Semantic representation of multimedia content: Knowledge representation and semantic indexing

In this paper we present a framework for unified, personalized access to heterogeneous multimedia content in distributed repositories. Focusing on semantic analysis of multimedia documents, metadata, user queries and user profiles, it contributes to the bridging of the gap between the semantic nature of user queries and raw multimedia documents. The proposed approach utilizes as input visual content analysis results, as well as analyzes and exploits associated textual annotation, in order to extract the underlying semantics, construct a semantic index and classify documents to topics, based on a unified knowledge and semantics representation model. It may then accept user queries, and, carrying out semantic interpretation and expansion, retrieve documents from the index and rank them according to user preferences, similarly to text retrieval. All processes are based on a novel semantic processing methodology, employing fuzzy algebra and principles of taxonomic knowledge representation. The first part of this work presented in this paper deals with data and knowledge models, manipulation of multimedia content annotations and semantic indexing, while the second part will continue on the use of the extracted semantic information for personalized retrieval.

A framework for a video analysis tool for suspicious event detection

This paper proposes a framework to aid video analysts in detecting suspicious activity within the tremendous amounts of video data that exists in today’s world of omnipresent surveillance video. Ideas and techniques for closing the semantic gap between low-level machine readable features of video data and high-level events seen by a human observer are discussed. An evaluation of the event classification and detection technique is presented and a future experiment to refine this technique is proposed. These experiments are used as a lead to a discussion on the most optimal machine learning algorithm to learn the event representation scheme proposed in this paper.

Exploring interoperability of language resources: the case of cross-lingual semi-automatic enrichment of wordnets

In this paper we present an application fostering the integration and interoperability of computational lexicons, focusing on the particular case of mutual linking and cross-lingual enrichment of two wordnets, the ItalWordNet and Sinica BOW lexicons. This is intended as a case-study investigating the needs and requirements of semi-automatic integration and interoperability of lexical resources, in the view of developing a prototype web application to support the GlobalWordNet Grid initiative.

Semantic representation of Korean numeral classifier and its ontology building for HLT applications

The complexity of Korean numeral classifiers demands semantic as well as computational approaches that employ natural language processing (NLP) techniques. The classifier is a universal linguistic device, having the two functions of quantifying and classifying nouns in noun phrase constructions. Many linguistic studies have focused on the fact that numeral classifiers afford decisive clues to categorizing nouns. However, few studies have dealt with the semantic categorization of classifiers and their semantic relations to the nouns they quantify and categorize in building ontologies. In this article, we propose the semantic recategorization of the Korean numeral classifiers in the context of classifier ontology based on large corpora and KorLex Noun 1.5 (Korean wordnet; Korean Lexical Semantic Network), considering its high applicability in the NLP domain. In particular, the classifier can be effectively used to predict the semantic characteristics of nouns and to process them appropriately in NLP. The major challenge is to make such semantic classification and the attendant NLP techniques efficient. Accordingly, a Korean numeral classifier ontology (KorLexClas 1.0), including semantic hierarchies and relations to nouns, was constructed.

E-redesigning of society: towards experiential connectivity of generations in Lithuania

The paper reflects on the unique experience of social and technological development in Lithuania since the regaining of independence as a newly reshaped society constructing a distinctive competitive IST-based model at global level. This has presented Lithuanian pattern of how to integrate different experiences and relations between generations in implementing complex information society approaches. The resulting programme in general is linked to the Lisbon objectives of the European Union. The experience of transitional countries in Europe, each different but facing some common problems, may be useful to developing countries in Africa.

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The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.

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Mixture of KL subspaces for relevance feedback

Relevance feedback has recently emerged as a solution to the problem of improving the retrieval performance of an image retrieval system based on low-level information such as color, texture and shape features. Most of the relevance feedback approaches limit the utilization of the user’s feedback to a single search session, performing a short-term learning. In this paper we present a novel approach for short and long term learning, based on the definition of an adaptive similarity metric and of a high level representation of the images. For short-term learning, the relevant and non-relevant information given by the user during the feedback process is employed to create a positive and a negative subspace of the feature space. For long-term learning, the feedback history of all the users is exploited to create and update a representation of the images which is adopted for improving retrieval performance and progressively reducing the semantic gap between low-level features and high-level semantic concepts. The experimental results prove that the proposed method outperforms many other state of art methods in the short-term learning, and demonstrate the efficacy of the representation adopted for the long-term learning.

Methods for quantitative usability requirements: a case study on the development of the user interface of a mobile phone

Quantitative usability requirements are a critical but challenging, and hence an often neglected aspect of a usability engineering process. A case study is described where quantitative usability requirements played a key role in the development of a new user interface of a mobile phone. Within the practical constraints of the project, existing methods for determining usability requirements and evaluating the extent to which these are met, could not be applied as such, therefore tailored methods had to be developed. These methods and their applications are discussed.

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Contextualization of Geospatial Database Semantics for Human–GIS Interaction

Human interactions with geographical information are contextualized by problem-solving activities which endow meaning to geospatial data and processing. However, existing spatial data models have not taken this aspect of semantics into account. This paper extends spatial data semantics to include not only the contents and schemas, but also the contexts of their use. We specify such a semantic model in terms of three related components: activity-centric context representation, contextualized ontology space, and context mediated semantic exchange. Contextualization of spatial data semantics allows the same underlying data to take multiple semantic forms, and disambiguate spatial concepts based on localized contexts. We demonstrate how such a semantic model supports contextualized interpretation of vague spatial concepts during human–GIS interactions. We employ conversational dialogue as the mechanism to perform collaborative diagnosis of context and to coordinate sharing of meaning across agents and data sources.

ONTRACK: Dynamically adapting music playback to support navigation

Listening to music on personal, digital devices whilst mobile is an enjoyable, everyday activity. We explore a scheme for exploiting this practice to immerse listeners in navigation cues. Our prototype, ONTRACK, continuously adapts audio, modifying the spatial balance and volume to lead listeners to their target destination. First we report on an initial lab-based evaluation that demonstrated the approach’s efficacy: users were able to complete tasks within a reasonable time and their subjective feedback was positive. Encouraged by these results we constructed a handheld prototype. Here, we discuss this implementation and the results of field-trials. These indicate that even with a low-fidelity realisation of the concept, users can quite effectively navigate complicated routes.

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Multimodal support to group dynamics

The complexity of group dynamics occurring in small group interactions often hinders the performance of teams. The availability of rich multimodal information about what is going on during the meeting makes it possible to explore the possibility of providing support to dysfunctional teams from facilitation to training sessions addressing both the individuals and the group as a whole. A necessary step in this direction is that of capturing and understanding group dynamics. In this paper, we discuss a particular scenario, in which meeting participants receive multimedia feedback on their relational behaviour, as a first step towards increasing self-awareness. We describe the background and the motivation for a coding scheme for annotating meeting recordings partially inspired by the Bales’ Interaction Process Analysis. This coding scheme was aimed at identifying suitable observable behavioural sequences. The study is complemented with an experimental investigation on the acceptability of such a service.

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Explicit semantic events detection and development of realistic applications for broadcasting baseball videos

This paper presents a framework that explicitly detects events in broadcasting baseball videos and facilitates the development of many practical applications. Three phases of contributions are included in this work: reliable shot classification, explicit event detection, and elaborate applications. At the shot classification stage, color and geometric information are utilized to classify video shots into several canonical views. To explicitly detect semantic events, rule-based decision and model-based decision methods are developed. We emphasize that this system efficiently and exactly identifies what happened in baseball games rather than roughly finding some interesting parts. On the basis of explicit event detection, many accurate and practical applications such as automatic box score generation and game summarization could be built. The reported results show the effectiveness of the proposed framework and demonstrate some research opportunities about bridging the semantic gap for sports videos.

A cost-effective lexical acquisition process for large-scale thesaurus translation

Thesauri and controlled vocabularies facilitate access to digital collections by explicitly representing the underlying principles of organization. Translation of such resources into multiple languages is an important component for providing multilingual access. However, the specificity of vocabulary terms in most thesauri precludes fully-automatic translation using general-domain lexical resources. In this paper, we present an efficient process for leveraging human translations to construct domain-specific lexical resources. This process is illustrated on a thesaurus of 56,000 concepts used to catalog a large archive of oral histories. We elicited human translations on a small subset of concepts, induced a probabilistic phrase dictionary from these translations, and used the resulting resource to automatically translate the rest of the thesaurus. Two separate evaluations demonstrate the acceptability of the automatic translations and the cost-effectiveness of our approach.

Interacting with mobile services: an evaluation of camera-phones and visual tags

We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive, although they had several important reservations about camera-phone technology more generally. Data from our pointing-device task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings, design lessons for camera-phone and visual-tag applications are presented.

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Connecting the family with awareness systems

Awareness systems have attracted significant research interest for their potential to support interpersonal relationships. Investigations of awareness systems for the domestic environment have suggested that such systems can help individuals stay in touch with dear friends or family and provide affective benefits to their users. Our research provides empirical evidence to refine and substantiate such suggestions. We report our experience with designing and evaluating the ASTRA awareness system, for connecting households and mobile family members. We introduce the concept of connectedness and its measurement through the Affective Benefits and Costs of communication questionnaire (ABC-Q). We inform results that testify the benefits of sharing experiences at the moment they happen without interrupting potential receivers. Finally, we document the role that lightweight, picture-based communication can play in the range of communication media available.

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Learning element similarity matrix for semi-structured document analysis

Capturing latent structural and semantic properties in semi-structured documents (e.g., XML documents) is crucial for improving the performance of related document analysis tasks. Structured Link Vector Mode (SLVM) is a representation recently proposed for modeling semi-structured documents. It uses an element similarity matrix to capture the latent relationships between XML elements—the constructing components of an XML document. In this paper, instead of applying heuristics to define the element similarity matrix, we propose to compute the matrix using the machine learning approach. In addition, we incorporate term semantics into SLVM using latent semantic indexing to enhance the model accuracy, with the element similarity learnability property preserved. For performance evaluation, we applied the similarity learning to k-nearest neighbors search and similarity-based clustering, and tested the performance using two different XML document collections. The SLVM obtained via learning was found to outperform significantly the conventional Vector Space Model and the edit-distance-based methods. Also, the similarity matrix, obtained as a by-product, can provide higher-level knowledge on the semantic relationships between the XML elements.

Ethical regulations on robotics in Europe

There are only a few ethical regulations that deal explicitly with robots, in contrast to a vast number of regulations, which may be applied. We will focus on ethical issues with regard to “responsibility and autonomous robots”, “machines as a replacement for humans”, and “tele-presence”. Furthermore we will examine examples from special fields of application (medicine and healthcare, armed forces, and entertainment). We do not claim to present a complete list of ethical issue nor of regulations in the field of robotics, but we will demonstrate that there are legal challenges with regard to these issues.

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