Multilingual federated search is a big deal for a couple of reasons. First, no one has done it up to now. Yes, Google just added translation into its universal search. And, no doubt Bing will follow suit. But, being able to search the quality scientific and technical information that sometimes is only available via federated search, and doing it in foreign languages, is important.
The second reason that multilingual federated search is so important is because China, Japan, Russia, and other nations produce large volumes of research output. As the world shrinks we can’t afford to ignore the non-English literature. In a blog article the author noted that Thomson Reuters highlighted the importance of China’s research output on the basis of sheer volume :
According to citation analysis based on data from Web of Science, China is ranked second in the world by number of scientific papers published in 2007. Scientific’s World IP Today Report on Global Patent Activity 2007 reported that China almost doubled its volume of patents from 2003 to 2007, and looks set to become a strong rival to Japan and the United States in years to come.
The bottom line: federated search is about research and research is global.
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Deep Web expert Marcus Zillman makes freely available a tremendous wealth of resources for people who want to understand the Deep Web, particularly how to search it. His recently published article, Deep Web Research 2010, reminds me of how prolific Mr. Zillman is and that the only fault I can find in Mr. Zillman’s work is the overwhelming volume of resources he provides.
Deep Web Research 2010 provides a list of perhaps 200 resources in 10 categories:
- Articles, Papers, Forums, Audios and Videos
- Cross Database Articles
- Cross Database Search Services
- Cross Database Search Tools
- Peer to Peer, File Sharing, Grid/Matrix Search Engines
- Resources – Deep Web Research
- Resources – Semantic Web Research
- Bot Research Resources and Sites
- Subject Tracer Information Blogs
There are many fascinating links to follow. I did notice that some of the links were either to sites where one would need to subscribe to a service or buy an article and that some of the links were old and the content could be out of date. But, those concerns aside, one could spend days or weeks getting lost in readings about the Deep Web.
The commercial investing and personal finance web-site, The Motley Fool, published a brief article about the deep Web. No, the article does not dive very deep in its assessment of the deep Web. It’s a very cursory introduction. But, it’s great to see such coverage at all in such a well respected investment site.
The article tells two ways that investors can make money from the deep Web: buy stock in companies that mine deep Web data, and use the deep Web in your investment research.
I strongly agree with this paragraph:
If you have a keen interest in [the deep Web], it is also possible to invest in technology that is going to indirectly help open up this ‘invisible web’. Let me cite one area that I think holds promise. I reckon analytics programs that can successfully measure the response of ad campaigns to the deep web community or successfully trace browsing habits in these areas will make their owners/investors a lot of money.
Yes, I believe sentiment mining is in its infancy and will only grow in its importance to marketers. If you have a few minutes you might enjoy the article.
Last reminder. Contest entries are due today.
I so much enjoy Carl Grant’s writings. Last month I got to meet Carl in person at the Enterprise Search Summit conference where I led a panel on federated search that he was a member of. I have to say I enjoy Carl in person every bit as much as I do via email and phone. And, we had a great dinner at a Cuban restaurant in San Jose.
A few weeks ago Carl authored an article at the ExLibris Blog: Another facet of the “library bypass strategies.” Here’s a piece of it.
[A concern] is in the area of e-content and discovery products which are being offered to the library marketplace. Increasingly, these are offered as pre-packaged solutions with a discovery interface and with databases from a select number of organizations. But there are some real differences in the offerings and librarians need to be careful how they select and implement this technology.
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We’re in the home stretch here. December 15 is the last day to get your contest submissions in. For those of you who don’t know about the contest and prizes, check out this press release.
SANTA FE, N.M., Dec. 2, 2009 — Submissions are due by December 15 for the second annual writing contest launched by the Federated Search Blog. Last year’s contest asked blog readers to predict the future of federated search and it rewarded winners with nearly $1,000 in cash prizes, and invaluable recognition in the industry through participation on a panel at the prestigious Computers In Libraries (CIL) Conference. This year’s contest doubles the cash prizes.
The 2010 contest challenges participants to creatively describe the most impressive federated search application they’ve ever seen or imagined. Submissions can be in the form of poetry (any style), essay, video, web-site mockup or other creative expression. An independent team of judges will choose first, second and third prize winners, who will earn cash prizes of $1000, $500 and $250 from Deep Web Technologies, sponsor of the Blog. Additionally, the winning submission will be featured in CIL Magazine and the top winner will participate in a panel at the CIL Conference in Spring 2010. Travel expenses will be paid by Deep Web Technologies.
“I’m excited about the contest. Aside from the cash prizes, I’m delighted about the visibility that the top winner gets and how that can greatly enhance his or her career, or help get a student’s career off to a great start,” said Sol Lederman, lead author for the Blog. “And, CIL’s support of the contest is very important to its success so I’m happy about their continued participation.”
Contest rules are available at http://federatedsearchblog.com/2009/10/21/broader-contest-bigger-prizes.