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Inference search engines? -- links to inference searches included.


Can inference search-engines narrow-down the number of often irrelevant
results, by using specific keywords; for the purpose of discerning
emerging social & business trends?

For example, if authors of content subconsciously mention the keywords
"lately and noticed" within the same brief sentence, the reader may
infer "an unintended message" through the process of "inferentia l
scanning;" a method of noting "semantic anomalies" which may
signal emerging trends.
Note: The wildcard character asterisk "*" is important for two
examples:

-- In the current month and year, the wildcard character "*"
represents a specific date. In quotations: "October * 2005" infers
content that mentions the current month and year. Yet, search results
also include older content.

-- Search terms in quotations with the wildcard character "*"
indicates two words NEAR each other: "lately * noticed." This type
of search is excellent for trend spotting.

-- Search results are further narrowed-down by an astounding 80-90% by
excluding such words he, she, me. After all, content which may signal
emerging trends usually doesn't contain 'he, she, me.' Certain
pronouns usually indicate personal accounts of individuals; rather than
the "collective conscious" of people & businesses developing into
emerging trends.

-- Examples of links offer plenty of ideas for experimenting with
different combinations of keywords. To narrow-down searches further;
the addition of keywords mentioning specific industries, occupations,
businesses, people, places, culture, etc. can discern developing
trends.

There are many examples of keywords useful for trend-spotting. Five
examples:

-- Lately and noticed example.

http://www.google.com/search?as_q=+l...h=&safe=images
-- Noticed lately is another variation.

http://www.google.com/search?hl=en&l...m3&btnG=Search
--'Lately and become' OR 'lately and becoming' can yield
"important developments" to watch.

http://www.google.com/search?as_q=%2...h=&safe=images
--'People have become' OR 'people are becoming' may infer
emerging developments from social points of view.

http://www.google.com/search?as_q=%2...h=&safe=images
--'Trend toward' AND 'becoming more' are one of the first
examples of keywords I developed for trend-watching.

http://www.google.com/search?hl=en&l...m3&btnG=Search
Entering in keywords which may infer content signaling the emerging
business & public zeitgeist yields a wide variety search results. In
quite a few cases, search results don't necessarily have value e.g.,
individual opinions which don't necessarily indicate emerging trends.
In some cases, search results yield specialty websites that are
fee-only and even restricted access content. Usually, content which may
be interpreted like "a crystal-ball of sorts" is free.

Any recommendations for marketing an "inference-like"
search-engine?

Thank-you

Oct 13 '05 #1
39 4391
Noticedtrends wrote:
Can inference search-engines narrow-down the number of often irrelevant
results, by using specific keywords; for the purpose of discerning
emerging social & business trends?

For example, if authors of content subconsciously mention the keywords
"lately and noticed" within the same brief sentence, the reader may
infer "an unintended message" through the process of "inferentia l
scanning;" a method of noting "semantic anomalies" which may
signal emerging trends.


Public relations wonks feed stories with exactly those key words to
bored, talentless news people who are in need of stories all the time.
Lies, lies, lies.

What you need is a system that you can train up. Punish it when it
predicts incorrectly or (less popularly used) reward it when it predicts
correctly. A neural net component to an expert system is in order.
--
mbstevens
http://www.mbstevens.com/
Oct 13 '05 #2

mbstevens wrote:
Noticedtrends wrote:
Can inference search-engines narrow-down the number of often irrelevant
results, by using specific keywords; for the purpose of discerning
emerging social & business trends?

For example, if authors of content subconsciously mention the keywords
"lately and noticed" within the same brief sentence, the reader may
infer "an unintended message" through the process of "inferentia l
scanning;" a method of noting "semantic anomalies" which may
signal emerging trends.
Public relations wonks feed stories with exactly those key words to
bored, talentless news people who are in need of stories all the time.
Lies, lies, lies.

Any set of keywords can be applied for better or for worse (mostly for
better in this case). Let's not throw the baby out with the bathwater!
What you need is a system that you can train up. Punish it when it
predicts incorrectly or (less popularly used) reward it when it predicts
correctly. A neural net component to an expert system is in order.
Great idea; it's not going to happen anytime soon. Human inputs &
intuition are needed for filtering out the truth from lies; just as
human feedback is needed for discerning..... ......emerging trends! --
mbstevens
http://www.mbstevens.com/


Oct 13 '05 #3
__/ [Noticedtrends] on Thursday 13 October 2005 21:50 \__
Can inference search-engines narrow-down the number of often irrelevant
results, by using specific keywords; for the purpose of discerning
emerging social & business trends?

Yes, but I guess it was rhetorical or maybe the question was intended to ask
if engines 'in the wild' are capable or are doing this.

For example, if authors of content subconsciously mention the keywords
"lately and noticed" within the same brief sentence, the reader may
infer "an unintended message" through the process of "inferentia l
scanning;" a method of noting "semantic anomalies" which may
signal emerging trends.

I have been thinking about such concepts when registering http://iuron.com a
few days ago. There is not much use of any semantics, yet.

Note: The wildcard character asterisk "*" is important for two
examples:

-- In the current month and year, the wildcard character "*"
represents a specific date. In quotations: "October * 2005" infers
content that mentions the current month and year. Yet, search results
also include older content.

The problem with much of the content on the Web is that even dates are
hard-coded in unnatural ways. As oppose to XML, standardised metadata or
the like, dates are embedded as standard content, unlike LaTeX, for
instance.

-- Search terms in quotations with the wildcard character "*"
indicates two words NEAR each other: "lately * noticed." This type
of search is excellent for trend spotting.

What would be the intended practicality? Use tags in Technorati, for
example, to spot trends. Tagclouds come to mind too. They feeds on plenty
of fresh RSS'd (XML, hence time labelled) content.

-- Search results are further narrowed-down by an astounding 80-90% by
excluding such words he, she, me. After all, content which may signal
emerging trends usually doesn't contain 'he, she, me.' Certain
pronouns usually indicate personal accounts of individuals; rather than
the "collective conscious" of people & businesses developing into
emerging trends.

-- Examples of links offer plenty of ideas for experimenting with
different combinations of keywords. To narrow-down searches further;
the addition of keywords mentioning specific industries, occupations,
businesses, people, places, culture, etc. can discern developing
trends.

There are many examples of keywords useful for trend-spotting. Five
examples:

-- Lately and noticed example.

<LONG URL>

-- Noticed lately is another variation.

<LONG URL> >

--'Lately and become' OR 'lately and becoming' can yield
"important developments" to watch.

<LONG URL> >

--'People have become' OR 'people are becoming' may infer
emerging developments from social points of view.

<LONG URL> >

--'Trend toward' AND 'becoming more' are one of the first
examples of keywords I developed for trend-watching.

<LONG URL> >

Entering in keywords which may infer content signaling the emerging
business & public zeitgeist yields a wide variety search results. In
quite a few cases, search results don't necessarily have value e.g.,
individual opinions which don't necessarily indicate emerging trends.
In some cases, search results yield specialty websites that are
fee-only and even restricted access content. Usually, content which may
be interpreted like "a crystal-ball of sorts" is free.

Any recommendations for marketing an "inference-like"
search-engine?

Thank-you

I like your direction of thoughts, but I think you must go farther than that
in order to make it viable or marketable. I am currently looking into
similar idea and may soon speak to one of the fathers of the semantic Web.
I truly believe it's where we all are headed.

Roy
--
Roy S. Schestowitz | Useless fact: Women blink twice as much as men
http://Schestowitz.com | SuSE Linux | PGP-Key: 74572E8E
3:45pm up 50 days 3:59, 3 users, load average: 0.13, 0.12, 0.09
http://iuron.com - next generation of search paradigms
Oct 14 '05 #4
Roy Schestowitz wrote:
The problem with much of the content on the Web is that even dates are
hard-coded in unnatural ways. As oppose to XML, standardised metadata or
the like, dates are embedded as standard content, unlike LaTeX, for
instance.


There are some Perl modules that can help with this kind of data mining
until such time as there is a semantic web.

--'People have become' OR 'people are becoming' may infer
emerging developments from social points of view.
<LONG URL> >

--'Trend toward' AND 'becoming more' are one of the first
examples of keywords I developed for trend-watching.


Because of the very common practice of PR people to claim trends when
there aren't any, depending on the content of any few articles is not
likely to predict a trend. You would have to mine over hundreds of
articles, comparing content with your system. Since it is possible to
create temporary 'trends' with PR techniques, if you have enough money
to pump into it, careful weighing of sources is also in order.
Modification of weights given to particular sources might be one method
of training the system -- among others.
Oct 14 '05 #5

Roy Schestowitz wrote:
__/ [Noticedtrends] on Thursday 13 October 2005 21:50 \__
Can inference search-engines narrow-down the number of often irrelevant
results, by using specific keywords; for the purpose of discerning
emerging social & business trends?

Yes, but I guess it was rhetorical or maybe the question was intended to ask
if engines 'in the wild' are capable or are doing this.

For example, if authors of content subconsciously mention the keywords
"lately and noticed" within the same brief sentence, the reader may
infer "an unintended message" through the process of "inferentia l
scanning;" a method of noting "semantic anomalies" which may
signal emerging trends.

I have been thinking about such concepts when registering http://iuron.com a
few days ago. There is not much use of any semantics, yet.

Note: The wildcard character asterisk "*" is important for two
examples:

-- In the current month and year, the wildcard character "*"
represents a specific date. In quotations: "October * 2005" infers
content that mentions the current month and year. Yet, search results
also include older content.

The problem with much of the content on the Web is that even dates are
hard-coded in unnatural ways. As oppose to XML, standardised metadata or
the like, dates are embedded as standard content, unlike LaTeX, for
instance.

-- Search terms in quotations with the wildcard character "*"
indicates two words NEAR each other: "lately * noticed." This type
of search is excellent for trend spotting.

What would be the intended practicality? Use tags in Technorati, for
example, to spot trends. Tagclouds come to mind too. They feeds on plenty
of fresh RSS'd (XML, hence time labelled) content.
Initial search queries in most search-engines recognize the wildcard character "*" within two keywords in quotations -- very-much like the Boolean NEAR; locating examples of keywords very close to each other. Same applies for current month, wildcard chacrater, & year. Search-engine results note "..." within text if keywords don't match month, any date, year.


Any considerations for applying NEAR search options in most
search-engines?
-- Search results are further narrowed-down by an astounding 80-90% by
excluding such words he, she, me. After all, content which may signal
emerging trends usually doesn't contain 'he, she, me.' Certain
pronouns usually indicate personal accounts of individuals; rather than
the "collective conscious" of people & businesses developing into
emerging trends.

-- Examples of links offer plenty of ideas for experimenting with
different combinations of keywords. To narrow-down searches further;
the addition of keywords mentioning specific industries, occupations,
businesses, people, places, culture, etc. can discern developing
trends.

There are many examples of keywords useful for trend-spotting. Five
examples:

-- Lately and noticed example.

<LONG URL>

-- Noticed lately is another variation.

<LONG URL> >

--'Lately and become' OR 'lately and becoming' can yield
"important developments" to watch.

<LONG URL> >

--'People have become' OR 'people are becoming' may infer
emerging developments from social points of view.

<LONG URL> >

--'Trend toward' AND 'becoming more' are one of the first
examples of keywords I developed for trend-watching.

<LONG URL> >

Entering in keywords which may infer content signaling the emerging
business & public zeitgeist yields a wide variety search results. In
quite a few cases, search results don't necessarily have value e.g.,
individual opinions which don't necessarily indicate emerging trends.
In some cases, search results yield specialty websites that are
fee-only and even restricted access content. Usually, content which may
be interpreted like "a crystal-ball of sorts" is free.

Any recommendations for marketing an "inference-like"
search-engine?

Thank-you

I like your direction of thoughts, but I think you must go farther than that
in order to make it viable or marketable. I am currently looking into
similar idea and may soon speak to one of the fathers of the semantic Web.
I truly believe it's where we all are headed.

Roy
--
Roy S. Schestowitz | Useless fact: Women blink twice as much as men
http://Schestowitz.com | SuSE Linux | PGP-Key: 74572E8E
3:45pm up 50 days 3:59, 3 users, load average: 0.13, 0.12, 0.09
http://iuron.com - next generation of search paradigms


Oct 14 '05 #6

Roy Schestowitz wrote:
__/ [Noticedtrends] on Thursday 13 October 2005 21:50 \__
Can inference search-engines narrow-down the number of often irrelevant
results, by using specific keywords; for the purpose of discerning
emerging social & business trends?

Yes, but I guess it was rhetorical or maybe the question was intended to ask
if engines 'in the wild' are capable or are doing this.

For example, if authors of content subconsciously mention the keywords
"lately and noticed" within the same brief sentence, the reader may
infer "an unintended message" through the process of "inferentia l
scanning;" a method of noting "semantic anomalies" which may
signal emerging trends.

I have been thinking about such concepts when registering http://iuron.com a
few days ago. There is not much use of any semantics, yet.

Note: The wildcard character asterisk "*" is important for two
examples:

-- In the current month and year, the wildcard character "*"
represents a specific date. In quotations: "October * 2005" infers
content that mentions the current month and year. Yet, search results
also include older content.

The problem with much of the content on the Web is that even dates are
hard-coded in unnatural ways. As oppose to XML, standardised metadata or
the like, dates are embedded as standard content, unlike LaTeX, for
instance.

-- Search terms in quotations with the wildcard character "*"
indicates two words NEAR each other: "lately * noticed." This type
of search is excellent for trend spotting.

What would be the intended practicality? Use tags in Technorati, for
example, to spot trends. Tagclouds come to mind too. They feeds on plenty
of fresh RSS'd (XML, hence time labelled) content.
Initial search queries in most search-engines recognize the wildcard character "*" within two keywords in quotations -- very-much like the Boolean NEAR; locating examples of keywords very close to each other. Same applies for current month, wildcard chacrater, & year. Search-engine results note "..." within text if keywords don't match month, any date, year.


Any considerations for applying NEAR search options in most
search-engines?
-- Search results are further narrowed-down by an astounding 80-90% by
excluding such words he, she, me. After all, content which may signal
emerging trends usually doesn't contain 'he, she, me.' Certain
pronouns usually indicate personal accounts of individuals; rather than
the "collective conscious" of people & businesses developing into
emerging trends.

-- Examples of links offer plenty of ideas for experimenting with
different combinations of keywords. To narrow-down searches further;
the addition of keywords mentioning specific industries, occupations,
businesses, people, places, culture, etc. can discern developing
trends.

There are many examples of keywords useful for trend-spotting. Five
examples:

-- Lately and noticed example.

<LONG URL>

-- Noticed lately is another variation.

<LONG URL> >

--'Lately and become' OR 'lately and becoming' can yield
"important developments" to watch.

<LONG URL> >

--'People have become' OR 'people are becoming' may infer
emerging developments from social points of view.

<LONG URL> >

--'Trend toward' AND 'becoming more' are one of the first
examples of keywords I developed for trend-watching.

<LONG URL> >

Entering in keywords which may infer content signaling the emerging
business & public zeitgeist yields a wide variety search results. In
quite a few cases, search results don't necessarily have value e.g.,
individual opinions which don't necessarily indicate emerging trends.
In some cases, search results yield specialty websites that are
fee-only and even restricted access content. Usually, content which may
be interpreted like "a crystal-ball of sorts" is free.

Any recommendations for marketing an "inference-like"
search-engine?

Thank-you

I like your direction of thoughts, but I think you must go farther than that
in order to make it viable or marketable. I am currently looking into
similar idea and may soon speak to one of the fathers of the semantic Web.
I truly believe it's where we all are headed.

Roy
--
Roy S. Schestowitz | Useless fact: Women blink twice as much as men
http://Schestowitz.com | SuSE Linux | PGP-Key: 74572E8E
3:45pm up 50 days 3:59, 3 users, load average: 0.13, 0.12, 0.09
http://iuron.com - next generation of search paradigms


Oct 14 '05 #7
The trends that are discerned through 'inferential scanning' relate to
how the natural social/economic zeitgest evolves, and not to some
'manufactured PR.

Oct 14 '05 #8
Good thing these posts are posting to 'search-engine forums.' Why did
GOOGLE Newsgroups repeat message #6 in message #8? The reply spaces can
display in two or three different variations, and the responses may be
posted (despite the preview option) at the wrong locations of
discussion threads? Why are the processes of posting responses become
less intuitive?

Oct 14 '05 #9
Noticedtrends wrote:
The trends that are discerned through 'inferential scanning' relate to
how the natural social/economic zeitgest evolves, and not to some
'manufactured PR.


Have you seen this article on inferential scanning?
http://if.psfk.com/when/archives/tre...f_content.html
....Your original post makes me think so.

I brought the PR stuff up just to make you aware that it is an easy
trap. It is hard enough for a human to differentiate hype from real
trends. Some PR people are very smart, and a great deal of their work
is promoting 'trends' that may or may not exist.

Looking for unintended wording as clues...
Sounds kind of like trying to turn software into a Freudian analyst --
Catch those pesky Floydian Ships, er.. Freudian Slips, or the near like.

The trouble I see with it is that any smart PR wonk is going to be
using phrases like 'lately' and 'noticed' in close relation in any so
called 'trend' she's trying to boost. She is likely to use 'people have
become' or 'trend toward' -- indeed any phrase that will make the reader
come to believe that a real trend is happening. It is one of the oldest
and most commonly used tricks in the PR book. Cola marketers,
Republicans, Democrats, candy manufacturers, medicines, you name it --
if they have PR people they are likely to be trying to convince you that
there are trends in their direction at hand.

What I need to know is how this 'inferential scanning' is going to
differentiate between public relations crocks and real trends. You say
it does, but nothing I have read answers the question.

How will it do so?
Oct 14 '05 #10

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