58422 Mining the Web: eigenVectors, Kriging, Inverse DistanceWeighting Searches 58422

Site and Features: http://www.eigensearch.com

Search engine, eigenMethod, eigenvector, mathematical, manifolds, science, technical, search tools, eigenmath, Jacobian, quantum, mechanics, manifolds, science, physics, chemistry, law, legal, government, home, office, business, domain lookup, medical, travel, food, university students, searching, searchers, surfing, advanced search, search tools

Chemistry, mathematics, physical sciences, engineering, aerospace, astronomy, photography, news, computers, software, investment, venture capital, stakeholder, Biology, Chemistry, Geosciences, Biotechnology, Medical, Nursing, Anthropology, psychology, psychiatry, Philosophy, History, Business, bachelor, Ph.D., Masters, administrative, MBA, eigenMethod, eigenvector, mathematical, manifolds, science, technical, search tools, eigenmath, Jacobian, quantum, mechanics, manifolds, physics, chemistry, law, legal, health, government, home, office, business, domain, lookup, medical, travel, food, university, students, search, searches, search engine, directory, directories, category, categories, help, searching, searchers, surfing, advanced search, search help, search tips


Beta Users and advanced features Sign-up here... http://www.eigensearch.com/inc/const...betasignup.htm

Central to eigenSearch Advanced is the freedom to construct complex search explorations, save the forms for later use; and apply weight factor to each phrase and term. EigenSearch processing will apply eigenvector math and Jacobian matrices to construct search terms that are tailored to your exploration. Cross-pollination is also applied as described below. The eigenvector approach is clearly highly advanced and would normally be useful for very sophisticated applications. Nevertheless, anyone may utilize the method. An advanced form is simply a matrix in which the user types words and phrases randomly in a multi-cell form (please click thumbnail to view).

Advanced features

EigenOperator (cross pollination) and eigenvector constructs
Cross document content pollination within every web site directory tree (unlike conventional search engines and tools eigenSearch checks for your terms and phrases and drills down though multiple directory documents)
EigenSearch cross-pollination is applied to documents within the same (tree) level in a URL (peer documents). Thereby limiting the amount of contamination of results
Illustration:
"Blood Hounds" + "English Breed" will present documents that contain either of these phrases within the same peer level in a document storage structure; for example, within the directory: www.smartdogs/hounds.
eigenSearch limits pollinating occurrences outside a peer level. For example; "blood hounds" + "English breed" found in two different directories would not report an eigenSearch result: i.e. "Blood hounds" found in www.smartdogs/hounds and "English Breed" found in. www.smartdogs/hounds/Europe would not be found. EigenSearch therefore searches one tree (peer) level in a site and looks for multiple occurrences of multiple phrases across all documents within this peer level.
Corporate products can be tailored to drill down infinite levels for eigenOperator (cross-pollinating operator) matching.
eigenSearch single phrase results will find all documents and show the results as independent findings. This way the user can find results across many documents and the combined highly constrained results are reserved for a single level cross pollination.
Extremely high (cross-pollinating) eigenValues will correspond to finely granular and refined search explorations.

Beta users receive the following features:
Login and password
Save search constructs for later use in your own personal construct tables
EigenOperator (cross Pollinating Operator) advanced features as described above (eigenvector to follow)
Database (Table) upload and eigenvector computations
EigenSearch seeks 300,000 beta testers for its advanced eigenOperator based cognitive engine. This engine will allow for a multiplicity of search parameters for users to select so as to mathematically narrow results. The system will employ eigenVectors, eigenValues and eigenMatrices to determine relevance to user searches; thereby rendering high fidelity confirmed search results.
Naturally the computational power for doing such math is why beta testers are required. Each tester is welcome to comment on user friendliness, speed, change and ergonomic elegance. It is an eigenSearch goal to continue advancing the user interface so as to remain intuitively simple to use while at the same time providing hi-fidelity explorations.
All beta testers will receive a login and password, which provides entry into features for saving search constructs and parameters according to their own classification approach. Saved results and parameters can be used at any time and modified to alter search results. Beta users will be able to import their own data sets (2-dimentional) and perform an eigenValue analysis.







rp_

KEWL!


"Web Science" wrote in message
m...
Site and Features: http://www.eigensearch.com

Search engine, eigenMethod, eigenvector, mathematical, manifolds, science,
technical, search tools, eigenmath, Jacobian, quantum, mechanics, manifolds,
science, physics, chemistry, law, legal, government, home, office, business,
domain lookup, medical, travel, food, university students, searching,
searchers, surfing, advanced search, search tools

Chemistry, mathematics, physical sciences, engineering, aerospace,
astronomy, photography, news, computers, software, investment, venture
capital, stakeholder, Biology, Chemistry, Geosciences, Biotechnology,
Medical, Nursing, Anthropology, psychology, psychiatry, Philosophy, History,
Business, bachelor, Ph.D., Masters, administrative, MBA, eigenMethod,
eigenvector, mathematical, manifolds, science, technical, search tools,
eigenmath, Jacobian, quantum, mechanics, manifolds, physics, chemistry, law,
legal, health, government, home, office, business, domain, lookup, medical,
travel, food, university, students, search, searches, search engine,
directory, directories, category, categories, help, searching, searchers,
surfing, advanced search, search help, search tips


Beta Users and advanced features Sign-up here...
http://www.eigensearch.com/inc/const...betasignup.htm

Central to eigenSearch Advanced is the freedom to construct complex search
explorations, save the forms for later use; and apply weight factor to each
phrase and term. EigenSearch processing will apply eigenvector math and
Jacobian matrices to construct search terms that are tailored to your
exploration. Cross-pollination is also applied as described below. The
eigenvector approach is clearly highly advanced and would normally be useful
for very sophisticated applications. Nevertheless, anyone may utilize the
method. An advanced form is simply a matrix in which the user types words
and phrases randomly in a multi-cell form (please click thumbnail to view).

Advanced features

EigenOperator (cross pollination) and eigenvector constructs
Cross document content pollination within every web site directory tree
(unlike conventional search engines and tools eigenSearch checks for your
terms and phrases and drills down though multiple directory documents)
EigenSearch cross-pollination is applied to documents within the same
(tree) level in a URL (peer documents). Thereby limiting the amount of
contamination of results
Illustration:
"Blood Hounds" + "English Breed" will present documents that contain
either of these phrases within the same peer level in a document storage
structure; for example, within the directory: www.smartdogs/hounds.
eigenSearch limits pollinating occurrences outside a peer level. For
example; "blood hounds" + "English breed" found in two different directories
would not report an eigenSearch result: i.e. "Blood hounds" found in
www.smartdogs/hounds and "English Breed" found in.
www.smartdogs/hounds/Europe would not be found. EigenSearch therefore
searches one tree (peer) level in a site and looks for multiple occurrences
of multiple phrases across all documents within this peer level.
Corporate products can be tailored to drill down infinite levels for
eigenOperator (cross-pollinating operator) matching.
eigenSearch single phrase results will find all documents and show the
results as independent findings. This way the user can find results across
many documents and the combined highly constrained results are reserved for
a single level cross pollination.
Extremely high (cross-pollinating) eigenValues will correspond to finely
granular and refined search explorations.

Beta users receive the following features:
Login and password
Save search constructs for later use in your own personal construct tables
EigenOperator (cross Pollinating Operator) advanced features as described
above (eigenvector to follow)
Database (Table) upload and eigenvector computations
EigenSearch seeks 300,000 beta testers for its advanced eigenOperator
based cognitive engine. This engine will allow for a multiplicity of search
parameters for users to select so as to mathematically narrow results. The
system will employ eigenVectors, eigenValues and eigenMatrices to determine
relevance to user searches; thereby rendering high fidelity confirmed search
results.
Naturally the computational power for doing such math is why beta testers
are required. Each tester is welcome to comment on user friendliness, speed,
change and ergonomic elegance. It is an eigenSearch goal to continue
advancing the user interface so as to remain intuitively simple to use while
at the same time providing hi-fidelity explorations.
All beta testers will receive a login and password, which provides entry
into features for saving search constructs and parameters according to their
own classification approach. Saved results and parameters can be used at any
time and modified to alter search results. Beta users will be able to import
their own data sets (2-dimentional) and perform an eigenValue analysis.







rp_

KEWL!


"Web Science" wrote in message
m...
Site and Features: http://www.eigensearch.com

Search engine, eigenMethod, eigenvector, mathematical, manifolds, science,
technical, search tools, eigenmath, Jacobian, quantum, mechanics, manifolds,
science, physics, chemistry, law, legal, government, home, office, business,
domain lookup, medical, travel, food, university students, searching,
searchers, surfing, advanced search, search tools

Chemistry, mathematics, physical sciences, engineering, aerospace,
astronomy, photography, news, computers, software, investment, venture
capital, stakeholder, Biology, Chemistry, Geosciences, Biotechnology,
Medical, Nursing, Anthropology, psychology, psychiatry, Philosophy, History,
Business, bachelor, Ph.D., Masters, administrative, MBA, eigenMethod,
eigenvector, mathematical, manifolds, science, technical, search tools,
eigenmath, Jacobian, quantum, mechanics, manifolds, physics, chemistry, law,
legal, health, government, home, office, business, domain, lookup, medical,
travel, food, university, students, search, searches, search engine,
directory, directories, category, categories, help, searching, searchers,
surfing, advanced search, search help, search tips


Beta Users and advanced features Sign-up here...
http://www.eigensearch.com/inc/const...betasignup.htm

Central to eigenSearch Advanced is the freedom to construct complex search
explorations, save the forms for later use; and apply weight factor to each
phrase and term. EigenSearch processing will apply eigenvector math and
Jacobian matrices to construct search terms that are tailored to your
exploration. Cross-pollination is also applied as described below. The
eigenvector approach is clearly highly advanced and would normally be useful
for very sophisticated applications. Nevertheless, anyone may utilize the
method. An advanced form is simply a matrix in which the user types words
and phrases randomly in a multi-cell form (please click thumbnail to view).

Advanced features

EigenOperator (cross pollination) and eigenvector constructs
Cross document content pollination within every web site directory tree
(unlike conventional search engines and tools eigenSearch checks for your
terms and phrases and drills down though multiple directory documents)
EigenSearch cross-pollination is applied to documents within the same
(tree) level in a URL (peer documents). Thereby limiting the amount of
contamination of results
Illustration:
"Blood Hounds" + "English Breed" will present documents that contain
either of these phrases within the same peer level in a document storage
structure; for example, within the directory: www.smartdogs/hounds.
eigenSearch limits pollinating occurrences outside a peer level. For
example; "blood hounds" + "English breed" found in two different directories
would not report an eigenSearch result: i.e. "Blood hounds" found in
www.smartdogs/hounds and "English Breed" found in.
www.smartdogs/hounds/Europe would not be found. EigenSearch therefore
searches one tree (peer) level in a site and looks for multiple occurrences
of multiple phrases across all documents within this peer level.
Corporate products can be tailored to drill down infinite levels for
eigenOperator (cross-pollinating operator) matching.
eigenSearch single phrase results will find all documents and show the
results as independent findings. This way the user can find results across
many documents and the combined highly constrained results are reserved for
a single level cross pollination.
Extremely high (cross-pollinating) eigenValues will correspond to finely
granular and refined search explorations.

Beta users receive the following features:
Login and password
Save search constructs for later use in your own personal construct tables
EigenOperator (cross Pollinating Operator) advanced features as described
above (eigenvector to follow)
Database (Table) upload and eigenvector computations
EigenSearch seeks 300,000 beta testers for its advanced eigenOperator
based cognitive engine. This engine will allow for a multiplicity of search
parameters for users to select so as to mathematically narrow results. The
system will employ eigenVectors, eigenValues and eigenMatrices to determine
relevance to user searches; thereby rendering high fidelity confirmed search
results.
Naturally the computational power for doing such math is why beta testers
are required. Each tester is welcome to comment on user friendliness, speed,
change and ergonomic elegance. It is an eigenSearch goal to continue
advancing the user interface so as to remain intuitively simple to use while
at the same time providing hi-fidelity explorations.
All beta testers will receive a login and password, which provides entry
into features for saving search constructs and parameters according to their
own classification approach. Saved results and parameters can be used at any
time and modified to alter search results. Beta users will be able to import
their own data sets (2-dimentional) and perform an eigenValue analysis.







rp_