AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |
Back to Blog
Qwiki question dc1/6/2024 ![]() Tell them you read it here!įor a while, we've talked about the ways we think enterprise search can - and likely will - improve in the future. Topic Explorer is a search technology neutral product, so it will work with your current solution whether you're using Lucene/Solr or a popular commercial technolgy. With the right taxonomy, it can be a great research tool for just about any vertical - risk management, eDiscovery, patent research, and more. What's really great about Topic Explorer is that it isn't limited to just pharma. ![]() Raritan co-founder Ted Sullivan gives a great video demo of the product you should see. Many of you will remember Lexalytics as the company that provided great sentiment analysis in the original FAST ESP product prior to the acquisition by Microsoft. ![]() The product, Topic Explorer, provides a way for users to dig through content and explore concepts from Raritan's extensive knowledgebase of medical terminology, augmented by the text analytics capabilities provided by Lexalytics. have recently released a great tool they developed using the Lexalytics, Inc. Our partners over at Raritan Technologies Inc. We've got 4 Tier-2 vendors on our "short list" that might be able to reduce machine counts by a factor of 10 or more over the Tier-1 and open source guys. The Tier-1 vendors can handle hundreds of millions of dcs, sure, but usually on quite a few machines, plus of course their premium licensing, and some non trivial setup at that point.Īnd as much as we love Lucene, Solr, Nutch and Hadoop, our tests show you need a fair number of machines if you're going to turn around a half billion docs in less than a week.Īnd beyond indexing time, once you start doing 3 or 4 facet filters, you also hit another performance knee. Clients who have a problem, and vendors who claim they can help.īut a basic question keeps coming up - not licensing - but "how many machines will we need?" And not everybody can put their data on a public cloud, and private clouds can't always spit out a dozen virtual machines to play with, plus duplicates of that for dev and staging, so not quite as trivial as some folks thing. We've been chatting with folks lately about really large data sets. You might take a look around to see what platform is right for you now and into the future. On the other hand, former President Reagan had a saying: Trust, but verify". You may look back and discover you made the right choice. If you are willing to acquire a platform for a couple of years and see what happens, go for it. You'll also remember that Microsoft, after acquiring FAST Search, dropped the entire non-Windows platforms a year later which impacted upwards of 70% of the FAST installed base. Some customers made the switch early on and were happy others fought to make IDOL work like K2, even with the 'compatibility mode and never succeeded. Some acquisitions like Verity's acquisition by Autonomy resulted in a wholesale replacement of the platform. If you are evaluating Vivisimo, that's a bit more difficult. Assuming Velocity is working for you, this acquisition should cause you no concern. What should Vivisimo customers do now? Well, based on IBM's strong customer ethic, I think the answer is "don't panic" = do nothing for now'. for one thing, clustering algorithms (and probably patents) a reputation for being able to handle huge data sets and federation. Hadoop is the Apache answer for big data, and trust me Hadoop is a hot topic this year. IBM has made huge investments in open source search over the last 10 years, specifically yin Lucene/Solr. One thing all of these sites have in common? Lots of data. In fact, Vivisimo had great success in a number of huge government sites including the US Social Security site, FirstGov, the Defense Intelligence Agency, and commercial sites such as Ely Lilly. They also had some really strong federation capabilities built in. The first time we saw them, in 2004, they were marketing 'Clusty', a web clustering product that could examine huge numbers of web pages and then associate - or cluster - documents on specific terms. Vivisimo was founded in 2000 out of Carnegie Mellon University. Now the tough question: what’s it all about? For the answer, let's take a quick trip to the early years of the decade. Earlier today, IBM announced that it was acquiring Vivisimo for an undisclosed sum.
0 Comments
Read More
Leave a Reply. |