I'm looking for a list of common bad words so that I can create a filter.
Preferably a list with whole words, I don't want to filter out every word that contains a bad word (i.e. filtering all words containing ass would filter "assassinate")
I collected 2200 bad words in 12 languages: en, ar, cs, da, de, eo, es, fa, fi, fr, hi, hu, it, ja, ko, nl, no, pl, pt, ru, sv, th, tlh, tr, zh.
MySQL dump, JSON, XML or CSV options are available.
https://github.com/turalus/openDB
Check out: No swearing.. they presently have a limited api, but you can make a http request directly using their search url.
http://www.noswearing.com/search.php?st=ass&submit=Search
List of words plus script to insert into a MySQL database:
http://urbanoalvarez.es/blog/2008/04/04/bad-words-list/
Related
I have tried in vain to look up relevant questions. They are beyond my pay scale. I am not a professional. To explain this a bit more: in the HTML that I wrote, the em dash would be "& #151;" (that space inserted so it would not show up as an actual em dash). It ended up in the tables (someone else was doing that work) as "—". Those are not showing up correctly when searches are done using PHP. I only get the image with a question mark. I do have my SQL account set to Unicode.
Take a philosophical stand: The datastore (database table) should contain data, not some special encoding of the data.
The "data" is é
When you display that in HTML, you might need to convert it to e´. However, all modern browsers don't have a problem if é is encoded UTF-8.
If you choose to use "html entities", then have your application do the conversion after fetching é from the table. PHP has the function htmlentities() specifically for that task.
But, I still have not addressed what byte(s) are in the table to represent é. These days, you 'should' use UTF-8 (aka MySQL's utf8mb4). That would be two hex bytes C3A9, which can be discovered using SELECT HEX(col) .... If you use the old default, latin1, the hex would show C9.
A related question is whether you should store html 'tags' or construct the html on the fly after fetching the data. So, let me give you three philosophies; you pick which to apply:
The table contains pure data; formatting, etc, is done after fetching and before delivering to the user's browser.
The table contains an 'opaque' image of what needs to be sent to the browser -- complete with tags, entities, etc. With this approach, you may as well call it a BLOB, not TEXT.
Some compromise between those. Note: The use of CSS can avoid too much hard-coding of formatting before storing into the database.
Also, the first choice is much cleaner for searching. This may lead you to pick it. However, another approach is to have two columns -- one aimed at delivering mostly-formatted ouput; the other for searching (tags removed, no entities, etc); it would be mostly text, but you probably could not generate a web page (with links, paragraphs, etc) from it.
é -- different strokes for different folks
é in latin1 (not advised) hex E9, 1 byte
é in utf8 C3A9 2 bytes
\u00E9 -- Unicode codepoint -- 6 bytes
é -- html entity (see PHP's htmlentities()) -- 8 bytes
%C3%A9 -- PHP's urlencode() (for URLs) -- 6 bytes
Responding to Comments
If entries_lists, entries_languages, and authors_entries are many:many mapping tables, please consider the several optimizations mentioned here.
Do not use utf8_encode. Instead, figure out what caused them not to be encoded correctly, and/or not displayed correctly. Start by
echo bin2hex($record['author']);
SELECT name, HEX(name) FROM authors WHERE ...
for some author with an accented letter.
I was checking one share trading site's AJAX response and below is what it showed up in Firebug Response tab of XHR section. Can anyone explain me what format is this and how is it parsed ?
<ST=tat>
<SI=0>
<TB=txtSearch>
<560v=Tata Motors Ltdv=TATMOT>
<566v=Tata Steel Ltdv=TATSTE>
<3199v=Ashram Online.com Ltdv=ASHONL>
<4866v=Kreon Finnancial Services Ltdv=KREFIN>
<552v=Tata Chemicals Ltdv=TATCHE>
<554v=Tata Power Company Ltdv=TATPOW>
<2986v=Tata Metaliks Ltdv=TATMET>
<300v=Tata Sponge Iron Ltdv=TATSPO>
<121v=Tata Coffee Ltdv=TATCOF>
<2295v=Tata Communications Ltdv=TATCOM>
<0v=Time In Milli-Secondsv=0>
I think what we are dealing with here is some proprietary format, likely an Eldricht SGML Horror of some sort.
Banking in general has all sorts of Eldricht horrors running about.
On a related note, this is very much not XML.
Edit:
A quick analysis* indicates that this is a format consisting of a series of statements bracketed by <>; with the parts of the statements separated by = or v=. = seems to indicate a parameter to a control statement, indicated by a two-letter code. (<ST=tat>), while v= seems to indicate an assignment or coupling of some kind (short for "value"?), or perhaps just a field separator.
<ST appears to be short for "search term"; <TB appears to be short for "(source) table". The meaning of <SI eludes me. It is possible that <TB terminates the metadata section, but it's equally possible that the metadata section has a fixed number of terms.
As nothing refers to the number of fields in each statement in the data section, and they are all of the same length (3 fields), it is likely that the number of fields is fixed, but it might derive from the value of <TB, or even <SI, in some way.
What is abundantly clear, however, is that this data is not intended for consumption by other applications than the one that supplies it.
*Caveat: Without a much larger sample it's impossible to tell if this analysis is valid.
It is not a commonly used "web format".
It is probably a proprietary format used by that site and will be parsed by their custom JavaScript.
Given some (English) word that we shall assume is a plural, is it possible to derive the singular form? I'd like to avoid lookup/dictionary tables if possible.
Some examples:
Examples -> Example a simple 's' suffix
Glitch -> Glitches 'es' suffix, as opposed to above
Countries -> Country 'ies' suffix.
Sheep -> Sheep no change: possible fallback for indeterminate values
Or, this seems to be a fairly exhaustive list.
Suggestions of libraries in language x are fine, as long as they are open-source (ie, so that someone can examine them to determine how to do it in language y)
It really depends on what you mean by 'programmatically'. Part of English works on easy to understand rules, and part doesn't. It has to do mainly with frequency. For a brief overview, you can read Pinker's "Words and Rules", but do yourself a favor and don't take the whole generative theory of linguistics entirely to heart. There's a lot more empiricism there than that school of thought really lends to the pursuit.
A lot of English can be statistically lemmatized. By the way, stemming or lemmatization is the term you're looking for. One of the most effective lemmatizers which work off of statistical rules bootstrapped with frequency-based exceptions is the Morpha Lemmatizer. You can give this a shot if you have a project that requires this type of simplification of strings which represent specific terms in English.
There are even more naive approaches that accomplish much with respect to normalizing related terms. Take a look at the Porter Stemmer, which is effective enough to cluster together most terms in English.
Going from singular to plural, English plural form is actually pretty regular compared to some other European languages I have a passing familiarity with. In German for example, working out the plural form is really complicated (eg Land -> Länder). I think there are roughly 20-30 exceptions and the rest follow a fairly simple ruleset:
-y -> -ies (family -> families)
-us -> -i (cactus -> cacti)
-s -> -ses (loss -> losses)
otherwise add -s
That being said, plural to singular form becomes that much harder because the reverse cases have ambiguities. For example:
pies: is it py or pie?
ski: is it singular or plural for 'skus'?
molasses: is it singular or plural for 'molasse' or 'molass'?
So it can be done but you're going to have a much larger list of exceptions and you're going to have to store a lot of false positives (ie things that appear plural but aren't).
Is "axes" the plural of "ax" or of "axis"? Even a human cannot tell without context.
You can take a look at Inflector.net - my port of Rails' inflection class.
No - English isn't a language which sticks to many rules.
I think your best bet is either:
use a dictionary of common words and their plurals (or group them by their plural rule, eg: group words where you just add an S, words where you add ES, words where you drop a Y and add IES...)
rethink your application
It is not possible, as nickf has already said. It would be simple for the classes of words you have described, but what about all the words that end with s naturally? My name, Marius, for example, is not plural of Mariu. Same with Bus I guess. Pluralization of words in English is a one way function (a hash function), and you usually need the rest of the sentence or paragraph for context.
I have a huge list of person's full names that I must search in a huge text.
Only part of the name may appear in the text. And it is possible to be misspelled, misstyped or abreviated. The text has no tokens, so I don't know where a person name starts in the text. And I don't if know if the name will appear or not in the text.
Example:
I have "Barack Hussein Obama" in my list, so I have to check for occurrences of that name in the following texts:
...The candidate Barack Obama was elected the president of the United States... (incomplete)
...The candidate Barack Hussein was elected the president of the United States... (incomplete)
...The candidate Barack H. O. was elected the president of the United States... (abbreviated)
...The candidate Barack ObaNa was elected the president of the United States... (misspelled)
...The candidate Barack OVama was elected the president of the United States... (misstyped, B is next to V)
...The candidate John McCain lost the the election... (no occurrences of Obama name)
Certanily there isn't a deterministic solution for it, but...
What is a good heuristic for this kind of search?
If you had to, how would you do it?
You said it's about 200 pages.
Divide it into 200 one-page PDFs.
Put each page on Mechanical Turk, along with the list of names. Offer a reward of about $5 per page.
Split everything on spaces removing special characters (commas, periods, etc). Then use something like soundex to handle misspellings. Or you could go with something like lucene if you need to search a lot of documents.
What you want is a Natural Lanuage Processing library. You are trying to identify a subset of proper nouns. If names are the main source of proper nouns than it will be easy if there are a decent number of other proper nouns mixed in than it will be more difficult. If you are writing in JAVA look at OpenNLP or C# SharpNLP. After extracting all the proper nouns you could probably use Wordnet to remove most non-name proper nouns. You may be able to use wordnet to identify subparts of names like "John" and then search the neighboring tokens to suck up other parts of the name. You will have problems with something like "John Smith Industries". You will have to look at your underlying data to see if there are features that you can take advantage of to help narrow the problem.
Using an NLP solution is the only real robust technique I have seen to similar problems. You may still have issues since 200 pages is actually fairly small. Ideally you would have more text and be able to use more statistical techniques to help disambiguate between names and non names.
At first blush I'm going for an indexing server. lucene, FAST or Microsoft Indexing Server.
I would use C# and LINQ. I'd tokenize all the words on space and then use LINQ to sort the text (and possibly use the Distinct() function) to isolate all the text that I'm interested in. When manipulating the text I'd keep track of the indexes (which you can do with LINQ) so that I could relocate the text in the original document - if that's a requirement.
The best way I can think of would be to define grammars in python NLTK. However it can get quite complicated for what you want.
I'd personnaly go for regular expressions while generating a list of permutations with some programming.
Both SQL Server and Oracle have built-in SOUNDEX Functions.
Additionally there is a built-in function for SQL Server called DIFFERENCE, that can be used.
pure old regular expression scripting will do the job.
use Ruby, it's quite fast. read lines and match words.
cheers
Seeking a method to:
Take whitespace separated tokens in a String; return a suggested Word
ie:
Google Search can take "fonetic wrd nterpreterr",
and atop of the result page it shows "Did you mean: phonetic word interpreter"
A solution in any of the C* languages or Java would be preferred.
Are there any existing Open Libraries which perform such functionality?
Or is there a way to Utilise a Google API to request a suggested word?
In his article How to Write a Spelling Corrector, Peter Norvig discusses how a Google-like spellchecker could be implemented. The article contains a 20-line implementation in Python, as well as links to several reimplementations in C, C++, C# and Java. Here is an excerpt:
The full details of an
industrial-strength spell corrector
like Google's would be more confusing
than enlightening, but I figured that
on the plane flight home, in less than
a page of code, I could write a toy
spelling corrector that achieves 80 or
90% accuracy at a processing speed of
at least 10 words per second.
Using Norvig's code and this text as training set, i get the following results:
>>> import spellch
>>> [spellch.correct(w) for w in 'fonetic wrd nterpreterr'.split()]
['phonetic', 'word', 'interpreters']
You can use the yahoo web service here:
http://developer.yahoo.com/search/web/V1/spellingSuggestion.html
However it's only a web service... (i.e. there are no APIs for other language etc..) but it outputs JSON or XML, so... pretty easy to adapt to any language...
You can also use the Google API's to spell check. There is an ASP implementation here (I'm not to credit for this, though).
First off:
Java
C++
C#
Use the one of your choice. I suspect it runs the query against a spell-checking engine with a word limit of exactly one, it then does nothing if the entire query is valid, otherwise it replaces each word with that word's best match. In other words, the following algorithm (an empty return string means that the query had no problems):
startup()
{
set the spelling engines word suggestion limit to 1
}
option 1()
{
int currentPosition = engine.NextWord(start the search at word 0, querystring);
if(currentPosition == -1)
return empty string; // Query is a-ok.
while(currentPosition != -1)
{
queryString = engine.ReplaceWord(engine.CurrentWord, queryString, the suggestion with index 0);
currentPosition = engine.NextWord(currentPosition, querystring);
}
return queryString;
}
Since no one has yet mentioned it, I'll give one more phrase to search for: "edit distance" (for example, link text).
That can be used to find closest matches, assuming it's typos where letters are transposed, missing or added.
But usually this is also coupled with some sort of relevancy information; either by simple popularity (to assume most commonly used close-enough match is most likely correct word), or by contextual likelihood (words that follow preceding correct word, or come before one). This gets into information retrieval; one way to start is to look at bigram and trigrams (sequences of words seen together). Google has very extensive freely available data sets for these.
For simple initial solution though a dictionary couple with Levenshtein-based matchers works surprisingly well.
You could plug Lucene, which has a dictionary facility implementing the Levenshtein distance method.
Here's an example from the Wiki, where 2 is the distance.
String[] l=spellChecker.suggestSimilar("sevanty", 2);
//l[0] = "seventy"
http://wiki.apache.org/lucene-java/SpellChecker
An older link http://today.java.net/pub/a/today/2005/08/09/didyoumean.html
The Google SOAP Search APIs do that.
If you have a dictionary stored as a trie, there is a fairly straightforward way to find best-matching entries, where characters can be inserted, deleted, or replaced.
void match(trie t, char* w, string s, int budget){
if (budget < 0) return;
if (*w=='\0') print s;
foreach (char c, subtrie t1 in t){
/* try matching or replacing c */
match(t1, w+1, s+c, (*w==c ? budget : budget-1));
/* try deleting c */
match(t1, w, s, budget-1);
}
/* try inserting *w */
match(t, w+1, s + *w, budget-1);
}
The idea is that first you call it with a budget of zero, and see if it prints anything out. Then try a budget of 1, and so on, until it prints out some matches. The bigger the budget the longer it takes. You might want to only go up to a budget of 2.
Added: It's not too hard to extend this to handle common prefixes and suffixes. For example, English prefixes like "un", "anti" and "dis" can be in the dictionary, and can then link back to the top of the dictionary. For suffixes like "ism", "'s", and "ed" there can be a separate trie containing just the suffixes, and most words can link to that suffix trie. Then it can handle strange words like "antinationalizationalization".