Towards Avatars with Artificial Minds: Role of Semantic Memory

he first step towards creating avatars with human-like artificial minds is to give them human-like memory structures with an access to general knowledge about the world. This type of knowledge is stored in semantic memory. Although many approaches to modeling of semantic memories have been proposed they are not very useful in real life applications because they lack knowledge comparable to the common sense that humans have, and they cannot be implemented in a computationally efficient way. The most drastic simplification of semantic memory leading to the simplest knowledge representation that is sufficient for many applications is based on the Concept Description Vectors (CDVs) that store, for each concept, an information whether a given property is applicable to this concept or not. Unfortunately even such simple information about real objects or concepts is not available. Experiments with automatic creation of concept description vectors from various sources, including ontologies, dictionaries, encyclopedias and unstructured text sources are described. Haptek-based talking head that has an access to this memory has been created as an example of a humanized interface (HIT) that can interact with web pages and exchange information in a natural way. A few examples of applications of an avatar with semantic memory are given, including the twenty questions game and automatic creation of word puzzles

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

CHORUS Deliverable 3.3: Vision Document - Intermediate version

The goal of the CHORUS vision document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area (in line with the mandate of CHORUS as a Coordination Action). This current intermediate draft of the CHORUS vision document (D3.3) is based on the previous CHORUS vision documents D3.1 to D3.2 and on the results of the six CHORUS Think-Tank meetings held in March, September and November 2007 as well as in April, July and October 2008, and on the feedback from other CHORUS events. The outcome of the six Think-Thank meetings will not just be to the benefit of the participants which are stakeholders and experts from academia and industry – CHORUS, as a coordination action of the EC, will feed back the findings (see Summary) to the projects under its purview and, via its website, to the whole community working in the domain of AV content search. A few subjections of this deliverable are to be completed after the eights (and presumably last) Think-Tank meeting in spring 2009

Quality assessment technique for ubiquitous software and middleware

The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 201