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Re: [ontolog-forum] Self Interest Ontology

To: "'[ontolog-forum] '" <ontolog-forum@xxxxxxxxxxxxxxxx>
Cc: corpora@xxxxxx, 'Eric Atwell' <E.S.Atwell@xxxxxxxxxxx>
From: "Rich Cooper" <rich@xxxxxxxxxxxxxxxxxxxxxx>
Date: Tue, 1 May 2012 19:52:01 -0700
Message-id: <556B45EAF49746BE9F203D8FF9F488E9@Gateway>

Please add the following comment from the Corpus Analysis list to the message from the Ontology Forum still further below and draw the obvious conclusions:


To evaluate a system for annotating dialogue acts, you could take a

Discourse Corpus where the text has been manually annotated with

discourse connectives and relations, apply your system to the same text,

and compare your system's analysis with the manual analysis. For example,

if you work with Arabic, you could try the Arabic Discourse Corpus

http://www.arabicdiscourse.net/ built by Leeds PhD student Amal Alsaif.


One problem you may find is that analyses are only directly comparable

if you use the same tag-set of discourse connectives and relations

  - eg for the Arabic Discourse Corpus, see

  http://www.arabicdiscourse.net/connectives/ and



I assume you want to evaluate accuracy; you might also want to

evaluate ease-of-use, portability, speed etc of your annotation tool,

and for this you could compare it to other annotation tools eg

Amal Alsaif's READ tool: http://www.arabicdiscourse.net/annotation-tool/



I hope this is useful


Eric Atwell, Leeds University



This seems to me to be consistent with the algorithm below that generates the Self Interest Ontology based on a sample corpus.  Therefore it should help researchers improve the designation of self interest in texts for various applications or further research on dialogues. 





Rich Cooper


Rich AT EnglishLogicKernel DOT com

9 4 9 \ 5 2 5 - 5 7 1 2

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Rich Cooper
Sent: Tuesday, May 01, 2012 7:32 PM
To: '[ontolog-forum] '
Subject: [ontolog-forum] Self Interest Ontology


The Wall Street Journal has a column called “the Law Blog” which could help create ontological theories about self interest based on observations in law.  The present issue is about patents, and the patent changes passed recently into law. 


There are also comments that reflect the self interest of the participants, which express self interest on various levels of evaluation, each subjective in construction. 


Does anyone have suggestions about how to describe self interest based on this use case?  Any suggestions or comments would be appreciated.  The link is at:




The evolution of law, in this example, patent law, could be traced from the early laws to the present, and the changes could also be informative about how law changes reflect the interests of the individuals.


The reason I bring this article up is described below.   


Perhaps a legal ontology could be created from this information by mining the text from that unifying point of view – each party chooses behaviors that reflect their individual self interest(s). 


Including self interest among the agents should help explore and eventually explain the way the data is restructured with English rules and facts, as well as algebraic and logical constraints.  That also makes it amenable to a discovery structure And/Or graph. 


The discovery structure And/Or graph provides an ordering of choices made by an ordering of agents.  The Solution Forest produced by the And/Or search algorithm is then available to be validated against a heuristic evaluation function.  Suppose the evaluation function is chosen from among the Solutions of the And/Or search algorithm. 


Validating the evidence would then be a process of choosing the most useful, or least risky, or most probable, or least fuzzy, or top ROI choice of solution subtree from the solution forest in the search. 


If I am not making this clear, think of the evaluation function in an And/Or search which uses a comparison between alternative solution subtrees stored as a forest of trees within the And/Or graph. 


An evaluation of a filler for a role among candidate fillers can organize the process by the preferred choice, so that the choices are ordered (“become primary key indexes” if you prefer database terminology) and the enumeration of the valuation or arrival order becomes the primary key for new columns that can describe the various properties of the enumerated objects.  Once the primary key has been constructed, the arrival order of each choice is already available, and therefore could provide this key. 


The And/Or graph in this example establishes meaning from the various indexes, i.e., object enumerations.  The Self Interest Ontology generated by this process is represented by the resulting And/Or graph, the extra columns associated with objects, relationships, rules and other representations (TBD) are encoded as nodes and arcs in the And/Or graph and the associated And/Or solution subtrees. 


Iterating this algorithmic process will lead the individual agent to automatically organize a corpus of documents.  Enumerating the iterations leads in turn to a recursion of evaluation for newly discovered columns to reflect objects, such as choices, or whatever substructures can be found through the And/Or search forest. 


Thanks for any contributions; I am seeking comments, critiques or suggestions – pick your appellation. 





Rich Cooper


Rich AT EnglishLogicKernel DOT com

9 4 9 \ 5 2 5 - 5 7 1 2


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