Change from one word to another

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Find Levenstein distance of two text fragments.

Create a list of all words in text.

Lemmatize all words in text.

Apply stemming to all words in text.

Add color to punctuation symbols in text.

Add color to letters in text.

Add color to words in text.

Add color to sentences in text.

Add color to paragraphs in text.

Mess up characters in your text.

Generate text using random words.

Generate lorem ipsum placeholder text.

Generate a crossword puzzle from the given words.

Convert text characters to their corresponding code points.

Convert numeric character code points to text.

Convert CSV data to plain text columns.

Convert plain text columns to a CSV file.

Create a list of all 3-grams.

Create a list of all n-skip-m-grams.

Encode the entire text to a single number.

Decode text that was encoded as a number back to text.

Divide text into chunks of certain size.

Apply formatting and modification functions to text.

Count the number of punctuation marks and other sybmols in text.

Count the number of letters in text.

Count the number of sentences in text.

Count the number of paragraphs in text.

Analyze text for most frequent letters, words, and phrases.

Analyze text for interesting patterns.

Add accent marks to text letters.

Add a counter before every letter in text.

Add a counter before every word in text.

Add a counter before every sentence in text.

Add a counter before every paragraph in text.

Interleave the letters or words of the given text fragments.

Mess up the spacing between letters in any text.

Extract all emails from text.

Extract all URLs from text.

Extract all numbers from text.

Extract all countries from text.

Extract all cities from text.

Convert text to punycode.

Convert punycode to text.

Encode text to Baudot encoding.

Decode Baudot-encoded text.

Encode text to base32 encoding.

Decode base32-encoded text.

Encode text to base45 encoding.

Decode base45-encoded text.

Encode text to base58 encoding.

Decode base58-encoded text.

Encode text to Ascii85 encoding.

Decode Ascii85-encoded text.

Encode text to base65536 encoding.

Decode base65536-encoded text.

Encode text to nettext encoding.

Decode nettext-encoded text.

Convert written text into natural sounding voice.

Convert a voice recording to text.

Encode text to UTF8 encoding.

Decode UTF8-encoded text.

Encode text to UTF16 encoding.

Decode UTF8-encoded text.

Encode text to UTF32 encoding.

Decode UTF32-encoded text.

Convert text to Unix-to-Unix encoding.

Decode Unix-to-Unix-encoded text.

Convert text to Xxencoding.

Encode text to QP encoding.

Remove all HTML tags from Text.

Remove all XML tags from Text.

Remove new line symbols from the end of each text line.

Find the difference between two text fragments.

Generate various text typos.

Generate a mirror reflection of text.

Grep text for regular expression matches.

Extract first symbols, words, or lines from text.

Extract last symbols, words, or lines from text

Return the first letter of each word in text.

Make every sentence to be two sentences in the given text.

Delete certain sentences from text.

Make every paragraph to be two paragraphs in the given text.

Create an image from all words in text.

Create a circle from all letters in text.

Create a spiral from all letters in text.

Create a circle from all words in text.

Create a matrix of any dimensions from letters in text.

Create a matrix of any dimensions from words in text.

Create a spiral from all words in text.

Split the input text into syllables.

Write any text on an LCD display (with LCD font).

Convert text to 2-dimensional drawing.

Convert text to 3-dimensional drawing.

Create a horizontally or vertically scrolling text.

Create a GIF animation of a text message.

Create a GIF animation that slowly reveals a text message.

Decode text using the wrong encoding and create garbled text.

Try to find original text from garbled mojibaked text.

Make text harder to read.

Generate the entire alphabet from a to z.

Print the alphabet in random order.

Make text barely readable.

Delete swear words from text.

Edit text in a neat browser-based editor.

asked Feb 5, 2010 at 7:02

codaddict’s graph approach is valid, though it takes O(n^2) time to build each graph, where n is the number of words of a given length. If that’s a problem, you can build a bk-tree much more efficiently, which makes it possible to find all words with a given edit distance (in this case, 1) of a target word.

answered Apr 16, 2013 at 0:30

You could simply use recursive back-tracking but this is far from the most optimal solution.

# Given two words of equal length that are in a dictionary, write a method to transform one word into another word by changing only
# one letter at a time.  The new word you get in each step must be in the
# dictionary.

# def transform(english_words, start, end):

# transform(english_words, 'damp', 'like')
# ['damp', 'lamp', 'limp', 'lime', 'like']
# ['damp', 'camp', 'came', 'lame', 'lime', 'like']


def is_diff_one(str1, str2):
    if len(str1) != len(str2):
        return False

    count = 0
    for i in range(0, len(str1)):
        if str1[i] != str2[i]:
            count = count + 1

    if count == 1:
        return True

    return False


potential_ans = []


def transform(english_words, start, end, count):
    global potential_ans
    if count == 0:
        count = count + 1
        potential_ans = [start]

    if start == end:
        print potential_ans
        return potential_ans

    for w in english_words:
        if is_diff_one(w, start) and w not in potential_ans:
            potential_ans.append(w)
            transform(english_words, w, end, count)
            potential_ans[:-1]

    return None


english_words = set(['damp', 'camp', 'came', 'lame', 'lime', 'like'])
transform(english_words, 'damp', 'lame', 0)

answered Oct 16, 2015 at 21:12

I don’t think this is edit distance.

I think this can be done using a graph. Just construct a graph from your dictionary, and attempt to navigate using your favorite graph traversal algorithm to the destination.

answered Feb 5, 2010 at 7:05

This is C# code to solve the problem using BFS:

//use a hash set for a fast check if a word is already in the dictionary
    static HashSet<string> Dictionary = new HashSet<string>();
    //dictionary used to find the parent in every node in the graph and to avoid traversing an already traversed node
    static Dictionary<string, string> parents = new Dictionary<string, string>();

    public static List<string> FindPath(List<string> input, string start, string end)
    {
        char[] allcharacters = {'a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'};

        foreach (string s in input)
            Dictionary.Add(s);
        List<string> currentFrontier = new List<string>();
        List<string> nextFrontier = new List<string>();
        currentFrontier.Add(start);
        while (currentFrontier.Count > 0)
        {
            foreach (string s in currentFrontier)
            {
                for (int i = 0; i < s.Length; i++)
                {
                    foreach (char c in allcharacters)
                    {
                        StringBuilder newWordBuilder = new StringBuilder(s);
                        newWordBuilder[i] = c;
                        string newWord = newWordBuilder.ToString();
                        if (Dictionary.Contains(newWord))
                        {
                            //avoid traversing a previously traversed node
                            if (!parents.Keys.Contains(newWord))
                            {
                                parents.Add(newWord.ToString(), s);
                                nextFrontier.Add(newWord);
                            }

                        }
                        if (newWord.ToString() == end)
                        {
                            return ExtractPath(start, end);

                        }
                    }
                }
            }
            currentFrontier.Clear();
            currentFrontier.Concat(nextFrontier);
            nextFrontier.Clear();
        }
        throw new ArgumentException("The given dictionary cannot be used to get a path from start to end");
    }

    private static List<string> ExtractPath(string start,string end)
    {
        List<string> path = new List<string>();
        string current = end;
        path.Add(end);
        while (current != start)
        {
            current = parents[current];
            path.Add(current);
        }
         path.Reverse();
         return path;
    }

answered Apr 10, 2014 at 20:18