We introduce a search engine and information retrieval system for providing access to opinion data. Natural language technology of generalization of syntactic parse trees is introduced as a similarity measure between subjects of textual opinions to link them on the fly. Information extraction algorithm for automatic summarization of web pages in the format of Google sponsored links is presented. We outline the usability of the implemented system, integrated opinion delivery environment (IODE).

This paper intends to demonstrate how Applicative and Combinatory Categorial Grammar (ACCG) can be drawn on to design powerful software applications for the teaching of languages. To this end, we present some modules from our “pictographic translator”, a software that performs syntactical analysis of sentences in natural language directly written by the user, and then dynamically displays series of pictograms that illustrate the words and structure of the user’s sentences. After a short presentation of our application and an introduction to ACCG, we will examine how this formalism enables the building of several high-level functions in our system, such as disambiguation, structure exhibition and grammatical correction/validation. We finally open a short discussion concerning the potential (and limits) of this architecture with regards to multilingualism.

EcoLexicon is a multilingual terminological knowledge base (TKB) on the environment. It is currently being converted into a domain-specific ontology, however, ontological properties are modelled according to surface semantics. For this reason, we are integrating our TKB in the form of a “satellite ontology” into FunGramKB, a multipurpose knowledge base specifically designed for natural language understanding. We explain how the dynamism of environmental concepts can benefit from a formal description in meaning postulates and their inclusion in FunGramKB Cognicon scripts. This would lead to the automatic generation of flexible conceptual networks and definitional templates across different contexts.

In affective natural language generation (NLG) a major aim is to be able to influence the emotional effects evoked in the addressee through the intelligent use of language. While previous work has shown that varying the form of the language, while keeping the content the same, can have a measurable effect on the emotions of the addressee, we report here on work which investigated which linguistic techniques to give the text a more or less positive slant contribute to these emotional effects. We report on three studies in which texts that gave positive feedback on an IQ test performance were tested for emotional effects on the recipient. The first study followed a comparison method on the sentence level, and the second study compared the texts as a whole. In both of these, participants were asked to rate the emotional effects that they thought the texts would have. On the other hand, in the third study different types of feedback were evaluated in a context of use, where participants were asked to perform an IQ test, read their feedback and report on their actual emotional state. In the first two studies, participants confirmed that the texts contained essentially the same content. The positive slanting techniques generally resulted in texts that were judged to be either positive or equal to neutral texts, although the effects were less strong than in previous work, which employed a variety of techniques, and there were a number of exceptions which impact on the usefulness of these techniques. However the IQ-test experiment did not show any emotional effects arising from variation in the form of the feedback. We reflect on possible reasons for this outcome and what it might mean for further work on Affective NLG.

Since the reinvigoration of emotions research, many computationalmodels of emotion have been developed. None ofthese models, however, fully address the integration of emotiongeneration and emotional effect in the context of cognitiveprocesses. This paper seeks to unify various modelsof computational emotions while fully integrating with workdone in cognitive architectures. We propose a perspective onhow this integration would occur and EmoCog, a cognitivearchitecture with mechanisms for emotion generation and effects.

It has been also demonstrated that emotional In its basic underpinning assumptions, cognitive load states (e.g., negative mood or anxiety) directly influence theory relies on the analogy between the information cognitive task performance and the operation of working processing aspects of evolution by natural selection and memory, while less evidence exists about the effect of the human cognition (Sweller & Sweller, 2006). It considers emotional content of the processed information (e.g., both biological evolution and human cognition as Kensinger & Corkin, 2003).

We propose a new interpretation for a certain kind of ASO preference rules to handling prioritized symptoms. Our interpretation is based on the idea of dependence based priority propagation. Then, we present a fixpoint based answer set optimization method under such an interpretation.

We present research in decision tree analysis that studies a data set and finds new patterns that were not obvious using statistical methods. Our method is applied to a database of accommodative esotropic patients. Accommodative esotropia is an eye disease that when left untreated leads to blindness. Patients whose muscles deteriorate often need corrective surgery, since less invasive methods of treatment tend to fail in these patients. Using a learn and prune methodology, decision tree analysis of 354 accommodative esotropic patients led to the discovery of two conjunctive variables that predicted deterioration in the initial year of treatment better than what was previously determined using standard statistical methods.

We address the problem of simulate democratic elections via a set of competing agents.We propose a logical model based on a set of non-cooperative agents which compete for attracting a maximum number of votes from a population. Each agent builds a set of strategies (formed by the promises, actions and proposals of the agent) used to convince to the potential voters.

Subset space logic (SSL, henceforth) was presented in early In this paper, we consider public announcement logic (PAL, 90s as a bimodal logic to formalize reasoning about sets and henceforth) in several different geometric models, and prove points (Moss and Parikh 1992). The language of SSL has its completeness of those models. Moreover, we also consider two modal operators K and . A subset space model is a some applications of our ideas in different fields varying triple S 〈S, σ, v〉 where S is a nonempty set, σ is a collection from game theory to epistemic logic. What makes our of subsets (not necessarily a topology), v is a valuation work novel is the fact that PAL has never been investigated function. Semantics of SSL for modal operators is given in geometric and topological models with further applications.