may someone give me a hint on how to index only words with a minimum length using Apache Lucene 5.3.1?
I've searched through the API but didn't find anything which suits my needs except this, but I couldn't figure out how to use that.
Thanks!
Edit:
I guess that's important info, so here's a copy of my explanation of what I want to achieve from my reply below:
"I don't intend to use queries. I want to create a source code summarization tool for which I created a doc-term matrix using Lucene. Now it also shows single- or double-character words. I want to exclude them so they don't show up in the results as they have little value for a summary. I know I could filter them when outputting the results, but that's not a clean solution imo. An even worse would be to add all combinations of single- or double-character words to the stoplist. I am hoping there is a more elegant way then one of those."
You should use a custom Analyzer with LengthTokeFilter. E.g.
Analyzer ana = CustomAnalyzer.builder()
.withTokenizer("standard")
.addTokenFilter("standard")
.addTokenFilter("lowercase")
.addTokenFilter("length", "min", "4", "max", "50")
.addTokenFilter("stop", "ignoreCase", "false", "words", "stopwords.txt", "format", "wordset")
.build();
But it is better to use a stopword (words what occur in almost all documents, like articles for English language) list. This gives a more accurate result.
Related
I'm not too familiar with Lucene so my apologies if this isn't clear or I'm getting my terms/nomenclature mixed up.
So I have a requirement where a field containing text (example part:123) should be able to be found via the following:
part:123
part 123
part123
Now my understanding of StandardAnalyzer is that it will break the word "part:123" into terms "part" and "123".
So with that, I'm able to search with part:123 or part 123, but because they're two different terms "part123" won't work.
It seems to me like I'd also need to get the indexer to add another term where both are combined, so it'd be "part", "123", "part123".
Is this the right way to accomplish this -- and does anyone know how I'd go about implementing this?
Thanks!
Using Lucene's standard analyzer. Title field in question is non-stored, analyzed. The query is as follows:
title:"Some-Url-Friendly-Title"
In Luke, this query gets correctly re-written as:
title:"some url friendly title" (- replaced by whitespace, everything lowercased).
I thought the Lucene.net version would be:
new TermQuery(new Term("title","Some-Url-Friendly-Title"))
However, no results are returned.
Then I tried:
_parser.GetFieldQuery("title","Some-Url-Friendly-Title")
And it worked as expected!
Both queries were executed via:
_searcher.Search([query object], [sort object])
Can somebody point me in the right direction to see what the differences between TermQuery and _parser.GetFieldQuery() are?
A TermQuery is much simpler than running a query through a queryparser. Not only is it not lowercased, and doesn't understand to break up hyphenated terms, it isn't even tokenized. It just searches for the term you tell it to look for. That means it is looking for the term "Some-Url-Friendly-Title" as a single untokenized keyword, in your index. I assume you are using an analyzer, so chances are no such tokens exist.
To take it a step further, if you had been searching for "Some Url Friendly Title" as the Term text, you still wouldn't come up with anything, since it's looking for "Some Url Friendly Title" as a Single Token, not as the four tokens (or rather, terms) in your index.
If you look at what a the standard query parser generates when you parse your query, you'll see that TermQueries are only one of the building blocks it uses to generate the complete query, along with BooleanQuery, and possibly PhraseQuery, PrefixQueriy, etc.
In Lucene.Net version 3.0.3 the GetFieldQuery is inaccessible due to it's protection modifier. Use
MultiFieldQueryParser.Parse(searchText, field)
instead.
I am using Lucene to search in a Data-set, I need to now how "" search (I mean exact phrase search) mechanism has been implemented?
I want to make it able to result all "little cat" hits when the user enters "littlecat". I now that I should manipulate the indexing code, but at least I should now how the "" search works.
I want to make it able to result all "little cat" hits when the user enters "littlecat"
This might sound easy but it is very tough to implement. For a human being little and cat are two different words but for a computer it does not know little and cat seperately from littlecat, unless you have a dictionary and your code check those two words in dictionary. On the other hand searching for "little cat" can easily search for "littlecat" aswell. And i believe that this goes beyong the concept of an exact phrase search. Exact phrase search will only return littlecat if you search for "littlecat" and vice versa. Even google seemingly (expectedly too), doesnt return "little cat" on littlecat search
A way to implement this is Dynamic programming - using a dictionary/corpus to compare your individual words against(and also the left over words after you have parsed the text into strings).
Think of it like you were writing a custom spell-checker or likewise. In this, there's also a scenario when more than one combination of words may be left over eg -"walkingmydoginrain" - here you could break the 1st word as "walk", or as "walking" , and this is the beauty of DP - since you know (from your corpus) that you can't form legitimate words from "ingmydoginrain" (ie rest of the string - you have just discovered that in this context - you should pick the segmented word as "Walking" and NOT walk.
Also think of it like not being able to find a match is adding to a COST function that you define, so you should get optimal results - meaning you can be sure that your text(un-separated with white spaces) will for sure be broken into legitimate words- though there may be MORE than one possible word sequences in that line(and hence, possibly also intent of the person seeking this)
You should be able to find pretty good base implementations over the web for your use case (read also : How does Google implement - "Did you mean" )
For now, see also -
How to split text without spaces into list of words?
I am trying to teach myself Lucene.Net to implement on my site. I understand how to do almost everything I need except for one issue. I am trying to figure out how to allow a fuzzy search for all search terms in a search string.
So for example if I have a document with the string The big red fox, I am trying to get bag fix to match it.
The problem is, it seems like in order to perform fuzzy searches, I have to add ~ to every search term the user enters. I am unsure of the best way to go about this. Right now I am attempting this by
string queryString = "bag rad";
queryString = queryString.Replace("~", string.Empty).Replace(" ", "~ ") + "~";
The first replace is due to Lucene.Net throwing an exception if the search string has a ~ already, apparently it can't handle ~~ in a phrase. This method works, but it seems like it will get messy if I start adding fuzzy weight values.
Is there a better way to default all words to allow for fuzzyness?
You might want to index your documents as bi-grams or tri-grams. Take a look at the CJKAnalyzer to see how they do it. You will want to download the source and look at the source.
Can someone please explain the difference between the different analyzers within Lucene? I am getting a maxClauseCount exception and I understand that I can avoid this by using a KeywordAnalyzer but I don't want to change from the StandardAnalyzer without understanding the issues surrounding analyzers. Thanks very much.
In general, any analyzer in Lucene is tokenizer + stemmer + stop-words filter.
Tokenizer splits your text into chunks, and since different analyzers may use different tokenizers, you can get different output token streams, i.e. sequences of chunks of text. For example, KeywordAnalyzer you mentioned doesn't split the text at all and takes all the field as a single token. At the same time, StandardAnalyzer (and most other analyzers) use spaces and punctuation as a split points. For example, for phrase "I am very happy" it will produce list ["i", "am", "very", "happy"] (or something like that). For more information on specific analyzers/tokenizers see its Java Docs.
Stemmers are used to get the base of a word in question. It heavily depends on the language used. For example, for previous phrase in English there will be something like ["i", "be", "veri", "happi"] produced, and for French "Je suis très heureux" some kind of French analyzer (like SnowballAnalyzer, initialized with "French") will produce ["je", "être", "tre", "heur"]. Of course, if you will use analyzer of one language to stem text in another, rules from the other language will be used and stemmer may produce incorrect results. It isn't fail of all the system, but search results then may be less accurate.
KeywordAnalyzer doesn't use any stemmers, it passes all the field unmodified. So, if you are going to search some words in English text, it isn't a good idea to use this analyzer.
Stop words are the most frequent and almost useless words. Again, it heavily depends on language. For English these words are "a", "the", "I", "be", "have", etc. Stop-words filters remove them from the token stream to lower noise in search results, so finally our phrase "I'm very happy" with StandardAnalyzer will be transformed to list ["veri", "happi"].
And KeywordAnalyzer again does nothing. So, KeywordAnalyzer is used for things like ID or phone numbers, but not for usual text.
And as for your maxClauseCount exception, I believe you get it on searching. In this case most probably it is because of too complex search query. Try to split it to several queries or use more low level functions.
In my perspective, I have used StandAnalyzer and SmartCNAnalyzer. As I have to search text in Chinese. Obviously, SmartCnAnalyzer is better at handling Chinese. For diiferent purposes, you have to choose properest analyzer.