is a way to generate the most specific regular expression (if such a thing exists) that matches a given string. Here's an illustration of what I want the method to do:
str = "(17 + 31)"
find_pattern(str)
# => /^\(\d+ \+ \d+\)$/ (or something more specific)
My intuition was to use Regex.new to accumulate the desired pattern by looping through str and checking for known patterns like \d, \s, and so on. I suspect there is an easy way for doing this.
This is in essence an algorithm compression problem. The simplest way to match a list of known strings is to use Regexp.union factory method, but that just tries each string in turn, it does not do anything "clever":
combined_rx = Regexp.union( "(17 + 31)", "(17 + 45)" )
=> /\(17\ \+\ 31\)|\(17\ \+\ 45\)/
This can still be useful to construct multi-stage validators, without you needing to write loops to check them all.
However, a generic pattern matcher that could figure out what you mean to match from examples is not really possible. There are too many ways in which you could consider strings to be similar or not. The closest I could think of would be genetic programming where you supply a large list of should match/should not match strings and the code guesses at the best regex by constructing random Regexp objects (a challenge in itself) and seeing how accurately they match and don't match your examples. The best matchers could be combined and mutated and tried again until you got 100% accuracy. This might be a fun project, but ultimately much more effort for most purposes than writing the regular expressions yourself from a description of the problem.
If your problem is heavily constrained - e.g. any example integer could always be replaced by \d+, any example space by \s+ etc, then you could work through the string replacing "matchable units", in fact using the same regular expressions checked in turn. E.g. if you match \A\d+ then consume the match from the string, and add \d+ to your regex. Then take the remainder of the string and look for next matching pattern. Working this way will have its limitations (you must know the full set of patterns you want to match in advance, and all examples would have to be unambiguous). However, it is more tractable than a genetic program.
What is the concept behind writing a program to find out rare codons in a list of sequences? I'm not asking the codings from anyone. Just want to know the concept.
here's some python for you:
codon = "TAG"
sequence = "AAAAAAAAAATAG"
if sequence.find(codon) != -1:
#found codon in the string!
Looking for patterns inside strings is the very reason-of-existence of loved loved and feared Regular Expressions.
These are expressions full of symbols which represent string patterns. With an appropriately built regular expression, you can search a text for any sub-text that "matches" the regular expression. This can allow you to find very complex patterns and perform a lot of operations like splitting, replacing, etc.
Hope this helps.
Arising out of this question, I'm looking for an elegant (ruby) way to compute the word signature suggested in this answer.
The idea suggested is to sort the letters in the word, and also run length encode repeated letters. So, for example "mississippi" first becomes "iiiimppssss", and then could be further shortened by encoding as "4impp4s".
I'm relatively new to ruby and though I could hack something together, I'm sure this is a one liner for somebody with more experience of ruby. I'd be interested to see people's approaches and improve my ruby knowledge.
edit: to clarify, performance of computing the signature doesn't much matter for my application. I'm looking to compute the signature so I can store it with each word in a large database of words (450K words), then query for words which have the same signature (i.e. all anagrams of a given word, that are actual english words). Hence the focus on space. The 'elegant' part is just to satisfy my curiosity.
The fastest way to create a sorted list of the letters is this:
"mississippi".unpack("c*").sort.pack("c*")
It is quite a bit faster than split('') and join(). For comparison it is also best to pack the array back together into a String, so you dont have to compare arrays.
I'm not much of a Ruby person either, but as I noted on the other comment this seems to work for the algorithm described.
s = "mississippi"
s.split('').sort.join.gsub(/(.)\1{2,}/) { |s| s.length.to_s + s[0,1] }
Of course, you'll want to make sure the word is lowercase, doesn't contain numbers, etc.
As requested, I'll try to explain the code. Please forgive me if I don't get all of the Ruby or reg ex terminology correct, but here goes.
I think the split/sort/join part is pretty straightforward. The interesting part for me starts at the call to gsub. This will replace a substring that matches the regular expression with the return value from the block that follows it. The reg ex finds any character and creates a backreference. That's the "(.)" part. Then, we continue the matching process using the backreference "\1" that evaluates to whatever character was found by the first part of the match. We want that character to be found a minimum of two more times for a total minimum number of occurrences of three. This is done using the quantifier "{2,}".
If a match is found, the matching substring is then passed to the next block of code as an argument thanks to the "|s|" part. Finally, we use the string equivalent of the matching substring's length and append to it whatever character makes up that substring (they should all be the same) and return the concatenated value. The returned value replaces the original matching substring. The whole process continues until nothing is left to match since it's a global substitution on the original string.
I apologize if that's confusing. As is often the case, it's easier for me to visualize the solution than to explain it clearly.
I don't see an elegant solution. You could use the split message to get the characters into an array, but then once you've sorted the list I don't see a nice linear-time concatenate primitive to get back to a string. I'm surprised.
Incidentally, run-length encoding is almost certainly a waste of time. I'd have to see some very impressive measurements before I'd think it worth considering. If you avoid run-length encoding, you can anagrammatize any string, not just a string of letters. And if you know you have only letters and are trying to save space, you can pack them 5 bits to a letter.
---Irma Vep
EDIT: the other poster found join which I missed. Nice.