Search engines
Analysis of search technology, products, services, and vendors. Related subjects include:
A great new (to me) phrase – “Adversarial Information Retrieval”
I’ve just discovered a great new phrase – adversarial information retrieval. It’s not really new, since papers are now being accepted for what will be the third annual conference on the subject. But it seems to have gained currency over the past few months.
Edit: The term seems to have been coined in 2000.
I think this area is really where the bulk of the research into public search engine algorithms goes. And that’s another way of saying that web and enterprise search are very different things.
| Categories: Categorization and filtering, Search engine optimization (SEO), Search engines, Spam and antispam | 2 Comments |
The Chinese censorship threat continues to ratchet up
Ted Samsen of Infoworld is worried that the Chinese are attempting to ratchet up internet censorship yet further. Welcome to the club, buddy. This problem is a big one, and I don’t think it’s going to be addressed without vigorous action. I particular, I suspect that what is needed may be some major efforts in white-hat spamming. Lance Cottrell of Anonymizer has clever ideas along those lines for fighting censorship in the short term, but I think a bigger effort is needed as well.
Google, by the way, is caught in a tough spot and knows it.
| Categories: Categorization and filtering, Censorship, Google, Search engines, Spam and antispam, Website filtering | Leave a Comment |
FAST said to be pursuing BI
Dave Kellogg thinks FAST will be ineffective and defocused because of its efforts in business intelligence. I can’t comment on whether that analysis is brilliant, self-serving, or both, because anything I’ve been told on the subject is under embargo.
Embargos were a crucial PR tactic when Regis McKenna exploited them for the original rollout of the Macintosh in 1984. But I suspect that in many cases they’ve quite outlived their usefulness. If I wait between the time I’m briefed and the time the embargo is up to write something, my thoughts about it get fuzzy. If I write something at the time and put it on ice, it may be obsolete because of what other people write in the mean time.
More and more, if something is embargoed, I wind up not writing about it at all.
EDIT: Point #4 of my post on the mismatch between relational databases and text search is pretty relevant here.
| Categories: BI integration, Enterprise search, FAST | 1 Comment |
But Google trumps most site search
Popular on Digg, for obvious reasons, is a post showing that Google is better for searching Digg than Digg’s own search engine. No shock there. If I want to search Wikipedia for information on astrowidgets, I’ll just google on the phrase wikipedia astrowidgets. That works much better than Wikipedia’s own search.
Speaking of which — if you want to search for my writing, I’m using Google web search technology too. It works like a charm.
| Categories: Google, Search engines, Specialized search | 2 Comments |
41 differences between web and enterprise search
Based on a patent application, SEOmoz has discerned 65 aspects of the Google ranking algorithm.* I counted only 24 that really had much at all to do with enterprise search. This leaves 41 or so focused on spam/SEO-fighting and/or on-page linking issues that have no enterprise parallel. And for more depth, here’s a long article from another SEO site, on a specific phrase-concurrence spam-fighting technique that has no apparent applicability to trusted corpuses.
*I highly recommend this link. It is by far the best single-page overview of web search algorithmic issues I’ve ever seen.
I’ve said it before, but it bears repeating — web search and enterprise search (or search of a constrained corpus) are very different technical problems.
| Categories: Enterprise search, Google, Search engines | 5 Comments |
Text mining and search, joined at the hip
Most people in the text analytics market realize that text mining and search are somewhat related. But I don’t think they often stop to contemplate just how close the relationship is, could be, or someday probably will become. Here’s part of what I mean:
- Text mining powers search. The biggest text mining outfits in the world, possibly excepting the US intelligence community, are surely Google, Yahoo, and perhaps Microsoft.
- Search powers text mining. Restricting the corpus of documents to mine, even via a keyword search, makes tons of sense. That’s one of the good ideas in Attensity 4.
- Text mining and search are powered by the same underlying technologies. For starters, there’s all the tokenization, extraction, etc. that vendors in both areas license from Inxight and its competitors. Beyond that, I think there’s a future play in integrated taxonomy management that will rearrange the text analytics market landscape.
| Categories: Attensity, Business Objects and Inxight, Enterprise search, FAST, Google, IBM and UIMA, Ontologies, Open source text analytics, Search engines, Text mining | 3 Comments |
Enterprise-specific web search: High-end web search/mining appliances?
OK. I have a vision of one way search could evolve, which I think deserves consideration on at least a “concept-car” basis. This is all speculative; I haven’t discussed it at length with the vendors who’d need to make it happen, nor checked the technical assumptions carefully myself. So I could well be wrong. Indeed, I’ve at least half-changed my mind multiple times this weekend, just in the drafting of this post. Oh yeah, I’m also mixing several subjects together here too. All-in-all, this is not my crispest post …
Anyhow, the core idea is that large enterprises spider and index a subset of the Web, and use that for most of their employees’ web search needs. Key benefits would include:
- Filtering out spam hits. This is obviously important for search, and in some cases could help with public-web text mining as well. It should be OK to be more aggressive on spam-site filtering in an enterprise-specific index than it is in general web search.
- Filtering out malicious/undesirable downloads of various sorts. I’m thinking mainly of malware/spyware here, but of course it can also be used for netnannying porn-prevention and the like as well. Again, this is more easily done for the enterprise market than for the search world at large. (I anyway think that Google could blow Websense out of the water any time they wanted to – except, of course, for the not-so-small matter of not being seen as participating in the censorship business — but that’s a separate discussion.)
- Capturing employees’ search strings. This could be useful for various purposes, including discerning their interests, and building the corporate ontology for internal web search.
- Freshness control. If there’s a site you really care about, you can make sure it’s re-indexed frequently.
| Categories: Categorization and filtering, Convera, Enterprise search, FAST, Google, IBM and UIMA, Search engines, Spam and antispam, Specialized search, Text mining, Website filtering | 1 Comment |
Danny Sullivan and Yahoo on the past and future of search
Danny Sullivan argues that search interfaces haven’t changed significantly for a decade, and that this suggests that the ways people have tried to change them aren’t likely to work when people try the same things yet again. He backs his thesis up with lots of historical screenshot pictures, some of which actually made me a bit nostalgic. In particular, he suggests that topic/cluster-based query refinement is a non-starter.
If he’s wrong, it will probably be because people today are satisfied with search only some of the time. Here, in a Business Week article, is a pretty good cut at where search so far has and hasn’t worked:
“Web searching can be frustrating for a lot of people,” says Tomi Poutanen, Yahoo’s director of product management for social search. “Search does a very good job if you are searching for something factual or doing research. It is not as good when searching for experiential knowledge—such as what is a good sushi restaurant in New York—where a person’s experience would count in having that answer.”
| Categories: Search engines | Leave a Comment |
Two own-dogfood text-based bug-tracking applications
Last July I wrote about Google’s text-based project management system. Dave Kellogg of Mark Logic offers links to discussion of a related Google project, and adds news of his own — Mark Logic built a text-based bug tracking system in its own MarkLogic technology.
| Categories: Enterprise search, Google, Mark Logic, Search engines, Specialized search | Leave a Comment |
When the result is a lousy paragaph
John Dvorak, who I recall as being pompous but funny at the Microsoft Windows 1.0 release event (yes, I’m that old) — and rarely funny thereafter — has a rant on machine translation. The second page has some examples of different translations of the same passage. They do make me wonder why translations aren’t run through a more complete grammar-fixing process. Or, if that would have too many risky side effects, why the same translation program doesn’t offer several DIFFERENT translations, tuned to optimize against different kinds of error.
The same principle, of course, could be applied to gists/summaries in other text technologies, such as search. Sometimes, a decent UI would have room to allow user configurability and/or multiple bites at the output apple.
| Categories: Search engines | Leave a Comment |