Content Representation With A Twist

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.

Friday, February 24, 2006

Usability problem in the widespread 'is a' approach

As introduced earlier, taxonomies as thesauri and classifications organize terms in a net similar to a tree. Hierarchically, the terms get ordered mainly by is a relationships, seldom by has a ones. Also there are relationships between terms that have "something" to do with each other, but cannot be ordered validly hierarchically. Like bird and bird cage. Some taxonomies force one parent term per node, i.e. a structure that easily can be identified as being mainly a tree, with exception of some cross reference like associative relationships. Other taxonomies don't force the one parent per term rule, so that such a one might easily look more like a net but like a tree. The prior ones are called "mono-hierarchical", while the latters' label is "poly-hierarchical".

What's the problem?

Taxonomies don't do anything more but relating the terms to other terms. The task to define the terms they leave to dictionaries.

This presupposition requires that the one who's using a taxonomy already is a kind of an expert in the field organized by the taxonomy. If you're looking for a term you don't know where to look up, you're lost.

Say, some part fell from your car, and since then it doesn't move anymore. You don't know the term for that part, and the very one is too heavy, so you cannot just take it to the garage. -- Because of its primary is a nature, a taxonomy is of no use here for you. Another chance is to go to the garage without the part and attempt to explain the nature of it to a worker there. (So far, my university information science teacher guided me.)

So, the problem of a taxonomy is that it doesn't support the most straight ahead approach to identify an item -- to select the most conspicuous properties of the item the taxonomy -- broader: knowledge storage, e.g. a garage worker's memory -- already knows about.<<


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.

Thursday, February 23, 2006

From the Information Science local point of view (upgraded)

Information Science and its predecessor sciences like documentation or library science tackle one big problem in information: stay able to retrieve pieces of information once stored.

In ancient days the pieces of information mainly were material, i.e. not computer-indexable. For example, books were such a kind of material.

Common approach from the information science point of view is to assign each of the books with a set of keywords: When you want to retrieve one of them later, you go ahead, choose some of the keywords, and lookup them in a catalogue which itself refers to the books
theirselves.

To be able to handle this all, you need at least three kinds of storage:
  1. a storage for the books, e.g. a kind of library, organized in a way to stay able to at least locate the shelf a particular book is placed in
  2. a storage for the catalogue
  3. and, most important: a storage for the keywords.
The keywords theirselves have to be stored somewhere. If you neglect this part of the task, one day you will apply this keyword to the book and another day another keyword, but both meaning the same -- i.e. being synonyms.

So, what result originates from that?

Assumed you associated two books X and Y very similar in content with two synonymous but different keywords, A and B. One day you want to know something about a topic that is covered by both books X and Y, but you don't know about that. You directly go to the catalogue. You pick up a search keyword that accidently fell into your mind. Say B.
You look up the appropriate catalogue card and find Y. -- That there is a closely related X book you don't even get aware of. So you fetch the Y book, but the X book remains in shelf. Possibly it would have been valuable to find X as well.


Therefore keywords get stored theirselves too.

The main goal of a keyword storage is similar to the other pieces of information storages: To stay able to find the wanted contents, i.e. the keywords -- and to find exactly the keywords wanted. "Keywords wanted" are those that might be applied to one or more books.

The appropriate tool for keyword or, more precisely, term (as in "search term") storage is a terminology. It mentions every word that was applied to at least one piece of information -- e.g. book -- of the pieces of information storage -- e.g. library. (In a converse, to keep administrative work load small, there's the suggest to choose only keywords already listed in the terminology, to associate books with.)

In a simple case, a terminology might be an alphabetical list of terms. Even better a taxonomy is: For each of the terms it offers an orientation help: Usually there are broader and narrower variants of terms: a mammal is treated to be broader than a dog or cat or cow or horse or something else which is a mammal. (In fact, taxonomies refer to items but list the labels of the items. Taxonomies are closely related to ontologies.)

So, a taxonomy offers is a relationships to identify the location of a given term in the whole taxonomy. Less common than is a are has a relationships, like the ones applied between car and something like wheels, motor, front window, doors etc. Both of these relationships are called hierarchical relationships.

My diploma thesis was about the thesaurus kind of taxonomy, so I currently I am not sure if this applies for the classification kind as well: There is at least one more kind of relationship -- the associative one. It relates terms at each other that don't belong to a hierarchical order, but somehow have something to do with each other, like bird and bird cage. (Admittedly, they might be related using a has a relationship, but I never came across such an assignment.)

Synonyms in taxonomies get treated a special way

Synonyms in taxonomies get treated a special way: They get collected to a single class. Each of the items of that class is (/treated to be, compare to administrators' cheats above) synonymous with every other item of the class.

In classifications there are just classes related to each other, being representative for the terms belonging to the class. In thesauri there are no such classes. During thesaurus creation sets of synonymous terms get identified. One "most significant/common" term gets chosen to be the term representative for all the other synonyms. This "most significant/common" one is called "descriptor", while the others become non-descriptors.

Why all the fuss about the synonym details?

If you look up a synonym you get redirected to the class or descriptor the synonym belongs to. None of the books/other pieces of information ever gets keyworded by a synonym. That solves the problem of searching the X and Y books mentioned above one day by the A and another day by the B search term: Either A points
to B or B to A or both to a third term, say C. And both the books are associated by the "most significant/common" term, e.g. C. So, either if you chose A or B as your search term, you always find all the relevant pieces of information/books, e.g. X and Y.


So far the common part of terminologies.


But there is a usability problem in the widespread is a approach.<<

Glossary

  • to retrieve
    • to find again
  • class
    • a set of synonymous words
  • synonym
    • a word meaning the same as another word
    • sometimes there is a difference between them both, but the one applying them doesn't notice
    • terminology administrators sometimes think it is not worth the effort to keep "very similar" terms distinct, so they merge them into a single class by claiming the very words were synonyms
  • catalogue card
    • associations between keywords are stored on catalogue cards which, as a whole, make up the catalogue itself



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.

Saturday, February 18, 2006

From the Information Science local point of view

Information Science and its predecessor sciences like documentation or library science tackle one big problem in information: stay able to retrieve pieces of information once stored.

In ancient days the pieces of information mainly were material, i.e. not computer-indexable. For example, books were such a kind of material.

Common approach from the information science point of view is to associate each of the books with a set of keywords: When you want to retrieve one of them later, you go ahead, choose some of the keywords, and lookup them in a catalogue which itself refers to the books itself.

To be able to handle this all, you need at least three kinds of storage:
  1. a storage for the books, e.g. a kind of library, organized in a way to stay able to at least locate the shelf a particular book is placed in
  2. a storage for the catalogue
  3. and, most important: a storage for the keywords.
The keywords theirselves have to be stored somewhere. If you neglect this part of the task, one day you will apply this keyword to the book and another day another keyword, but both meaning the same -- i.e. are synonyms.

So, what result originates from that?

Assumed you associated two contently very similar books X and Y with two synonymuos but different keywords, A and B. One day you want to know something about a topic that is covered by both books X and Y, but you don't know about that. You directly go to the catalogue. You pick up a search keyword that accidently fell into your mind. Say B. You look up the appropriate catalogue card and find Y. -- That there's a closely related X book you don't even get aware of. So you fetch the Y book, but the X book remains in shelf. Possibly it would have been valuable to find X as well.

Therefore keywords get stored theirselves too.


The main goal of a keyword storage is similar to the other pieces of information storages: To stay able to find the wanted contents, i.e. the keywords -- and to find exactly the keywords wanted. "Keywords wanted" are those that might be applied to one or more books.

The appropriate tool for keyword or, more precisely, term (as in "search term") storage is a terminology. It mentions every word that was applied to at least one piece of information -- e.g. book -- of the pieces of information storage -- e.g. library. (In a converse, to keep administrative workload small, there's the suggest to choose only keywords already listed in the terminology, to associate books with.)


In a simple case, a terminology might be an alphabetical list of terms. For each of the terms it offers an orientation help: Usually there are broader and narrower variants of terms: a mammal is treated to be broader than a dog or cat or cow or horse or something else which is a mammal. (In fact, terminologies refer to items but list the labels of these.)

So, a terminology offers is a relationships to identify the location of a given term in the whole terminology. Less common than is a are has a relationships, like the ones applied between car and something like wheels, motor, front window, doors etc. These kinds of relationships are called hierarchical relationships.

My diploma thesis was about the thesaurus kind of terminology, so I currently I am not sure if this applies for the classification kind as well: There is at least one more kind of relationship -- the associative one. It relates terms at each other that don't belong to a hierarchical order, but somehow have something to do with each other, like bird and bird cage. (Admittedly, they might be related using a has a relationship, but I never came across such an assignment.)

Synonyms in terminologies get treated a special way


Synonyms in terminologies get treated a special way: They get collected to a single class. Each of the items of that class is (/treated to be, compare to administrators' cheats above) synonymuos with each other item of the class.

In terminologies called classification there just classes related to each other, being representative for the terms belonging to the class. In thesaurus kind of terminologies there are no such classes. During thesaurus development a sets of synonymous terms get identified. One "most significant/common" term gets chosen to be the term representatively for all the other synonyms. This "most significant/common" one is called "descriptor", while the others become non-descriptors.

Why all the fuss about the synonym details?


If you lookup a synonym you get redirected to the class or descriptor the synonym belongs to. None of the books/other pieces of information ever gets keyworded by a synonym.

That solves the problem of searching the X and Y books mentioned above one day by the and another day by the B search term: Either A points to B or B to A or both to a third term, say C. And both the books are associated by the "most significant/common" term, e.g. C. So, either if you chose A or B as your search term, you always find all the relevant pieces of information/books, e.g. X and Y.

So far the common part of terminologies.

But there is a usability problem in the widespread is a approach.

Glossary


to retrieve - to find again

class - a set of synonymous words

catalogue card - associations between keywords are stored on catalogue cards which, as a whole, make up the catalogue itself

synonym - a word meaning the same as another word
  • sometimes there is a difference between them both, but the one applying them doesn't notice
  • taxonomy administrators sometimes think it is not worth the effort to keep "very similar" terms distinct, so they merge them into a single class by claiming the very words were synonyms



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.

guide lines for this blog

I am going to guide you to the interesting points of the Model of Meaning matter. Therefore I keep the introduction easily comprehensible, but nevertheless complete, so that after reading it you'll have the complete understanding to discuss the model qualifiedly.<<



Updates: 20070624: Tagged the posting. Removed my workaround for backlinks blogger.com didn't support in earlier times. Now, backlings are there, therefore the bypass can be dropped.

Friday, February 10, 2006

"ia: organizing notions" now removed

Prior blog "ia: organizing notions" now removed. All links there should be dead by now.<<



Updates: 20070624: Tagged the posting. Removed my workaround for backlinks blogger.com didn't support in earlier times. Now, backlings are there, therefore the bypass can be dropped.
ia: organizing notions has been merged into this blog now<<



Updates: 20070624: Tagged the posting.

init

just initiated this blog, now merging the prior ia: organizing notions here. It was described the following way
A blog upon my approach on organizing notions/concepts/ideas. As far as I know, this is a topic as well on information architecture.
where notions was exactly misleading. A wrong hint someone told me without considering the whole matter I am working on.



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.


[Merged from (the now removed) ia: organizing notions:] I've been working on this topic for a long time, so now I want to get it clear, reliably substantiated and prepared to get it discussed. I've taken several attempts to create a united blog for it, like knowledge, knowledge.meta and find using notions (partitially English--partitially German).

I wasn't resolutely to in fact publish it while working on it--but I am working on it yet such a long time, I am sure I cannot expect to finish it in the near future. And also, I have not anymore that lot of time to work on it as I had when I was a student. I made the mental step to be willing to let a potential employer get its hands on it (well, in fact, if the employer is a cute search engine provider), so it doesn't hurt anymore to publish it while it is not yet finished.

The place for that shall be here. Well, I'm going to rename the URL of this blog soon, but there the description of the model shall happen, and any discussion on it, too.<<



Updates: 20070624: Tagged the posting. Removed my workaround for backlinks blogger.com didn't support in earlier times. Now, backlings are there, therefore the bypass can be dropped.