Structuring Aspects 2
The readers of Structuring Aspects 1 had a misunderstanding of what it was written for. I suspect that a similar one will come out with the second series. Therefore, I will clarify that in the process of writing a coherent text explaining some presumable start-up, certain things had to be written in relatively detail, so that they occupy pages instead of a paragraph-other. But since Internet readers in general and Habra in particular do not like long texts, this also needs to be considered. As a result, I chose from two evils and designed the overgrown places with two separate notes, which summarized my attempts to collect, comprehend and comment on or supplement the existing ones in relation to the subject of structuring.
Regarding the structuring of knowledge, a hierarchical classification approach that goes back to Aristotle, is almost the only taxonomy . In any case, completely dominant. For example, folders are organized in Windows. This is convenient, especially when combined with the hierarchy visualization. The disadvantage is that the hierarchy can be built only by any one criterion or attribute, whereas its elements usually have a number of attributes, according to which they can be built into different hierarchies or combined into different sets. For example, the same music files can be systematized by genre, artist, period of creation, and more. But if you want to have hierarchies for all these criteria, you will have to stupidly copy files, taking up space in memory.
About the alternative method - facet classification , probably, not everyone heard. Not to mention the fact that it is far from being as intuitive as hierarchical classifications. However, a big plus of this method is undoubted, since the problem noted above is solved - the same objects can belong to different hierarchies or sets simultaneously.
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Judging by the article in Wikipedia , this list of conceptual approaches is completely exhausted. It would seem that these things should relate to gnoseology / epistemology (the science of knowledge) or cognitive science , but this is not spelled out clearly. In any case, I was not able to find (sub) a section of knowledge, devoted in general to the problems of classifications and knowledge structuring. As I understand it, epistemology focuses on several other things, and cognitive science does not focus on structuring problems in terms of applicability especially for people, human perception. People are studied in terms of building models of memory and thinking, but not with the goal of deriving general structuring principles, on the basis of which people could most adequately and easily perceive knowledge or operate on them, but with the aim of using these models in artificial intelligence. In addition, the question can be raised not only about the ease of perception. For example, the possibility of alternatives mentioned above without duplicating content may be important not only in terms of saving memory, but also in terms of social interactions in the general wiki space. The absence of a specialized section devoted to structuring is rather strange, given its universal role in society (as I wrote about in the first article ), as well as the practical value of such knowledge for Internet services.
Here, at the junction of human and machine, in the mentioned area of artificial intelligence there is a rather developed section of knowledge representation (see also knowledge engineering ), largely related to the problems of structuring. For example, within its framework there is the concept of semantic networks . The latter, as well as classification hierarchies, are representable as a directed graph. Those. these things could be studied on a general basis, again, if this subject were formulated as an independent section of knowledge.
Separately from all of this, a method of structuring information such as supplying content objects with tags has become widely used on the Internet. The object thus actually belongs simultaneously to so many sets, how many different labels are assigned to it. A good way, while the structured space is not too large and / or not too heterogeneous. For example, it’s hard to imagine a reasonable tag cloud for Wikipedia. However, even books are written about this — Tagging: Peaple Powered Metadata for the Social Web (which I have not read. See also the folksonomy link). Judging by the name, the author understands tags as metadata.
The latter is slightly at odds with what is often called metadata, for example, in the concept of the Semantic Web . There is data about data, brief standardized descriptions of web resources, and standardized for the convenience of operating machines, not people. Although the topic of a generalized understanding of metadata notes that if you move away from rigid standardization, to be closer to human perception, the difference between data and metadata will become conditional and relative - the same content, depending on context, can serve both data and metadata. It is not noted that the role of metadata can carry links between objects. For example, in hierarchical (tree-like) structures of communication between objects, by default they go from the general to the particular (or vice versa, this is not important). It is important that such a link contains certain information about the objects to be linked. If we take the semantic structures, then the total set of different relationships-relationships for a given object can quite exhaustively describe it. This is one of the main ideas of the startup, which I plan to write about.
Regarding the structuring of knowledge, a hierarchical classification approach that goes back to Aristotle, is almost the only taxonomy . In any case, completely dominant. For example, folders are organized in Windows. This is convenient, especially when combined with the hierarchy visualization. The disadvantage is that the hierarchy can be built only by any one criterion or attribute, whereas its elements usually have a number of attributes, according to which they can be built into different hierarchies or combined into different sets. For example, the same music files can be systematized by genre, artist, period of creation, and more. But if you want to have hierarchies for all these criteria, you will have to stupidly copy files, taking up space in memory.
About the alternative method - facet classification , probably, not everyone heard. Not to mention the fact that it is far from being as intuitive as hierarchical classifications. However, a big plus of this method is undoubted, since the problem noted above is solved - the same objects can belong to different hierarchies or sets simultaneously.
')
Judging by the article in Wikipedia , this list of conceptual approaches is completely exhausted. It would seem that these things should relate to gnoseology / epistemology (the science of knowledge) or cognitive science , but this is not spelled out clearly. In any case, I was not able to find (sub) a section of knowledge, devoted in general to the problems of classifications and knowledge structuring. As I understand it, epistemology focuses on several other things, and cognitive science does not focus on structuring problems in terms of applicability especially for people, human perception. People are studied in terms of building models of memory and thinking, but not with the goal of deriving general structuring principles, on the basis of which people could most adequately and easily perceive knowledge or operate on them, but with the aim of using these models in artificial intelligence. In addition, the question can be raised not only about the ease of perception. For example, the possibility of alternatives mentioned above without duplicating content may be important not only in terms of saving memory, but also in terms of social interactions in the general wiki space. The absence of a specialized section devoted to structuring is rather strange, given its universal role in society (as I wrote about in the first article ), as well as the practical value of such knowledge for Internet services.
Here, at the junction of human and machine, in the mentioned area of artificial intelligence there is a rather developed section of knowledge representation (see also knowledge engineering ), largely related to the problems of structuring. For example, within its framework there is the concept of semantic networks . The latter, as well as classification hierarchies, are representable as a directed graph. Those. these things could be studied on a general basis, again, if this subject were formulated as an independent section of knowledge.
Separately from all of this, a method of structuring information such as supplying content objects with tags has become widely used on the Internet. The object thus actually belongs simultaneously to so many sets, how many different labels are assigned to it. A good way, while the structured space is not too large and / or not too heterogeneous. For example, it’s hard to imagine a reasonable tag cloud for Wikipedia. However, even books are written about this — Tagging: Peaple Powered Metadata for the Social Web (which I have not read. See also the folksonomy link). Judging by the name, the author understands tags as metadata.
The latter is slightly at odds with what is often called metadata, for example, in the concept of the Semantic Web . There is data about data, brief standardized descriptions of web resources, and standardized for the convenience of operating machines, not people. Although the topic of a generalized understanding of metadata notes that if you move away from rigid standardization, to be closer to human perception, the difference between data and metadata will become conditional and relative - the same content, depending on context, can serve both data and metadata. It is not noted that the role of metadata can carry links between objects. For example, in hierarchical (tree-like) structures of communication between objects, by default they go from the general to the particular (or vice versa, this is not important). It is important that such a link contains certain information about the objects to be linked. If we take the semantic structures, then the total set of different relationships-relationships for a given object can quite exhaustively describe it. This is one of the main ideas of the startup, which I plan to write about.
Source: https://habr.com/ru/post/84507/
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