A multi-agent based user context Bayesian neural network analysis system

The increasing user mobility demands placed upon IT services necessitates an environment that enables users to access optimal services at any time and in any place. This study presents research conducted to develop a system that is capable of analyzing user IT service patterns and tendencies and provides the necessary service resources by sharing each user’s context information. First, each user’s context information is gathered to provide the multi-agent software training data necessary to describe user operations in a hybrid peer-to-peer (P2P) structured communication environment. Next, the data collected about each user’s mobile device is analyzed through a Bayesian based neural network system to identify the user’s tendency and extract essential service information. This information provides a communication configuration allowing the user access to the best communication service between the user’s mobile device and the local server at any time and in any place, thereby enhancing the ubiquitous computing environment.     

Adaptation and user expertise modelling in AthosMail

This article describes the User Model component of AthosMail, a speech-based interactive e-mail application developed in the context of the EU project DUMAS. The focus is on the system’s adaptive capabilities and user expertise modelling, exemplified through the User Model parameters dealing with initiative and explicitness of the system responses. The purpose of the conducted research was to investigate how the users could interact with a system in a more natural way, and the two aspects that mainly influence the system’s interaction capabilities, and thus the naturalness of the dialogue as a whole, are considered to be the dialogue control and the amount of information provided to the user. The User Model produces recommendations of the system’s appropriate reaction depending on the user’s observed competence level, monitored and computed on the basis of the user’s interaction with the system. The article also discusses methods for the evaluation of adaptive user models and presents results from the AthosMail evaluation.The research was done while the author was affiliated with the University of Art and Design Helsinki as the scientific coordinator of the DUMAS project.     

What is the difference? A cognitive dissimilarity measure for information retrieval result sets

Result rankings from context-aware information retrieval are inherently dynamic, as the same query can lead to significantly different outcomes in different contexts. For example, the search term Digital Camera will lead to different—albeit potentially overlapping—results in the contexts customer reviews and shops, respectively. The comparison of such result rankings can provide useful insights into the effects of context changes on the information retrieval results. In particular, the impact of single aspects of the context in complex applications can be analyzed to identify the most (and least) influential context parameters. While a multitude of methods exists for assessing the relevance of a result ranking with respect to a given query, the question how different two result rankings are from a user’s point of view has not been tackled so far. This paper introduces DIR, a cognitively plausible dissimilarity measure for information retrieval result sets that is based solely on the results and thus applicable independently of the retrieval method. Unlike statistical correlation measures, this dissimilarity measure reflects how human users quantify the changes in information retrieval result rankings. The DIR measure supports cognitive engineering tasks for information retrieval, such as work flow and interface design: using the measure, developers can identify which aspects of context heavily influence the outcome of the retrieval task and should therefore be in the focus of the user’s interaction with the system. The cognitive plausibility of DIR has been evaluated in two human participants tests, which demonstrate a strong correlation with user judgments.     

MIMOSA: context-aware adaptation for ubiquitous web access

The ubiquitous computing scenario is characterized by heterogeneity of devices used to access services, and by frequent changes in the user’s context. Hence, adaptation according to the user’s context and the used devices is necessary to allow mobile users to efficiently exploit Internet-based services. In this paper, we present a distributed framework, named MIMOSA, that couples a middleware for context-awareness with an intermediary-based architecture for content adaptation. MIMOSA provides an effective and efficient solution for the adaptation of Internet services on the basis of a comprehensive notion of context, by means of techniques for aggregating context data from distributed sources, deriving complex contextual situations from raw sensor data, evaluating adaptation policies, and solving possible conflicts. The middleware allows programmers to modularly build complex adaptive services starting from simple ones, and includes tools for assisting the user in declaring her preferences, as well as mechanisms for detecting incorrect system behaviors due to a wrong choice of adaptation policies. The effectiveness and efficiency of MIMOSA are shown through the development of a prototype adaptive service, and by extensive experimental evaluations.     

Semantic web technologies to reconcile privacy and context awareness

Increasingly, application developers are looking for ways to provide users with higher levels of personalization that capture different elements of a user’s operating context, such as her location, the task that she is currently engaged in, who her colleagues are, etc. While there are many sources of contextual information, they tend to vary from one user to another and also over time. Different users may rely on different location tracking functionality provided by different cell phone operators; they may use different calendar systems, etc. In this article, we describe work on a Semantic e-Wallet aimed at supporting automated identification and access of personal resources, each represented as a Semantic Web Service. A key objective is to provide a Semantic Web environment for open access to a user’s contextual resources, thereby reducing the costs associated with the development and maintenance of context-aware applications. A second objective is, through Semantic Web technologies, to empower users to selectively control who has access to their contextual information and under which conditions. This work has been carried out in the context of myCampus, a context-aware environment aimed at enhancing everyday campus life. Empirical results obtained on Carnegie Mellon’s campus are discussed.     

On context-aware distributed event dissemination

In pervasive environments, the Pub/Sub paradigm is regarded as an important means of information sharing and event dissemination. In this paper, we first analyze different context in Pub/Sub systems that has remarkable impacts upon user’s satisfaction to event dissemination and then give corresponding strategies by exploiting time context and event-preference context so as to provide personalized event dissemination. That is, by leveraging time context, we provide the extended matching against long-standing events, and by leveraging event-preference context, we present the recommendation algorithm which is based on hidden Markov process. Performance analysis and experiment evaluation show that both strategies can improve user’s experiences of event dissemination.     

Adaptation of robot’s perception of fuzzy linguistic information by evaluating vocal cues for controlling a robot manipulator

This article proposes a method for adapting a robot’s perception of fuzzy linguistic information by evaluating vocal cues. The robot’s perception of fuzzy linguistic information such as “very little” depends on the environmental arrangements and the user’s expectations. Therefore, the robot’s perception of the corresponding environment is modified by acquiring the user’s perception through vocal cues. Fuzzy linguistic information related to primitive movements is evaluated by a behavior evaluation network (BEN). A vocal cue evaluation system (VCES) is used to evaluate the vocal cues for modifying the BEN. The user’s satisfactory level for the robot’s movements and the user’s willingness to change the robot’s perception are identified based on a series of vocal cues to improve the adaptation process. A situation of cooperative rearrangement of the user’s working space is used to illustrate the proposed system by a PA-10 robot manipulator.     

A web-based pervasive recommendation system for mobile tourist guides

Mobile tourist guides have attracted considerable research interest during the past decade, resulting in numerous standalone and web-based mobile applications. Particular emphasis has been given to personalization of services, typically based on travel recommender systems used to assist tourists in choosing places to visit; these systems address an important aspect of personalization and hence reduce the information burden for the user. However, existing systems fail to exploit information, behaviours, evaluations or ratings of other tourists with similar interests, which would potentially provide ground for the cooperative production of improved tourist content and travel recommendations. In this paper, we extend this notion of travel recommender systems utilizing collaborative filtering techniques while also taking into account contextual information (such as the current user’s location, time, weather conditions and places already visited by the user) for deriving improved recommendations in pervasive environments. We also propose the use of wireless sensor network (WSN) installations around tourist sites for enabling precise localization and also providing mobile users convenient and inexpensive means for uploading tourist information and ratings about points of interest (POI) via their mobile devices. We also introduce the concept of ‘context-aware rating’, whereby user ratings uploaded through WSN infrastructures are weighted higher to differentiate among users that rate POIs using the mobile tourist guide application while onsite and others using the Internet away from the POI.     

People, Information Systems and Change

Information systems are the glue between people and computers. Both the social and business environments are in a continual, some might say chaotic, state of change while computer hardware continues to double its performance about every 18 months. This presents a major challenge for information system developers.  The term user-friendly is an old one, but one which has come to take on a multitude of meanings. However, in today’s context we might well take a user-friendly system to be one where the technology fits the user’s cognitive models of the activity in hand. This article looks at the relationship between information systems and the changing demands of their users as the underlying theme for the current issue of Cognition, Technology and Work.  People, both as individuals and organisations, change. The functionalist viewpoint, which attempts to freeze and inhibit such change, has failed systems developers on numerous occasions. Responding to, and building on, change in the social environment is still a significant research issue for information systems specialists who need to be able to create living information systems.     

Modelling both the Context and the User

Research into context-aware computing risks losing sight of the user. This paper discusses how different types of information about a user, ranging from information about the current context to information about the user’s long-term properties, can simultaneously be relevant to a given adaptation decision. Pointers are given to two areas of research that can help with the integration of a broader range of information into context-aware systems: research on user-adaptive systems and on decision-theoretic methods.     

Effective Communication in Requirements Elicitation: A Comparison of Methodologies

The elicitation or communication of user requirements comprises an early and critical but highly error-prone stage in system development. Socially oriented methodologies provide more support for user involvement in design than the rigidity of more traditional methods, facilitating the degree of user–designer communication and the ‘capture’ of requirements. A more emergent and collaborative view of requirements elicitation and communication is required to encompass the user, contextual and organisational factors. From this accompanying literature in communication issues in requirements elicitation, a four-dimensional framework is outlined and used to appraise comparatively four different methodologies seeking to promote a closer working relationship between users and designers. The facilitation of communication between users and designers is subject to discussion of the ways in which communicative activities can be ‘optimised’ for successful requirements gathering, by making recommendations based on the four dimensions to provide fruitful considerations for system designers.     

Supporting Ubiquitous IMS-based Teleconferencing Through Discovery and Composition of IMS and Web Components

Natural communication among people happens in flexible ways and is strongly affected by the users’ situation (such as communication tools available, user’s location, and user’s preferences). This situation or context information is seldom used to initiate communication sessions among users. Current communication systems are indifferent about users’ context, often require time consuming manual configurations and often result in conferencing tools not being easily accessible when needed. This leads to lower adoption of innovative communications services. IMS SIP (IP Multimedia Subsystem, Session Initiation Protocol) sessions allow users to access the session from different points of contact (home, office, etc.), however, IMS still requires a prior knowledge of all SIP components that might be used in a SIP session. Furthermore, IMS makes limited use of context information (mainly user-defined availability). To address these issues our research approach combines techniques from pervasive computing with IMS networking principles to facilitate compositions of communication sessions based on users’ context. We propose a platform and APIs for pervasive application development support to allow greater intelligence in IMS applications. We additionally provide mechanisms for IMS applications to apply their intelligence to the configuration of physical devices and web resources used to set up a conference. The innovations proposed in this paper are: (1) A new standard for intelligent IMS-based conferencing applications. (2) Application Development Interfaces (APIs) for a platform for pervasive computing. (3) An architecture for a pervasive IMS platform.

Friendly information retrieval through adaptive restructuring of information space

Although a technique of relevance feedback is common in the field of information retrieval (IR), the feedback is usually done by means of query refinement; restructuring of the information space has not been attempted yet. The restructuring not only allows useful applications such as clustering but also is indispensable for IR if a modeling function employs correlation of terms. In this paper we present a new method of relevance feedback through the restructuring of the information space. Our method adapts document space to the user’s mental model by manipulating a dictionary vector. Therefore, user’s viewpoint is preserved after a series of retrieval processes and reused for retrieval performed later. We show its effectiveness through the retrieval experiments on FAQ (Frequntly Asked Questions) documents. Tomoko Murakami: She obtained her bachelor’s degree in Engineering from Aoyama Gakuin University in 1996, and her master’s degree in Media and Governance from Keio University in 1998. In 1998 she joined Human Interface Labolatory, Corporate Research & Development Center, Toshiba Corporation, Kawasaki, Japan. Her research interests are in Machine Learning, especially Inductive Logic Programming. She is a member of JSAI. Ryohei Orihara, Ph.D.: He is a research scientist at Human Interface Laboratory, Corporate Research & Development Center, Toshiba Corporation. He obtained his bachelor’s degree and master’s degree in Engineering and Ph.D. from University of Tsukuba in 1986, 1988 and 1999 respectively. His current research interests include machine learning, creativity support system, analogical reasoning and metaphor understanding. He was a visiting researcher at University of Toronto from 1993 to 1995. He is a member of IPSJ, JSAI and JSSST. He is presently on the editorial committee of the Journal of JSAI.     

Content-based image retrieval using fuzzy perceptual feedback

In this paper, a new framework called fuzzy relevance feedback in interactive content-based image retrieval (CBIR) systems is introduced. Conventional binary labeling scheme in relevance feedback requires a crisp decision to be made on the relevance of the retrieved images. However, it is inflexible as user interpretation of visual content varies with respect to different information needs and perceptual subjectivity. In addition, users tend to learn from the retrieval results to further refine their information requests. It is, therefore, inadequate to describe the user’s fuzzy perception of image similarity with crisp logic. In view of this, we propose a fuzzy relevance feedback approach which enables the user to make a fuzzy judgement. It integrates the user’s fuzzy interpretation of visual content into the notion of relevance feedback. An efficient learning approach is proposed using a fuzzy radial basis function (FRBF) network. The network is constructed based on the user’s feedbacks. The underlying network parameters are optimized by adopting a gradient-descent training strategy due to its computational efficiency. Experimental results using a database of 10,000 images demonstrate the effectiveness of the proposed method.

Towards the semantic and context-aware management of mobile multimedia

Users of mobile devices can nowadays easily create large quantities of mobile multimedia documents tracing significant events attended, places visited or, simply, moments of their everyday life. However, they face the challenge of organizing these documents in order to facilitate searching through them at a later time and sharing them with other users. We propose using context awareness and semantic technologies in order to improve and facilitate the organization, annotation, retrieval and sharing of personal mobile multimedia documents. Our approach combines metadata extracted and enriched automatically from the users’ context with annotations provided manually by the users and with annotations inferred by applying user-defined rules to context features. These new contextual metadata are integrated into the processes of annotation, sharing and keyword-based retrieval.     

An attempt to enhance performance in user session based information retrieval

The ongoing surge in the amount of online information has made the process of accurate retrieval much more difficult. Providers of information retrieval systems have come under a lot of pressure to improve their techniques to cater for the modern user. Conventional systems are often limited as they fail to understand the true search intent of the user. This is usually a result of both poor query formulation by the user and an inability of the search engine to process the query adequately. In this paper, an approach is presented that attempts to learn a user’s short-term interests through the clustering of their search results. A profile is maintained for each user to assist in the process of context resolution for a given query. The details of such an approach and experimental results to evaluate its effectiveness are presented in this paper.     

Exploring Context-aware Information Push

Despite much interest over recent years in the area of context-aware computing, there are still a number of significant gaps in our understanding of the HCI issues associated with such systems. One particular issue that remains relatively unexplored is how to design around the apparently conflicting goals of adapting to changes in context while at the same time adhering to the principle of predictability. In this paper, we describe our exploration into this issue through two alternative designs of an interactive context-aware tourist guide. One original design was based around information pull, i.e. the emphasis is on the user to decide when context-aware information is presented. Our second design incorporates the notion of information push whereby the actual presentation of context-aware information is triggered by contextual events, e.g. changes in the user’s location or changes to the opening times of attractions. Through the evaluation of these alternative designs we hope to gain a better understanding of the usability implications relating to push vs. pull in both this specific domain and in interactive context-aware systems in general.     

A social approach to context-aware retrieval

We present a general purpose solution to Web content and services perusal by means of mobile devices, named Social Context-Aware Browser. This is a novel approach for information access based on users’ context, that exploits social and collaborative models to overtake the limits of the existing solutions. Instead of relying on a pool of experts and on a rigid categorization, as it is usually done in the context-aware field, our solution allows the crowd of users to model, control, and manage the contextual knowledge through collaboration and participation. To have a dynamic and user-tailored context representation, and to enhance the process of retrieval based on users’ actual situation, the community of users is encouraged to define the contexts of interest, to share, use, and discuss them, and to associate context to content and resources (Web pages, services, applications, etc.). This paper provides an overall presentation of our solution, describing the idea, the implementation, and the evaluation through a benchmark based methodology.