Objective
Common quality of today's information technology, in an aim to become able to identify items, is to mark up every single item. – The Model of Meaning heads to build the foundation to manage-without any such markup.
The approach is about content representation in the literal sense of the term.
Updates: none so far
Showing posts with label content representation. Show all posts
Showing posts with label content representation. Show all posts
Monday, August 20, 2007
Friday, July 13, 2007
wanted: tag cloud for the other pages mentioning the term "content representation"
I'd like to learn what all these 91,900 search results related to content representation might be about. (Curiously, I wonder where I left the article directly pointing to that search result -- when it still were 88,900 "only".)
To learn that quickly, first I need to decide whether to see the pages manually or "mechanically". Then, I'd need to learn how to use the Google API to quickly get all the hits -- which actually end by page 78 which in fact is not 90 thousand plus search results but only a "small" number of only 788 hits.
However, since I'd like to redo this search every now and then again, and as I might like to do the search for sites like Cite Seer as well, it might be worth the effort to develop a small program which helps me in determining the content of all the pages. -- A tag cloud and toying around with precision and recall might contribute a bit to the visualized cloud. -- The cloud terms' sizes could visualize quantity in recall, while the precision might get indicated by color incoding, e.g. blue .. green .. yellow .. orange .. red, like on maps, where high precision might get indicated by red and low precision by blue.
There's a tag cloud generator available in Debian's share of Perl libraries. I already modified it, and it's available on demand. -- However, I'd prefer to have any place in the web to put my version to. Any repository out there for that library?
Updates: none so far
To learn that quickly, first I need to decide whether to see the pages manually or "mechanically". Then, I'd need to learn how to use the Google API to quickly get all the hits -- which actually end by page 78 which in fact is not 90 thousand plus search results but only a "small" number of only 788 hits.
However, since I'd like to redo this search every now and then again, and as I might like to do the search for sites like Cite Seer as well, it might be worth the effort to develop a small program which helps me in determining the content of all the pages. -- A tag cloud and toying around with precision and recall might contribute a bit to the visualized cloud. -- The cloud terms' sizes could visualize quantity in recall, while the precision might get indicated by color incoding, e.g. blue .. green .. yellow .. orange .. red, like on maps, where high precision might get indicated by red and low precision by blue.
There's a tag cloud generator available in Debian's share of Perl libraries. I already modified it, and it's available on demand. -- However, I'd prefer to have any place in the web to put my version to. Any repository out there for that library?
Updates: none so far
Friday, June 22, 2007
Homework to do
My yesterday findings result in a lot of homework to do.
First of all, as a left-over of a former post I have to make clear what a MOM net is, what it stores and how it does so. The recent posting on the issue about finding a heater repair part by using a thesaurus is a first step there.
Second, Chris Chatham's posting on differences between brain and computers I reviewed. But I missed that there's a lot of reader comments I didn't read yet. A to do. Also the insight 'content representation' still seems to refer to marking up content by key words or thesaurus terms demands to make clear my point of view on that topic, and why I chose the term content representation rather than any other. And, in turn, what I refer to by "marking up content by key words" demands for a explanation. Things to do.
Third, what I already begun, is to tidy up the blog. I think posting might be much more useful if sudden readers can dive in at any point, without needing to know what I wrote about before. Therefore, from now on, key concepts shall be cleared tersely (hence the heater posting) by separate postings. And any new postings referring to these concepts shall do point there instead of going into detail every new posting -- which might disturb too much -- you as well as myself, when developing a thought.
Let`s see how it works out.
Updates: none so far
First of all, as a left-over of a former post I have to make clear what a MOM net is, what it stores and how it does so. The recent posting on the issue about finding a heater repair part by using a thesaurus is a first step there.
Second, Chris Chatham's posting on differences between brain and computers I reviewed. But I missed that there's a lot of reader comments I didn't read yet. A to do. Also the insight 'content representation' still seems to refer to marking up content by key words or thesaurus terms demands to make clear my point of view on that topic, and why I chose the term content representation rather than any other. And, in turn, what I refer to by "marking up content by key words" demands for a explanation. Things to do.
Third, what I already begun, is to tidy up the blog. I think posting might be much more useful if sudden readers can dive in at any point, without needing to know what I wrote about before. Therefore, from now on, key concepts shall be cleared tersely (hence the heater posting) by separate postings. And any new postings referring to these concepts shall do point there instead of going into detail every new posting -- which might disturb too much -- you as well as myself, when developing a thought.
Let`s see how it works out.
Updates: none so far
Some articles on content representation
Since nearing the first mile stone of MOM SSC, I thought, it might make some sense to connect to others occupied with content representation. I technoratied for "content representation" (including the quotation marks) and found several postings aparently totally irrelated to content representation. Also, today "content representation" seems to primarily mean "mark up", e.g. by terms provided by a thesaurus or the like. However, I found one attracting me, pointing to another one which in turn pointed me to 10 Important Differences Between Brains and Computers by Chris Chatham, posted on March 27, 2007.
Number one of his list of differences is nothing new -- "Brains are analogue; computers are digital", therefore skipped.
Number two reveals a new buzz word for describing MOM, "content-addressable memory", and it describes it as follows: "the brain uses content-addressable memory, such that information can be accessed in memory through " [...] spreading activation" from closely related concepts. [...]" When I read it first, I thought, oh, there might be someone with a similar concept in mind like MOM. On the second look, I realized, that claim likely originates just from psychology. The review continues the above quote by "For example, thinking of the word 'fox' may automatically spread activation [...]" which points a bit into neurology. I wonder who that claim "thinking of a word" or "thinking of a fox" or even "thinking of the word 'fox'" can be proven to spin off activation. I mean, that would imply someone proved "the word 'fox'" and a neuron equal, since the neuron is that instance sending activation to other neurons. -- However, I share that opinion, the one a neuron represents an item, but I am just not aware of a proof for that. If you have such a one at hand, I'd be really glad if you could hint me to the source. (Just since it'd support my own claims.)
Aside, I don't share the idea thinking of a word might immediately stimulate "memories related to other clever animals" [as my source, the above linked article, continues] related content. I think, at least it needs to think of the fox itself instead of just the word "fox". And, to finish the quoted sentence, it ends in "fox-hunting horseback riders, or attractive members of the opposite sex."
Back to MOM, taking "content-addressable memory" as a label for it, actually is chosen accordingly: Chris Chatham continues his second difference with a "The end result is that your brain has a kind of 'built-in Google,' in which just a few cues (key words) are enough to cause a full memory to be retrieved." Well, that's exactly what MOM is after: To pick up matching "memories" by just a few cues. -- The way Chris Chatham is describing the issue is pretty close to the original issue that led me to figuring out MOM: A guy who got his heater damaged who must find the spare part by utilizing a thesaurus. The thesaurus mostly consists of abstraction relationships between item names listed there. And rather often, there is no definition for the items provided -- thesaurus makers seem to presume you're a specialist on that field of topic or you wouldn't make use of a thesaurus at all. However, restricted to that tool, if that tool is restricted to abstraction relationships mainly, you cannot find the part you need to repair the heater. But what if you'd remove all the is a (i.e. abstraction) relationships and set up a "kind of thesaurus" consisting of has a relationships only? -- That way, you'd find the spare part as quickly as your in-mind "Google" might do. At least if you've got another tool at hand that jumps you over all the crap of temporarily unnecessary details, like the knowledge that -- let's switch the example to a pet cat -- the four feet, torso, tail, neck and head that belong to the cat also belong to any quadruped animal. Such as a pet dog, or also a pet hamster.
With differences #3–#9 I were familiar with respectively became clear to me over the time I developed the Model of Meaning, e.g. the claim provided by "Difference # 6: No hardware/software distinction can be made with respect to the brain or mind". That's rather clear, but I am not going to explain it here, since this posting is just a note to me (and anyone who might be interested), that there is a posting around which by content is close to MOM.
Difference #10, on the first glance looked unfamiliar to me -- "Brains have bodies" --, but although I wasn't aware of those change blindness findings "that our visual memories are actually quite sparse" quickly brought me back to what I already know (well, strongly believe; I lack the laboratories to proove my theoretic findings by scissoring mice). It's rather clear that "the brain is 'offloading' its memory requirements to the environment in which it exists: why bother remembering the location of objects when a quick glance will suffice?"
Updates: none so far
Number one of his list of differences is nothing new -- "Brains are analogue; computers are digital", therefore skipped.
Number two reveals a new buzz word for describing MOM, "content-addressable memory", and it describes it as follows: "the brain uses content-addressable memory, such that information can be accessed in memory through " [...] spreading activation" from closely related concepts. [...]" When I read it first, I thought, oh, there might be someone with a similar concept in mind like MOM. On the second look, I realized, that claim likely originates just from psychology. The review continues the above quote by "For example, thinking of the word 'fox' may automatically spread activation [...]" which points a bit into neurology. I wonder who that claim "thinking of a word" or "thinking of a fox" or even "thinking of the word 'fox'" can be proven to spin off activation. I mean, that would imply someone proved "the word 'fox'" and a neuron equal, since the neuron is that instance sending activation to other neurons. -- However, I share that opinion, the one a neuron represents an item, but I am just not aware of a proof for that. If you have such a one at hand, I'd be really glad if you could hint me to the source. (Just since it'd support my own claims.)
Aside, I don't share the idea thinking of a word might immediately stimulate "memories related to other clever animals" [as my source, the above linked article, continues] related content. I think, at least it needs to think of the fox itself instead of just the word "fox". And, to finish the quoted sentence, it ends in "fox-hunting horseback riders, or attractive members of the opposite sex."
Back to MOM, taking "content-addressable memory" as a label for it, actually is chosen accordingly: Chris Chatham continues his second difference with a "The end result is that your brain has a kind of 'built-in Google,' in which just a few cues (key words) are enough to cause a full memory to be retrieved." Well, that's exactly what MOM is after: To pick up matching "memories" by just a few cues. -- The way Chris Chatham is describing the issue is pretty close to the original issue that led me to figuring out MOM: A guy who got his heater damaged who must find the spare part by utilizing a thesaurus. The thesaurus mostly consists of abstraction relationships between item names listed there. And rather often, there is no definition for the items provided -- thesaurus makers seem to presume you're a specialist on that field of topic or you wouldn't make use of a thesaurus at all. However, restricted to that tool, if that tool is restricted to abstraction relationships mainly, you cannot find the part you need to repair the heater. But what if you'd remove all the is a (i.e. abstraction) relationships and set up a "kind of thesaurus" consisting of has a relationships only? -- That way, you'd find the spare part as quickly as your in-mind "Google" might do. At least if you've got another tool at hand that jumps you over all the crap of temporarily unnecessary details, like the knowledge that -- let's switch the example to a pet cat -- the four feet, torso, tail, neck and head that belong to the cat also belong to any quadruped animal. Such as a pet dog, or also a pet hamster.
With differences #3–#9 I were familiar with respectively became clear to me over the time I developed the Model of Meaning, e.g. the claim provided by "Difference # 6: No hardware/software distinction can be made with respect to the brain or mind". That's rather clear, but I am not going to explain it here, since this posting is just a note to me (and anyone who might be interested), that there is a posting around which by content is close to MOM.
Difference #10, on the first glance looked unfamiliar to me -- "Brains have bodies" --, but although I wasn't aware of those change blindness findings "that our visual memories are actually quite sparse" quickly brought me back to what I already know (well, strongly believe; I lack the laboratories to proove my theoretic findings by scissoring mice). It's rather clear that "the brain is 'offloading' its memory requirements to the environment in which it exists: why bother remembering the location of objects when a quick glance will suffice?"
Updates: none so far
Saturday, February 25, 2006
Approach from Tagging
ontology
Ontology is a form of classification which may be thought of as "conceptual" relationships. Whereas in a taxonomy terms may be classified together as "fruit", in an ontology the conceptual relationship may be "fruit which are used in pies" or "growing fruit for sale". Ontological relationships are inherently self-describing. Ontologies are the backbone of the semantic web, as they provide multiple links to data and therefore can support search and insightful navigation. — Source
Problem, I see: The meaning of "fruit which are used in pies" is not accessible to the machine. The machine depends on this kind of "knowledge" given to it, cannot exceed the borders resulting from that kind of knowledge. For short: The machine is unable to determine by itself whether or not a given item belongs to a "fruit which are used in pies" relationship, if nowhere is stated that this is the case. Same for different kinds of thesaurus relationships ("broader term", "narrower term", etc.), which I originally criticised.
I avoided to touch the semantic web attempt, since I feared such a kind of approach. Now, when I had to look up taxonomy, classification, terminology, etc. to avoid to mess them up, I came across the above statement, that the semantic web in fact approaches this way. Sad.
In my opinion, a machine needs a way, to get competence to decide. Knowledge to make the decision on. Knowledge on knowledge. Knowledge on knowledge to get able to verify its own knowledge. As long as there are parts of the machine's knowledge the machine cannot access, it hasn't got a chance to get independent of external minds, e.g. humans.
I don't think that the best approach to achieve that goal is to stack more and more complexity/abstraction layers on the already not-working attempts. Instead, I think, it is necessary to determine a way to make most basic knowledge accessible to the machine, in a way that the machine doesn't have to depend on externally given knowledge. I think, that if that basic goal is achieved, more complex kinds of content/knowledge can be built atop.<<
Updates: 20070624: Tagged the posting. Updated the posting style (layout) to my current style, such as using blockquotes when appropriate, more precise word picks, better grammar.
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