Page 230 - Artificial Intelligence for the Internet of Everything

Accessing Validity of Argumentation of Agents of the Internet of Everything 211

(Galitsky et al., 2015). Comparing the bottom two rows, we observe that it is
possible, but infrequent, to express an affective argument without CAs.
Assessing logical arguments extracted from text, we were interested in
cases where an author provides invalid, inconsistent, self-contradicting cases.
That is important for CRM systems focused on customer retention and facil-
itating communication with a customer (Galitsky et al., 2009). The domain
of residential real estate complaints was selected and a DeLP thesaurus was
built for this domain. An automated complaint-processing system can be
essential, for example, for property-management companies in their
decision-support procedures (Constantinos, Sarmaniotis, & Stafyla, 2003).
In our validity assessment, we focus on target features (claims) related to
how a given complaint needs to be handled, such as compensation_required,
proceed_with_eviction, rent_receipt, and others. A system decision is determined
by whether the claim is validated or not: if it is validated, then the decision
support system demands compensation, and if not validated, it decides that
compensation should not be demanded (for the compensation_required claim).
Validity assessment results are shown in Table 11.3. These results are
computed together for the detection and validation steps. In the first and
second rows, we show the results of the simplest complaint with a single rhe-
toric relation such as contrast with a single CA indicating an extracted argu-
mentation attack relation respectively. In the third row we assess complaints
of average complexity, and in the bottom row, the most complex, longer
complaints in terms of their CDTs are given. The third column shows detec-
tion accuracy for invalid argumentation in complaints in a stand-alone argu-
ment validation system. Finally, the fourth column shows the accuracy of the
integrated argumentation extraction and validation system.
In these results recall is low because in the majority of cases the invalidity
of claims is due to factors other than being self-defeated. Precision is

Table 11.3 Evaluation results for argument validation
F1of F1 of
Types of complaints P R validation total

Single rhetoric relation of type contrast 87.3 15.6 26.5 18.7
Single communicative action of type 85.2 18.4 30.3 24.8
disagree
Two or three specific relations or 80.2 20.6 32.8 25.4
communicative actions
Four and above specific relations or 86.3 16.5 27.7 21.7
communicative actions