I am looking for a way to query for the most common adjacent words and/or most common included words in a document given a set of documents containing a word.
For example, I would like a query that would accept 'windows' and return a list of words that are most commonly found in a document containing 'windows', like 'microsoft' or 'doors'.
I would like to find adjacent words, but I also see a potential need in my application for eventually knowing the most common words also present in the document. An example of that might be 'linux' or 'efficiency'. Those words might not be adjacent to 'windows' but they are likely to be in the same document.
I found this question which helps me part way, but that only gets me the most common words given all the documents, or a specific document, not a set of documents.
Related
I have tested all available Analyzers on my Search Index. But none, except Keyword Analyzer, gave me proper sorted results in alphabetical order. But Keyword Analyzer doesn't fit in my filtering requirements. With Keyword Analyzer i couldn't search for a sub-string in a given sentence.
Example: "description": "This is 2 test different Analyzers in a Search Index"
Whitespace Analyzer gives proper search results but it doesn't help me with sorting. Does anyone have pointers on how we can achieve both sorting and searching with Search Index?
The analyzers define how text is broken into words and how those words are truncated (stemmed) into tokens for indexing. For example, the keyword analyzer keeps words intact in their entirety which is handy for tags.
Analyzers don't have much to do with sorting. By default, sorting is by "best match first" i.e. the documents that are the closest match to your input string appear first, which is what you might expect from a search engine.
You can override the default sort by supplying a sort parameter. e.g.
e.g. q=frank+sinatra&sort=date
See https://console.bluemix.net/docs/services/Cloudant/api/search.html#search for further sorting options.
I'm attempting to parse a file without any sort of specification to guide me. I plan to split a section of this file into variable names, but I'm not sure how the fields are delimited. Clearly there is a pattern in the way the delimiters change...could someone point me in the right direction?
Here's the data I'm interested in (spaces added by me for clarity):
#EEFDAAH TFLBFile CM ExecutionName EL FileContents GI %reserved IJ &ReadCount KE vTest B#CQETMV#Dmain#Ž¾àÅU
Full file (minus some invisible control characters):
MFP214DTest
JA
BMExecutionNameLFileContents
BCEAƒSTCF01TFLBFileTestRead0f36c096fa0~1~2~1~2~0~0~0~0~0~0~0~0~0~0~0~0~0~0~TFLBFile~TFLBFile~~0~0~2~0~0~0~0~1~0~0~0~0~0~0~ExecutionName~ExecutionName~0~0~0~0~0~0~0~0~0~0~0~0~0~0~0~1~0~0~0~0~FileContents~FileContents~0~0~0~0~0~0~0~0~0~0~0~0~0~0~0~1~0~0~0~0~0~1~~0~2~'Test'~15~0~1~0~FQ_dbopenwithfieldsDG_dbreadHprintoutFAHJ#A#WSHSJSGSASDSFSLQNhSHSJSGSISPQRhSESHQThSBTKf#EEFDAAHTFLBFileCMExecutionNameELFileContentsGI%reservedIJ&ReadCountKEvTestB#CQETMV#Dmain#Ž¾àÅU
It may have been better if you had posted one or two more records, and and hex as well. You firstly need to identify record types if they differ. It does indeed look like the leading fields might be handled differently, a record level header, they look space delimited. Try assuming there is a fixed number of fields here. If this fails, there may be different record types and included data may be conditional upon a map or type at the beginning of the record. It may be possible the fields can be read in arbitrary sequence similarly to argv[] elements as value pairs. Architecture would also be useful information, trailing bytes look suspiciously binary..
I've got a vocabulary, a, abandon, ... , z.
For some reason, I will use array rather than Trie to store them.
Thus a simple method can be: wordA\0wordB\0wordC\0...word\0
But there are some more economic methods for memory I think.
Since like is a substring of likely, we can only store the first position and length of like instead of the string itself. Thus we generate a "large string" which contains every words in vocabulary and use position[i] and length[i] to get the i-th word.
For example, vocabulary contains three words ab, cd and bc.
I construct abcd as the "large string".
position[0] = 0, length[0] = 2
position[1] = 2, length[1] = 2
position[2] = 1, length[2] = 2
So how to generate the "large string" is the key to this problem, are there any cool suggestions?
I think the problem is similar to TSP problem（Traveling Salesman Problem）, which is a NP problem.
The search keyword you're looking for is "dictionary". i.e. data structures that can be used to store a list of words, and test other strings for being present or absent in the dictionary.
Your idea is more compact than storing every word separately, but far less compact than a good data structure like a DAWG. As you note, it isn't obvious how to optimally choose how to overlap your strings. What you're doing is a bit like what a lossless compression scheme (like gzip) would do. If you don't need to check words against your compact dictionary, maybe just use gzip or LZMA to compress a sorted word list. Let their algorithms find the redundancy and represent it compactly.
I looked into dictionaries for a recent SO answer that caught my interest: Memory-constrained external sorting of strings, with duplicates combined&counted, on a critical server (billions of filenames)
For a dictionary that doesn't have to have new words added on the fly, a Directed Acyclic Word Graph is the way to go. You match a string against it by following graph nodes until you either hit a point where there's no edge matching the next character, or you get to the end of your input string and find that the node in the DAWG is marked as being a valid end-of-word. (Rather than simply a substring that is only a prefix of some words). There are algorithms for building these state-machines from a simple array-of-words dictionary in reasonable time.
Your method can only take advantage of redundancy when a whole word is a substring of another word, or end-of-one, start-of-another. A DAWG can take advantage of common substrings everywhere, and is also quite fast to match words against. Probably comparable speed to binary-searching your data structure, esp. if the giant string is too big to fit in the cache. (Once you start exceeding cache size, compactness of the data structure starts to outweigh code complexity for speed.)
Less complex but still efficient is a Trie (or Radix Trie), where common prefixes are merged, but common substrings later in words don't converge again.
If you don't need to modify your DAWG or Trie at all, you can store it efficiently in a single block of memory, rather than dynamically allocating each node. You didn't say why you didn't want to use a Trie, and also didn't acknowledge the existence of the other data structures that do this job better than a plain Trie.
I have a large set of short strings. What are some algorithms and indexing strategies for filtering the list on items that contain a substring? For example, suppose I have a list:
val words = List(
"pick",
"prepick",
"picks",
"picking",
"kingly"
...
)
How could I find strings that contain the substring "king"? I could brute force the problem like so:
words.filter(_.indexOf("king") != -1) // yields List("picking", "kingly")
This is only practical for small sets; Today I need to support 10 million strings, with a future goal in the billions. Obviously I need to build an index. What kind of index?
I have looked at using an ngram index stored in MySQL, but I am not sure if this is the best approach. I'm not sure how to optimally query the index when the search string is longer than the ngram size.
I have also considered using Lucene, but this is optimized around token matching, not substring matching, and does not seem to support the requirement of simple substring matching. Lucene does have a few classes related to ngrams (org.apache.lucene.analysis.ngram.NGramTokenFilter is one example), but these seem to be intended for spell check and autocomplete use cases, not substring matching, and the documentation is thin.
What other algorithms and indexing strategies should I consider? Are there any open source libraries that support this? Can the SQL or Lucene strategies (above) be made to work?
Another way to illustrate the requirement is with SQL:
SELECT word FROM words WHERE word LIKE CONCAT('%', ?, '%');
Where ? is a user provided search string, and the result is a list of words that contain the search string.
How big is the longest word?
if that's about 7-8 char you may find all substrings for each and every string and insert that substrings in trie (the one is used in Aho-Corasik - http://en.wikipedia.org/wiki/Aho-Corasick)
It will take some time to build the tree but then searching for all occurances will be O(length(searched word)).
Postgres has a module which does a trigram index
That seems an interesting idea too- building a trigram index.
About a comment in your question regarding how to break down text searches greater than n-gram length:
Here's one approach which will work:
Say we have a search string as "abcde" , and we have built a trigram index. (You have strings which are of smaller lengths-this could hit a sweet spot for you)
Let the search results of abc= S1, bcd=S2,cde=S3 (where S1,S2,S3 are sets of indexes )
Then the longest common substring of S1,S2,S3 will give the indexes that we want.
We can transform each set of indexes,as a single string separated by a delimiter (say space) before doing LCS.
After we find the LCS,we would have to search the indexes for the complete pattern,since we have broken down the search term. ie we would have to prune results which have "abc-XYZ- bcd-HJI-def"
The LCS of a set of strings can be efficiently found Suffix Arrays. or Suffix trees
I have created a fulltext catalog that stores the data from some of the columns in a table, but the contents seem to have been split apart by characters that I don't really want to be considered word delimiters. ("/", "-", "_" etc..)
I know that I can set the language for word breaker, and http://msdn.microsoft.com/en-us/library/ms345188.aspx gives som idea on how to install new languages - but I need more direct control than that, because all of those languages still break on the characters I want to not break on.
Is there a way to define my own language to use for finding word breakers?
Full text indexes only consider the characters _ and ` while indexing. All the other characters are ignored and the words get split where these characters occur. This is mainly because full text indexes are designed to index large documents and there only proper words are considered to make it a more refined search.
We faced a similar problem. To solve this we actually had a translation table, where characters like #,-, / were replaced with special sequences like '`at`','`dash`','`slash`' etc. While searching in the full text, u've to again replace ur characters in the search string with these special sequences and search. This should take care of the special characters.
The ability to configure FTS indexing is fairly limited out of the box. I don't think that you can use languages to do this.
If you are up for a challenge, and have access to some C++ knowledge, you can always write a custom IFilter implementation. It's not trivial, but not too difficult. See here for IFilter resources.