I am creating an English search engine using Apache Lucene. Since I need to do the lemmatization for that, I am using Stanford CoreNLP and I know how to do that.
Is it possible to use MorfologikAnalyzer or something similar from the out of the box Apache Lucene to do the lemmatization?
Unfortunately, MorfologikAnalyzer is only suppose to work with Polish language and provide stemming capabilities, rather than lemmatization.
There are no built-in Apache Lucene analyzers that might help you. So, the existing options for you are the following:
Stanford CoreNLP
OpenNLP lemmatizer
NLTK Lemmatizer (Python)
Of course there are several paid lemmatization engines, some of them may be could be even more rich than those above, especially if lemmatization is required for the specific domain - publishing, etc.
I wouldn’t list any of them here, but it shouldn’t be hard to find them if needed.
Okay I am planning to create a local search engine in my intranet which searches the contents of files like xls,xlsx,doc,docx,pdb etc.
After searching in internet I am thinking that Luke Lucene can be used for this. Am I right?
Can Lucene be integrated in a Website?
I have around 500 Gb of files can Lucene handle these many files? Is there any alternative?
I know only basics of C and CPP.I dont have any prior knowledge on this. I am a self learner and please suggest me a good book on Lucene.
yes, Lucene can be used for this. But there is some code you need to write yourself (as Lucene is just a library):
- crawling code
- text extraction
- build a searcher app..
so you might be better looking at solr, that is built on top of Lucene, and has many built in features you would use: a solid server you can access with any language and dih for your crawling needs, and tika integration for text extraction, among many other things
I have worked with Lucene for indexing documents and providing search among them, however, my work was in English language, but now, I have a project which is Kurdish language, Kurdish language uses some Arabic unicode characters and several other characters, here is Table of Unicode Characters used in Kurdish-Arabic script
My question is how to create Analyzer for this language, or can I use Arabic Analyzer for this purpose?
Lucene has a list of other analyzers, including Arabic. I'm afraid there's no one which targets specifically Kurdish, but maybe you can extend Arabic analyzer to fit your needs?
Just bear in mind that all these analyzers come separately from the main Lucene distribution.
To answer your question about howto create a custom Analyzer for a new language..."Lucene In Action" book covers the creation of custom analyzers and it is pretty detailed. You can "leverage" a lot of the code found in other analyzers and just change what you need. Lucene is open source and very extensible, therefore profiling these changes is pretty easy.
Can we customize Lucene which is embedded in Solr just as we can in raw Lucene ? So that we can have "everything" that we have in Lucene in Solr ?
I am asking this because we are stuck at a point of deciding Solr vs Lucene, thinking like so :
Argument 1 :
"We might hit a dead zone in future if
we choose Solr, and Lucene is a better
choice hence... So we might as well
start writing HTTP wrappers and almost
half of Solr ourselves on top of
Lucene to be on safer side. "
Argument 2 :
"Solr already has all the features we
want to use, so why not just use it ?
Since people who commit to Lucene are
also responsible for committing to
Solr, all features of Lucene are
available to Solr too..."
I went through many blogs and posts that say something like :
For situations where you have very customized requirements requiring
low-level access to the Lucene API classes, Solr would be more a
hindrance than a help, since it is an extra layer of indirection.
-http://www.lucenetutorial.com/lucene-vs-solr.html
One way of defending Argument 2 is by confirming that we can customize the underlying Lucene in Solr just like we would do if we had only Lucene.
Can someone provide a better way of closing this argument ? :)
ps : We need a fast search with indexing and sharding terabytes of data...
Can we customize Lucene which is embedded in Solr ?
Yes, you can. But keep this in mind:
Lucene and Solr committers are some of the foremost experts in the field of full-text search. They have several years of experience in this field. If you think you can do better than them, then go ahead and change Solr to your needs (it's Apache-licensed so there aren't any commercial restrictions), and if you do so try to do it so that you can later contribute it back to the project so everyone can benefit and the project moves forward.
For the vast majority of Solr users though, the stock product is more than enough and satisfies all needs.
In other words, before jumping in to change the code, ask on a mailing list (stackoverflow or solr-user), there's a good chance that you don't really need to change any code.
"Fast search with indexing and sharding terabytes of data" is precisely what Solr was built for. It would be a bad case of Not-Invented-Here not to use it or any of the other similar solutions, such as ElasticSearch, Sphinx, Xapian, etc. If you think you'll need to customize or extend the search server in any way, consider the license and underlying code of each one. Solr and ElasticSearch are both Apache-licensed so they don't have commercial restrictions and are built on top of Lucene, a well-known library.
Our company has thousands of PDF documents. How do we create a simple search engine using Lucene, Solr or Nutch? We'll provide a basic Java/JSP web page were people can type in words and perform basic and/or queries then show them the document links of all matching PDF's.
I have had good luck with lucene, but it is not click, install and search, it does require a bit of work.
If you need something that yo can download and install and be searching within 10 minutes, look at the free Ominifind Yahoo Edition http://omnifind.ibm.yahoo.net/, it uses Lucene, but is packaged such that it is configured and ready to run upon install, a much easier way to try Lucene.
Nutch + Lucene + Pdf plugin enabled in Nutch is your solution. Nutch allows you to parse pdfs by enabling the pdf plugin.
Lucene will allow you to index the crawled and parsed data and Nutch has servelet which gives you a search interface.
We use the same for our internal lans.
None of the projects in the Lucene family can natively process PDFs, but there are utilities you can drop in and well written examples on how to roll your own.
Lucene will do pretty much whatever you need it to do, but there is overhead in terms of your time, as Tony said above. Thousands of documents really isn't that many, so you might be able to get away with a lighter weight alternative.
That said, I would still recommend looking at Solr - it's much, much easier to set up than Lucene, has support for backups, replication, etc., as well as a nifty JSON interface which would fit your use case very well: http://wiki.apache.org/solr/SolJSON
Google Search Appliance http://www.google.com/enterprise/gsa/
I think you want a system to manage your PDF file. Please try to use dspace system. Dspace is a digital library, it supports Lucene based on. www.dspace.org.
Take a look at eprints. It includes a workflow for adding new documents, automatically indexes and thumbnails PDF's and has fairly comprehensive full text search functionality. It can also be easily customised and branded.
Why re-invent the wheel. Again.
Answering such a broad question in this forum will be tough. I'd recommend you check out the book Lucene in Action, which covers the basics of indexing and searching in a quite readable fashion.
Given your application, it sounds like Nutch and Solr probably will not be necessary. Since all of your documents are available locally, Nutch probably won't be helpful. Solr may help you manage a cluster of searchers if you have a high query load, but Lucene is highly performant, and handles large document sets in a very scalable manner.
The one area that might consume a lot of your effort is the use of PDF. It's possible to index PDF documents, and there are Lucene contributions to facilitate the extraction of raw text from PDFs, but depending on the document, the quality of results can vary. Often, the context of a keyword in a PDF document is unclear because of formatting instructions, and that can make it hard to do proximity searches or show the context of a hit.
A great free search technology you might look at is the IBM Yahoo! free search. I'm not sure whether they followed through on plans to use Lucene under the covers, but it remains one of the really great, east to use free search technologies. It handles up to 500K documents, I believe, and it supports PDF and other non-text formats as well. Graphic user interface; easy to customize search results, and basic search analytics. Basic thesaurus, and powerful API so you can do pretty much whatever you want if the out of the box results are not to your liking. We've suggested this to a number of clients where there were fewer than half a million documents, and they love it.
If you've a Linux server, you could use Beagle to index them, and then just use the search functionality that comes with it. It has an (experimental) web search interface, and it can be hooked into the FireFox search box as well.
It automatically indexes files as they're included, and I'd suspect that you'll find it much more efficient to enhance or fix beagle than to write your own search interface to Lucene.
Having the (imho) distinct advantage of being on a Mac, I use SearchLight on a somewhat older G5. nice web interface to spotlight, the Mac OS' built-in indexing service.