Inferring the sentiment of social media content, for instance blog postings or online product reviews, is both of great interest to businesses and technically challenging to accomplish. This paper presents two computational methods for estimating social media sentiment which address the challenges associated with Web-based analysis. Each method formulates the task as one of text classification, models the data as a bipartite graph of documents and words, and assumes that only limited prior information is available regarding the sentiment orientation of any of the documents or words of interest. The first algorithm is a semi-supervised sentiment classifier which combines knowledge of the sentiment labels for a few documents and words with information present in unlabeled data, which is abundant online. The second algorithm assumes existence of a set of labeled documents in a domain related to the domain of interest, and leverages these data to estimate sentiment in the target domain. We demonstrate the utility of the proposed methods by showing they outperform several standard methods for the task of inferring the sentiment of online reviews of movies, electronics products, and kitchen appliances. Additionally, we illustrate the potential of the methods for multilingual business informatics through a case study involving estimation of Indonesian public opinion regarding the July 2009 Jakarta hotel bombings.

In this position paper we investigate the opportunities of using functionalities provided by social network sites for the collaborative formalization of semantics in the domain of health. In particular we identified benefits in regard to communication support, economic benefits, and technical opportunities. The implementation of the functionalities are illustrated by describing a use case from an ongoing project with the World Health Organization.

In this paper, we present a novel approach of translating natural languages specification to SBVR business rules. The business rules constraint business structure or control behaviour of a business process. In modern business modelling, one of the important phases is writing business rules. Typically, a business rule analyst has to manually write hundreds of business rules in a natural language (NL) and then manually translate NL specification of all the rules in a particular rule language such as SBVR, or OCL, as required. However, the manual translation of NL rule specification to formal representation as SBVR rule is not only difficult, complex and time consuming but also can result in erroneous business rules. In this paper, we propose an automated approach that automatically translates the NL (such as English) specification of business rules to SBVR (Semantic Business Vocabulary and Rules) rules. The major challenge in NL to SBVR translation was complex semantic analysis of English language. We have used a rule based algorithm for robust semantic analysis of English and generate SBVR rules. Automated generation of SBVR based Business rules can help in improved and efficient constrained business aspects in a typical business modelling.

Related to the recent issues on the environmental sustainability, the attention and importance of Reusable Medical Equipment (RME) has increased rapidly. As a part of System Redesign Project funded by Veterans Engineering Resource Center (VERC), “Design Evaluation for Reusable Medical Equipment” project has been conducted. This research project aims to develop new RME design assessment and evaluation framework and Design for Reusability (DFR) and Design for Sustainability (DFS) principles. In this paper, we will present a decision support system for RME design evaluation, based on DFR and DFS principles. To illustrate the proposed new framework, GI endoscope is used in this research. In the proposed system, we apply a Rough Set Theory to identify the relationships among design and reprocessing features. Also we use feature selection technique to select the customized features from the design features and reprocessing features to be used for design evaluation.

Sustainable design is as an important movement in design. Biologically inspired design is a major paradigm for sustainable design. In this paper, we analyze a corpus of biologically inspired design projects in terms of sustainability. We then describe a case study of analogical design of a fog harvesting net, and abstract from it the patterns of Hydrophobia and Hydrophilia. We indicate how these two function-mechanism design patterns occur in several design projects in our corpus. This analysis indicates how biologically inspired sustainable design can be analyzed in terms of cross-domain analogical transfer of design patterns.

Figure 1a first illustrates by the oval that a Cradle-to-cradle (C2C) design (McDonough & Braungart, critical problem in traditional design is that a product is designed 2002) recognizes that nothing short of full recycling of materials in isolation. In contrast, the products shown in the with no degradation in material quality is necessary square box of Figure 1b illustrate the concept of a product for long-term planet sustainability. C2C advocates looking family, where multiple products are designed within a system to the natural world as an ideal model of recycling, where of material use and reuse, which flows between product organic materials are continually recycled through processes lines. While there may still be materials that come from of decay and growth. They propose design methodology outside the family and there are materials that are byproducts that separates biological cycles and syntheticmaterial of the family production, a family design would seek cycles, enabling biological material to be reclaimed to minimize these and to exploit them in a still larger context.

In this contribution, it is suggested that argumentation theories may offer the tools to do so. More specifically, the pragmadialectical theory of argumentation (van Eemeren and Grootendorst 1992; 2004) is proposed as a solid instrument for analyzing and evaluating argumentation in consultation, as it not only provides a set of reasonableness criteria for argumentative conduct but also can account for arguers' need to effectively tailor argumentative messages to their recipients. The instrumental value of pragma-dialectics in the field of automated argument selection will be elucidated by means of a case study concerning antibiotics. In doing so, this contribution is closely connected to the paper by Rubinelli, Wierda, Labrie, and O'Keefe (AAAI Spring Symposium 2011) and provides an exploratory investigation of the advantages of a pragma-dialectical approach to the conceptual design of automated health communication systems and autonomous health promotion.

This paper describes a system that greatly simplifies the task of authoring new behaviors for virtual characters, including physical interactions between characters and other characters or objects. The system in implemented within Twig and allows users to interactively generate and test procedural controllers for characters, as well as triggering mechanisms and arbitration mechanisms for behaviors. It allows users to quickly add new behaviors, or reparameterize existing behaviors, without access to a motion capture studio or professional animators, making it a natural choice for AI researchers, particularly those operating within a university environment. Moreover, it allows a level of continuous parameterization that would be difficult to achieve with traditional animation techniques based on state machines and blending.

While much health data is available online, patients who are not technically astute may be unable to access it because they may not know the relevant resources, they may be reluctant to confront an unfamiliar interface, and they may not know how to compose an answer from information provided by multiple heterogeneous resources. We describe ongoing research in using natural English text queries and automated deduction to obtain answers based on multiple structured data sources in a specific subject domain. Each English query is transformed using natural language technology into an unambiguous logical form; this is submitted to a theorem prover that operates over an axiomatic theory of the subject domain. Symbols in the theory are linked to relations in external databases known to the system. An answer is obtained from the proof, along with an English language explanation of how the answer was obtained. Answers need not be present explicitly in any of the databases, but rather may be deduced or computed from the information they provide. Although English is highly ambiguous, the natural language technology is informed by subject domain knowledge, so that readings of the query that are syntactically plausible but semantically impossible are discarded. When a question is still ambiguous, the system can interrogate the patient to determine what meaning was intended. Additional queries can clarify earlier ones or ask questions referring to previously computed answers. We describe a prototype system, Quadri, which answers questions about HIV treatment using the Stanford HIV Drug Resistance Database and other resources. Natural language processing is provided by PARC’s Bridge, and the deductive mechanism is SRI’s SNARK theorem prover. We discuss some of the problems that must be faced to make this approach work, and some of our solutions.

his paper focuses on the issue of premissary relevance, as a challenge faced in health promotion interventions. To promote attitude change and influence health behavior change, it is crucial that we use premises that are relevant on an individual level. Relevance in argumentation refers to both the fact that the premises have to do with the standpoint at issue and the fact that our interlocutors will accept them. We claim that autonomous argumentation systems hold the promise to enable proper argumentative exchanges that capture and addresses what matters to individuals. To do so, however, there is a need to better consider and operationalise theories of argumentation that enable a reconstruction of the different stages of argumentation. The theory of argumentation known as pragma-dialectics can offer a promising basis for the architecture of autonomous health promotion advisors.