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Best Way to Build a Searchable Document Index?

Posted by ScuttleMonkey on from the build-a-better-boss-trap dept.

Blinocac writes "I am organizing the IT documentation for the agency I work for, and we would like to make a searchable document index that would render results based on meta tags placed in the documents, which include everything from Word files, HTML, Excel, Access, and PDF's." What methods or tools have others seen that work? Anything to avoid?

12 of 216 comments (clear)

  1. Lucene by v_1_r_u_5 · · Score: 5, Informative

    Check out Apache's free Lucene engine, found at lucene.apache.org/. Lucene is a powerful indexing engine that handles all kinds of docs, and you can easily mod it to handle whatever it doesn't. It also allows custom scoring and a very powerful query language.

    1. Re:Lucene by Anonymous Coward · · Score: 5, Informative

      yes. It's hard to beat Lucene if you don't mind working at the API level. If you want a ready-build web crawler, check out Nutch, which is based on Lucene.

    2. Re:Lucene by BoberFett · · Score: 3, Informative

      I haven't used Lucene, but as for commercial software I've used dtSearch and ISYS and they are both excellent full text search engines. Both have web interfaces as well as desktop programs, and SDKs are available for custom applications. They scale to a massive number of documents per index, in a large variety of formats and are very fast. They have additional features like returning documents of all types in HTML so no reader is required on the front end other than a browser so legacy formats are easier to access.

    3. Re:Lucene by knewter · · Score: 4, Informative

      Lucene's good. If you haven't yet have a look at Ferret, a port of Lucene for Ruby. It's listed as faster than Lucene. I've used it in 20+ projects now as my built-in fulltext index of choice, and it's pretty great. You can easily define your own ranking algorithms if you'd like. You can find more information on Ferret here: http://ferret.davebalmain.com/trac/

      I've got a prototype of the system described in the OP that we did while quoting a fairly large project. It's really easy to have an 'after upload' action that'll push the document through strings (or some other third party app that can operate similarly, given the document type) and throw the strings into a field that gets indexed as well. That pretty much handles everything you may need.

      Obviously I'd also allow someone to specify keywords when uploading a document, but if this engine's going to just be thrown against an existing cache of documents, strings-only's the way to go.

      --
      -knewter
    4. Re:Lucene by passthecrackpipe · · Score: 4, Informative

      "If you needed to run, say 100 indexing engines in parallel and merge the indexes, you'd have to research that. Somebody's probably done it."

      Yes, they have. In my previous job we had to search 2 terrabytes of plain text data (HTML) really fast. The company chose Autonomy, and many developers spent many months trying to make it work, consuming insane amounts of hardware resources for mediocre results, and still requiring . One lone (and brilliant) dev whipped up a Lucene proof of concept in a weekend, and it was faster (full index in a day) required less resources (a single HP DL 585, 16GB RAM, 4xdual core AMD as opposed to 10 of the same), had a smaller index (about a 5th of Autonomies'), returned results faster, the result set was more accurate, and was significantly more flexible in making it do what we actually needed it to do.

      Lucene wins hands down

      --
      People who think they know everything are a great annoyance to those of us who do.
  2. Google by Anonymous Coward · · Score: 3, Informative

    We have a Google appliance, but you can do it with regular Google, too. Just make sure you disable caching (with headers or by encrypting documents). Then place an IP or password restriction for non-Google crawlers (check IP, not user-agent). People will be able to search with the power of Google, but only people you allow in will be able to get the full documents.

    If you value your privacy, invest in a Google mini, though.

    1. Re:Google by rta · · Score: 5, Informative

      Previous place i worked we had a Google Mini and it was better than anything we had come up with in-house.

      We even pointed it at the web-cvs server and bugzilla and it was great at searching those too.

      To see all the bugs still open against v 2.2.1 or something like that bugzilla's own search was better. but for searching for "bugs about X" the google mini was great.

      It only cost something like $3k ircc.

      not exactly what you asked about, but you should definitely see if this wouldn't work for you instead.

    2. Re:Google by shepmaster · · Score: 3, Informative

      The company I work for, Vivisimo, makes an awesome search engine. Although I've never dealt with the Google box directly, I know that we have had customers get fed up with the Google box and replace it quite easily with our software. Click the first link to see a pretty flash demo, or go to Clusty.com to try out a subset of the functionality for real. We specialize in "complex, heterogenous search solutions", which exactly fits most intranet sites I've seen. Files are on SMB shares, local disks, Sharepoint, Lotus, Documentum, IMAP, Exchange, etc, etc, etc. We connect to all those sources and provide a unified interface. You can do really neat tricks with combining content across multiple repositories, such as metadata from a database added to files on SMB shares. We support Linux, Solaris, and Windows, all 32 and 64 bit. Although I may work here, it really is a great product, and I use it at home to crawl my email archives and various blogs, websites, forums, things that I use frequently but have sucky search.

  3. Most easy solution by PermanentMarker · · Score: 4, Informative

    it wil cost you some bucks just buy MS sharepoint portal server, and leave the indexing over to sharepoint.
    Your not even realy required to use added tags... (as most people will put in poor tags).

    But if you like you can add tags even with sharepoint.

    --
    I know you're out there. I can feel you now. I know that you're afraid. You're afraid of us. You're afraid of change.
    1. Re:Most easy solution by DigitalSorceress · · Score: 3, Informative

      Actually, if you are an MS shop and have Microsoft Server 2003, SharePoint Services 3.0 (as opposed to the SharePoint Portal server (now renamed, I believe, to Microsoft Office SharePoint Server) which does indeed cost a packet.

      I do a lot of LAMP development, and I'm not the strongest fan of Microsoft for a lot of things, but if you have a MS desktop and MS Office environment, SharePoint services really is quite decent for INTRANET applications. Especially for collaberation. You can set up work flows for check-out/check-in, and it integrates really nicely with some of the more recent MS Office releases. If you connect it to a real MS SQL server on the back end (as opposed to the express edition that it defaults to), you can have full text indexing even with the free SharePoint Services version. Only need for the full blown Portal/MOSS version is if you think you are going to have a large number of sharePoint sites, and want to simplify cross-connecting and management. (At least as far as I can recall)

      I'm not saying SharePoint is the way to go, but I'd at least read up on it and consider it IF you have a lot of MS Office stuff that you plan on indexing/sharing.

      I'd strongly advise avoiding it if you plan to do Internet-based stuff though... at lest until you get a good enough understanding of the security issues involved that you feel that you really know what you're doing.

      Just my $0.02 worth.

      --

      The Digital Sorceress
  4. Also see Xapian by dmeranda · · Score: 4, Informative

    I'd suggest you should consider a full-text search engine. First start here:
    http://en.wikipedia.org/wiki/Full_text_search

    If you're not afraid to do a little reading and potentially coding a custom front end, you may want to look at two of the big open source engines: Lucene and Xapian.

    Lucene is quite popular now, and is an Apache Java project. It's a good choice if you're a Java shop.

    Xapian seems to be based on a little more solid and modern information retrieval theory and is incredibly scalable and fast. It's written in C++, with SWIG-based front ends to many languages. It might not have as polished of a front end or as fancy of a website as Lucene, but I believe it's a better choice if you have really really huge data sets or want to venture outside the Java universe.

    There are also many other wholely-contained indexers too, mostly which are based on web indexing (they have spiders, query forms, etc.) all bundled together. Like ht://Dig, mnogosearch, and so forth. They are good, especially if you want more of a drop-in solution rather than a raw indexing engine, and if you're indexing web sites (and not complex entities like databases, etc).

  5. Look at how you will access the docs first by rclandrum · · Score: 3, Informative

    As someone who has made a 30-year career out of designing and building document management systems, I would urge you to look first at how you expect your users to find the documents they need. The expected results of a search should guide your choice of indexing methods - and the popular "meta tagging" method isn't always the best. There are shortcomings with all methods.

    Full-text indexing allows users to search the entire contents of documents, but the results are imprecise and voluminous and not terribly useful in most cases (think web search engines here). Yes, you can find all documents that contain the word "patent", but you get a lot of old references to patent leather shoes in addition to what you were probably after. So, with full-text search you get it all, but force the user to subsearch for what they really want.

    Using meta-tags gives the appearance of pre-classifying documents and having the users do it themselves means you don't have to have a dedicated person to assign the tags. The disadvantage is that everybody makes up their own tags or if you have a standard set, you have to rely on people being diligent about applying them. And tag popularity can easily change over time. For example, if you want to find docs that refer to "removable media", this might have garnered a "floppy" tag 15 years ago and "CD" or "DVD" today. You are therefore almost guaranteed of missing some documents using this method.

    Database indexing means that you list all your docs in a database, perhaps by title, author, date, or other fields that your users would find useful for searching. The advantage is that every doucment is indexed the same way, searching is really fast, and the results are usually relevant if your schema is meaningful. The disadvantages are that indexing the docs takes work on input and users need to know how to search to get the best results.

    Finally, you could organize the docs by simple name and folder. This works fine for the desktop and users usually can identify the category that points them to the folder they want. The disadvantage is that this only works well for limited document sets. Once you start getting hundreds of categories and thousands and thousands of documents, things become too hard to find.

    So - understand your users search requirements and the size of your expected database. Only then can you make an informed decision about how to create and index the repository.