清木 康

This paper includes five contributions on the topic of multimedia information systems for social, cross-cultural and environmental computing. Approaches, models, and methods for Web Semantization, Cross-cultural Image Computing, Information Modelling and Data Mining, Mobile Information Systems for Ubiquitous Society, and Multimedia Systems for Cross-cultural and Environmental Computing are introduced and discussed. This paper is based on the contributions presented in the panel discussion of EJC 2012 Conference.

In our paper we discuss advanced viewpoints to "Kansei" and cross-cultural computing, to context modelling, context-sensitive information systems, and cross-cultural software engineering. Culture is embodied in how people interact with other individuals and with their environment. It is a way of life formed under specific historical, natural and social conditions. Culture can be considered as one example of context. A computational method, a computer system, or an application is context-sensitive if it includes context-based functions and if it uses context to provide relevant information and services to the user, where relevancy depends on the user's impressions and the situation at hand. Because of globalization, cultural competence together with context sensitive information systems and their development has become an important dimension for success in today's international business and research.

This paper points out that achievements in the field of multimedia analysis and retrieval represent an important opportunity for improvement of recommender system mechanisms. Online shopping systems use various recommender systems; however a study of different approaches has shown that they do not exploit the potential of information carried by multimedia product data for product recommendations. We demonstrate how this can be accomplished by a personalized recommender system framework that is based on a method of analysis of colour features of entity images. Colour-features are based on image colour histograms, psychological properties of colours and a learning mechanism. We have developed a service-oriented framework for a personalized recommender system that is based on incorporation of this method into a highly interactive business process model. The framework is designed in a generic way and can be applied to an arbitrary domain. It is based on service- oriented architecture in order to promote its flexibility and reuse, which is important when applying it to existing recommender system environments. An experimental study was performed for the domain of travel agency. The framework provides several important advantages, such as automatic creation of entity image meta-data which is based on colour-based image analysis and extraction of their semantic properties, user-interaction based learning, dynamic selection and presentation ordering of entity images, and feedback for creation of base image entity sets.

Over the past decade, the rapid progress of multimedia data management technology has realized the large scale of media data transfer and resource-accumulation in the world. The multimedia computing technology has also been creating new information provision environments in the world-wide scope. Innovative integrations of large scale multimedia data management and computing technology will lead to a new information society. In the design of multimedia systems, one of the most important issues is how to search and analyze media data (images, music, movies and documents), according to impressions and contexts. We have proposed and introduced a "Kansei" and semantic associative search method based on our "Mathematical Model of Meaning (MMM) [11], [13], [14]". The concept of "Kansei" includes several meanings on sensitive recognition, such as "impression", "human senses", "feelings", "sensitivity", "psychological reaction" and "physiological reaction". This model realizes "Kansei" processing and semantic associative search for media data, according to user's impressions and contexts. This model is applied to compute semantic correlations between keywords, images, music and documents dynamically in a context-dependent way. The main feature of this model is to realize semantic associative search in the 2000 dimensional orthogonal semantic space with semantic projection functions. This space is created for dynamically computing semantic equivalence or similarity between keywords and media data. We have constructed "Cross-Cultural Multimedia Computing Systems" for sharing and analyzing different cultures with semantic associative functions applied to "cultural &amp multimedia data," as a new platform of cross-cultural collaborative environments. This environment enables to create a remote, interactive and real-time cultural and academic research exchange among different countries and cultures. © 2012 Springer-Verlag Berlin Heidelberg.

Context is a multi-dimensional concept. It is hard to define context generally for computer science. Which information is considered as context, which is not? Why are the certain context elements relevant for a certain case, but irrelevant for another? How to explain this to computers? Can computers learn these issues as humans do? In our paper we present different viewpoints to the concept of context and to context modelling starting from requirements engineering and ending up to multi-disciplinary education. Based on context related literature research and discussions in our paper, we can summarize that a complete and comprehensive definition and model of context is difficult to achieve and may not even be appropriate at all. However we can conclude that there is a common understanding that context always relates to an entity, context is used to solve a problem, context depends on the domain of use, context depends on time and context is evolutionary.

Image-query creation for expressing user's intentions is essential for efficient utilization of massive digital image resources. This paper presents an image-query creation method for expressing user's query intentions by combining multiple images for Content-based Image Retrieval. The image-query for expressing intentions is created by combining image resources in image aspects such as colors and objects. This method realizes image-query creation by the drawing on user's imagination to express intentions such as the addition of the color, the removal of the object, the conversion and the scaling. This method uses multiple actual images and applies several query-creation operators calculating image features for expressing intentions to those images. This paper shows implementation of the experimental system where image queries are expressed with specific intentions to clarify the feasibility and effectiveness of the proposed method with experimental results.

Virtual communities rely primarily on ICT to connect their members to work together, and to share knowledge and practices. The importance of virtual collaborative work is increasing not only because of its economical and environmental benefits, but also due to its flexibility for establishing dynamically new cross-organizational and cross-cultural innovative teams. Virtual collaborative spaces should support their joint activities. In order to design and realize such spaces, an understanding of the tasks to be carried out by the virtual community is necessary, as well as an understanding of the related processes, contexts, and knowledge. In our paper, we introduce a reference model of a Cross-Cultural Cyber Space (CCS) for context-based knowledge creation and sharing between the members of the cross-cultural collaborative community. We also describe the prototype implementation of the CCS, a 3D cross-cultural art museum system.

Cultural computing is an emerging field of multidisciplinary computer science. In the near future, cultural computing will have several important applications in the fields of business, knowledge society, environmental issues, health care, education and research. Our paper is written in collaboration with the authors, who are also participants in the collaborative research project "Ubiquitous Cross-Cultural Multimedia Systems for Mobile Computing Societies/Ubiquitous Cross-Cultural Knowledge Space". The issues discussed in our paper cover background knowledge related to cultural computing, general discussion of culture as a concept, an introduction to the concept and basic design of the Electronic Assistant for Cross-Cultural Communication, and an introduction to the design and implementation of the 3D Cross-Cultural Multimedia Museum" system and its applications. The 3D Cross-Cultural Multimedia Museum has been implemented as a prototype system of Cross-Cultural Cyber Space. The global changes caused not only by scientific and technological development, but by environmental issues as well, are our driving forces towards the era of cultural computing. Our paper is based on the presentations of the panel discussion at the EJC 2009 Conference.

For effective access to digital files on personal computers, many researchers have proposed and developed several personal information management tools including desktop search engines. However, it is still a challenging task to retrieve personal files according to their meaning and content. In this paper, we propose a personal information retrieval system that can semantically search for personal files based on users' intentions and interests in the desktop environment. Our system creates a retrieval vector space based on constructed sample files that reflect current user requirements. It represents personal files as vectors in the retrieval vector space. Our system allows users to re-build the retrieval space quickly according to change of their intentions. Therefore, when users' requirements change in the desktop environment, users can effectively retrieve personal files that match their current intentions and interests by using the re-built retrieval space. In this paper, we focus on the capacity for semantic information retrieval and the system's adaptability to users' intentions and interests, and we show the feasibility of the proposed system by experimental evaluation.

In this paper, we present a superordinate and subordinate relationship computation method. We have proposed a vector space search method for computing causal relationships. We extend this method to compute directionality relationships of superordinate and subordinate concepts. By using general knowledge expression with a tree structure, we generate vector spaces for computing those directionality relationships. This method dealing with the combination of those directionality relationships makes it possible to realize a superordinate and subordinate relationship computation, according to various objectives related to directionality relationships. We have implemented a superordinate and subordinate relationship computing system for directionality relationships among technical terms in the aerospace engineering .eld. We clarify the effectiveness and feasibility of our system by several experiments.