Dear Ferenc, (01)
I hate to do this to you again ... (believe me, I am not picking on you!) (02)
Referring to your post below ... (03)
I think "publishing" someone else's work hardly conforms to what one
would expect of a "member contribution." If you cite a few lines,
that's "fair use" ... if you provide a link to the document when
discussing it, that's what one might expect ... if you have the
authors permission to republish, you can do it elsewhere; Ontolog is
hardly the venue ... if you got this draft (in private, or say, as a
reviewer for a certain conference) for review, and you published this
openly without the permission of the author (or whoever entrusted you
to the review), that becomes an ethical issue at best; and is totally
violating our Contributing and IPR policies. (04)
Please observe our policies when contributing in the future. (05)
Thanks & regards. =ppy (06)
Peter Yim
Co-convener, ONTOLOG (07)
p.s. another friendly reminder ... I had suggested before, that it
would be best if one leaves a blank line between paragraphs and bullet
points. It will help make our archives more accessible to the
community. Please do it, if you can. Thanks. =ppy (08)
On 10/21/10, FERENC KOVACS <f.kovacs@xxxxxxxxxxxxxx> wrote:
> P.S. to my previous post:
>
> The bottom line on RELATIONS (AS VERBS) is
> that as a result of analysis involving "algebraic" operations you will get:
> 1) additive relations, such as parts and a whole, where interface is
> important
> when you do synthesis. Otherwise your chunking is not appropriate.
> 2) Productive relations, such as mental operations, including abstraction,
> isolation, formalization, etc. where nothing is dissected in reality, but
> new
> ideas are created all the time and where semantic primitives (objects,
> properties and relations) may be used to show the facet required in
> producing
> the related propositions. As the result of the synthsis you get back where
> you
> started from: Object - Existence/Non-existence, etc. The steps in this
> procedure
> may be numerically dentified so that you can find your way back. This does
> not
> look like a tree or a forest, but as a cycle, an infinite number of rings in
> SPACE and TIME as opposed to the mazes of knots in 2D
>
> By the way, I have just received a draft paper written still along the lines
> you
> tend to think about the subject
>
> If you are interested, contact the author as his paper is detached from
> here.
>
> ________________________________
>
> Hi,
>
> There goes a draft paper, comments are welcome!
>
>
> Semantic Data Aggregation through Semiotics
> Facilitating querying and inferencing
>
> Sebastián Samaruga
> http://xama.dev.java.net
> xama@xxxxxxxxxxxx
>
> Abstract
>
> Trying to fill the gap between real business (intelligence) domain
> applications
> and semantics through extensive data aggregation and a functional approach
> to
> knowledge representation through semiotics.
>
> Introduction
>
> Given Semiotics, and Semantics, which is a branch of Semiotics, regarding
> Peirce, along with Syntax / Grammar, and Pragmatics, the relationship arises
> that given three entities regarded as: Sign – Concept – Object, considering
> (Sowa[1]) “A sign has three aspects: it is (1) an entitythat represents (2)
> another entityto (3) an agent” that our underlying model can be composed of
> three classes, namely:
>
> * Type
> * Value
> * Name
>
> Given this basic 'units' of knowledge, we should model our data according to
> some rules so we can make useful things given this arrangement. The first
> step
> is to find a common 'meta – meta – model” for the model stated before so we
> can
> 'import' data from disparate sources into it. The data is ultimately
> aggregated
> into this three structures given meaningful parsing of it (and configuration
> files).
>
>
> Meta Meta Model
>
> The underlying common model for entities coming from diverse data sources
> should
> allow to covert from and to the 'model' easyly. Let's begin considering what
> a
> data structure could become after decomposing it a little. We should
> consider,
> for example, rows, or statements (from RDF), predicates or columns from a
> relational database and tables or types (rdf:Type) for example, from these
> two
> kind of data sources (RDBMs and RDF).
>
> Lets arrange them into objects of different classes. The name in the left is
> the
> name of the class, and the three value tuple named 'statements' is the
> arrangement of statements about other entities the object has:
>
> Mapping:
> Statements: <Context, Entity, Role>
> Entity:
> extends Mapping. Statements: <Context, Mapping, Role>
> Context:
> extends Entity, Statements: <Entity, Mapping, Role>
> Role:
> extends Context, Statements: <Context, Mapping, Entity>
>
> So, the Statements part is the references the object has to other objects in
> the
> data space, in the form of 3-tuples. The inheritance relationship is for
> allowing reification and further composition. The correspondences between
> these
> objects and a data source are roughly this:
>
> A Mapping represents a row (in a database table) or an RDF statement.
> An entity represents a value in a table cell or an RDF object.
> A context represents a table in a database or rdf:Type value of statement in
> RDF.
> A role represents a database column or a RDF predicate.
>
> The population of the model should allow for triadic relationships to be
> stated
> over the model, and to be accessible for querying in a meaningful way. (And
> the
> use of configuration mapping files for population of upper models)
>
> For example, in a Value x, let's say (200Km), we could 'operate'
> semiotically on
> it and 'ask' it for a reference to its related Type object, given a Name,
> let's
> say ('Distance'), and once we have the Type we arrived from the value,
> regarding
> it as that name, ask the Type object for a Value named ('Speed') and get
> (100Km/h). If we query using the same mechanism for a Value named ('Time')
> we
> should get (2h).
>
> Architecture
>
> The idea is building level over level based on mapping configurations files
> in
> XML that describe how entities in a lower level populates entities in an
> upper
> level. This should give us the layers of metametamodel (for data load),
> model
> (for inference, semantics) and later a business and agent layer to ease to
> provide user interface, reporting and interaction layers.
>
> The whole system should provide, through the use of accessory packages, such
> as
> a framework for FCA (FCA[2]) and information gathering and retrieval
> (Watson[3])
> for the build up of a kind of Business Intelligence (2.0) application
> framework,
> with dimensional and aggregated views of semantically integrated data.
>
> The project page of the ongoing development effort for this framework is
> online
> and available at: http://xama.dev.java.net
>
>
> References
>
> 1. JF Sowa,
> “Ontology, Metadata and Semiotics”
> http://users.bestweb.net/~sowa/peirce/ontometa.htm
>
> 2. Formal concept analysis:
> http://en.wikipedia.org/wiki/Formal_concept_analysis
>
> 3. Mark Watson ,
> “Practical Artificial Intelligence Programming With Java , Third Edition”
>
>
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