Google reveals
$3m bonus plan
Matt Hines CNET
News.com
The search giant's top executives will be in line for massive
bonuses if they meet their targets, according to documents
filed with the SEC.
Search giant Google launched a new bonus programme that could
pay its senior executives as much as $3m each this year if
the company meets its financial goals.
In a document filed Friday with the US Securities and Exchange
Commission, Google offered details of its 2005 senior-executive
bonus plan. The company said in the filling that it created
the variable cash incentive programme to motivate participants
to achieve the company's financial and other performance objectives,
and to reward them for their achievements when those objectives
are met.
Google said the bonus plan will be tendered to all of its
executive officers except for co-founders Sergey Brin and
Larry Page, and chief executive Eric Schmidt. However, those
three top executives are known to be riding the company's
wave of success to financial security. As beneficiaries of
Google's unorthodox 2004 initial public offering, Schmidt
recently sold 113,000 shares of the company's stock for about
$22m, while Brin sold 200,000 shares for about $40m.
Google 'Allegra' February
update; Rumours re LSI (latent semantic indexing) abound on
the SEO forums;
How much of this is actually being used by
the majors is a source of much debate my take is; this is
the next logical step in search and will become a major piece
of the SE's algorythms in the future; Google bought Applied
Semantics early last year so are clearly advanced as is also
Microsoft. So what to do? start using related keywords and
synonyms on your site and take some focus off single keywords.
In your links rotate link text and use the same idea. This
description of LSI I found as i was researching;
"Latent semantic indexing adds an important step to
the document indexing process. In addition to recording which
keywords a document contains, the method examines the document
collection as a whole, to see which other documents contain
some of those same words. LSI considers documents that have
many words in common to be semantically close, and ones with
few words in common to be semantically distant... Although
the LSI algorithm doesn't understand anything about what the
words mean, the patterns it notices can make it seem astonishingly
intelligent.
When you search an LSI-indexed database, the search engine
looks at similarity values it has calculated for every content
word, and returns the documents that it thinks best fit the
query. Because two documents may be semantically very close
even if they do not share a particular keyword, LSI does not
require an exact match to return useful results. Where a plain
keyword search will fail if there is no exact match, LSI will
often return relevant documents that don't contain the keyword
at all.
For example: "In an AP news wire database, a search
for Saddam Hussein returns articles on the Gulf War, UN sanctions,
the oil embargo, and documents on Iraq that do not contain
the Iraqi president's name at all." "
There are many articles out there on this subject if you
have a spare few hours;
An
Integrated Approach - From Latent Semantics to Spatial Hypertext
- Chaomei Chen
http://research.microsoft.com/users/marycz/ht98.htm
Latent
Semantic Indexing (LSI), by Clara Yu, et al., National
Institute for Technology and Liberal Education, January 1,
2002. http://javelina.cet.middlebury.edu/lsa/out/lsa_definition.htm
Latent
Semantic Indexing Software (LSI):TelcordiaTM Beyond Keyword
Retrieval
Using
Latent Semantic Indexing for Information Filtering by
Peter W. Foltz Uni of Colarado
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