Typing patterns: a key to user identification

As the deficiencies of traditional password-based access systems become increasingly acute, researchers have turned their focus to keystroke biometrics, which seeks to identify individuals by their typing characteristics. However, this field still faces many challenges before it can see full acceptance.     

Smart graphics: a new approach to meeting user needs

A convergence of computer graphics and other technologies such as artificial intelligence is leading to the development of smart graphics, which recognize application requirements, user characteristics, host-machine capabilities, and target usage, and adapt themselves accordingly. These new, dynamic capabilities extend the utility of computer graphics across a broad range of uses and potential applications. They may also engender the creation of new applications. For example, smart-graphics bar charts could change in accordance with fluctuating stock-market conditions. Developers could use smart graphics to customize GUIs and thus make them more useful. In addition, the technology has the potential to revolutionize graphics use in training, simulation, business productivity, and other applications     

Analyzing user requirements by use cases: a goal-driven approach

The purpose of requirements engineering is to elicit and evaluate necessary and valuable user needs. Current use-case approaches to requirements acquisition inadequately support use-case formalization and nonfunctional requirements. Based on industry trends and research, the authors have developed a method to structure use-case models with goals. They use a simple meeting planner system to illustrate the benefits of this new approach     

Study of collective user behaviour in Twitter: a fuzzy approach

The study of collective user behaviours in social networking sites has become an increasing important topic in social media mining. Understanding such behaviours has its potential to extract actionable patterns that can be beneficial to develop effective marketing strategies, optimise user experiences and maximise website revenues. With the rapid development of micro-blogging, Twitter has become a richer source of intelligence that can be used to study collective user behaviour, due to its efficient and meaningful user-to-user interactions. However, the classical statistical methods have some drawbacks in bridging the gap between user-generated data and human analysts who mostly use linguistic terms to analyse data and model/summarise knowledge learned. To address this gap, this work proposes a new approach, which employs the mass assignment theory-based fuzzy association rules algorithm (MASS-FARM), for the first time, to extract useful interaction behaviour of Twitter users. The influential factors (including activity time, number of friends/followers and the number of tweets) are represented as fuzzy granules, and the associations amongst are studied by employing MASS-FARM. The collective user behaviours are analysed in the Reply category and the Non-Reply category, respectively. The applicability and usefulness of the proposed method are demonstrated via an empirical study on a collected Twitter data set. The derived results are also discussed and compared with existing works.     

Closed-loop identification: a two step approach

The accuracy aspects of identification (with respect to both variance and bias of estimates) and the role of filtering in closed-loop identification is discussed in this paper. It is shown that the key difference between closed-loop and open-loop identification is the existence of the sensitivity function. A closed-loop identification algorithm which asymptotically yields the same expressions as open-loop identification, in both variance and bias errors, is proposed. The proposed algorithm is evaluated by simulated examples as well as experiments performed on a computer-interfaced pilot-scale process.     

Interactive user modeling: An integrative explicit-implicit approach

User modeling issues are examined in the context of a user-adapted guidance system. The system provides users with instructions about natural tasks without introducing a special time-consuming sub-dialog to learn the user's knowledge. A model for providing such guidance is developed on the basis of a phenomenological analysis of human guidance, and illustrated by a system that gives directions in geographical domains. The main features of the user model design include: (1) Bothimplicit andexplicit acquisition methods are employed in a flexible manner; (2) The guidance instructions and the user model are generated incrementally and interchangeably; (3) User's responses and no-responses are employed as a source of information for the user modeling. The model and the resulting system's performance are examined in light of recent development in the cognitive literature.E. Shifroni is a PhD candidate in Computer Science at the Technion. He received his B.A. in Mathematics and Computer Science from the Hebrew University of Jerusalem in 1982, and his M.S. degree in Computer Science from the same University in 1984. His primary interests lie in the areas of dialog systems and user modeling. This paper summarizes the current state of his thesis work on interactive user modeling.B. Shanon studied philosophy and linguistics in Tel-Aviv university, and linguistics and psychology at Stanford (PhD in psychology, 1974). After teaching at MIT joined the Department of Psychology of the Hebrew University, of which he is now chairperson. Also served as a visiting professor at Cornell University and Swarthmore College, as a visiting fellow at Princeton University, and as a visiting scholar at the center of interdisciplinary Research of the University of Bielefeld and at the Rockefeller Foundation Study center in Bellagio. Research interest focus on the conceptual foundation of cognitive science, the phenomenology of human conscious mentation, and on the psychology of creativity. A monograph presenting a comprehensive critique of the representational view of mind and a search for alternatives to it is forthcoming.     

Scanning on the fly: An approach to the user interface

Educational software must provide a “friendly” user interface in order to prevent student frustration. A recurring source of student frustration is the task of responding to prompts issued by the computer. Scanning on the fly reduces the difficulty of this task. It prevents the possibility of errors of form in student responses by accepting only keystrokes that lead to correctly formatted responses. This approach has the advantage that all text displayed by the computer pertains to the content of the lesson and none to the technical use of the computer. Its implementation is based on the notion of a finite state automaton, yielding reliable and easily modifiable software. Scanning on the fly has been used in the development of microcomputer-based instructional software for college algebra and trigonometry.     

Evaluation of user interfaces: EVADIS II— a comprehensive evaluation approach

As a result of the importance of the usability approach in system development and the EC's 'Directive concerning the minimum safety and health requirements for VDT workers' (EWG 1990), there is an accepted need for practical evaluation methods for user interfaces. The usability approach and the EC Directive are not restricted to user interface design, as they include the design of appropriate hardware and software, as well as organization, job, and task design. Therefore system designers are faced with many, often conflicting, requirements and need to address the question, 'How can usability requirements comprehensively be considered and evaluated in system development?' Customers buying hardware and software and introducing them into their organization ask, (How can I select easy-to-use hardware and software?' Both designers and customers need an evaluation procedure that covers all the organizational, user, hard- and software requirements. The evaluation method, EVADIS.II, we present in this paper overcomes characteristic deficiencies of previous evaluation methods. In particular, it takes the tasks, the user, and the organizational context into consideration during the evaluation process, and provides computer support for the use of the evaluation procedure.     

Towards a model-driven approach for multiexperience AI-based user interfaces

Software and Systems Modeling - Software systems start to include other types of interfaces beyond the “traditional” Graphical-User Interfaces (GUIs). In particular, Conversational User...     

On the series expansion approach to the identification ofHammerstein systems

A polynomial identification algorithm for recovering a nonlinearity in the Hammerstein system is proposed. The estimate employs the Legendre orthogonal system with adaptively selected number of terms. The global consistency along with rates of convergence are established. No assumptions concerning continuity of the nonlinearity or its functional form are made. A data-driven method using the cross-validation technique for selecting the number of terms in the estimate is presented     

Modeling user action planning: A comprehension based approach

We review our efforts to model user command production in an attempt to characterize the knowledge users of computers have at various stages of learning. We modeled computer users with a system called NETWORK (Mannes and Kintsch, 1988; 1991) and modeled novice, intermediate, and expert UNIX command production data collected by Doane et al. (1990b) with a system called UNICOM (Doane et al., 1989a; 1991). We use the construction-integration theory of comprehension proposed by Kintsch (1988) as a framework for our analyses. By focusing on how instructions activate the knowledge rele/ant to the performance of the specified task, we have successfully modeled major aspects of correct user performance by incorporating in the model knowledge about individual commands and knowledge that allows the correct combination of elementary commands into complex, novel commands. Thus, experts can be modeled in both NETWORK and in UNICOM. We further show that salient aspects of novice and intermediate performance can be described by removing critical elements of knowledge from the expert UNICOM model. Results suggest that our comprehension-based approach has promise for understanding user interactions and implications for system design are discussed.Dr. Stephanie Doane is Assistant Professor of Psychology and appointed at the Beckman Institute at the University of Illinois. Shereceived her BAin Experimental Psychology from the University of California, Santa Barbara, her MS in Experimental Psychology from Villanova University, and her PhD in Cognitive Psychology from the University of California, Santa Barbara. Dr. Doane's research has focused on skill acquisition and the development and validation of theoretically-based computational models of cognitive processes. Her current research addresses issues of learning to interact with complex systems and the role of learning context in skill acquisition.Dr. Suzanne Mannes is Assistant Professor of Psychology at the University of Delaware. She received her BA in Psychology from the State University of New York College at Plattsburgh and received her PhD in Cognitive Psychology from the University of Colorado at Boulder. Her experimental research focuses on the role of prior knowledge in text comprehension, particularly as it pertains to problem-solving abilities. She also investigates the use of hybrid computer systems to simulate results from such studies.Dr. Walter Kintsch is Professor of Psychology and Director of the Institute of Cognitive Science at the University of Colorado in Boulder. He received his MA and PhD degrees in Experimental Psychology from the University of Kansas. His main area of interest has been the psychology of language and memory. He is currently the editor of the Psychological review.Peter Poison is Professor of Psychology and member of the Institute of Cognitive Science at the University of Colorado. He received his BA degree in Psychology and BS degree in Industrial Engineering from Stanford University and his PhD degree in Psychology from Indiana University. Dr. Poison's research has focused on the development and empirical evaluation of mathematical and computer simulation models of cognitive processes including transfer of training, problem solving, and the acquisition of cognitive skills. His current research deals with quantitative models of human-computer interaction and the application of such models to the design of more easily learned computer systems.     

Automating user reviews using ontologies: an agent-based approach

The Web is becoming a global market place, where the same services and products are offered by different providers. When obtaining a service, consumers have to select one provider among many alternatives to receive a service or buy a product. In real life, when obtaining a service, many consumers depend on the user reviews. User reviews—presumably written by other consumers—provide details on the consumers’ experiences and thus are more informative than ratings. The down side is that such user reviews are written in natural language, making it extremely difficult to be interpreted by computers. Therefore, current technologies do not allow automation of user reviews and require too much human effort for tasks such as writing and reading reviews for the providers, aggregating existing information, and finally choosing among the possible candidates. In this paper, we represent consumers’ reviews as machine processable structures using ontologies and develop a layered multiagent framework to enable consumers to find satisfactory service providers for their needs automatically. The framework can still function successfully when consumers evolve their language and when deceptive reviewers enter the system. We show the flexibility of the framework by employing different algorithms for various tasks and evaluate them for different circumstances.     

The relationship between user participation and system success: a simultaneous contingency approach

The relationship between user participation and information system (IS) success has drawn attention from researchers for some time. It is assumed that strong participation of future users in the design of IS would lead to successful outcomes in terms of more IS usage, greater user acceptance, and increased user satisfaction. However, in spite of this, much of the empirical research so far has been unable to demonstrate its benefits. This paper examines the participation–success relationship in a broader context, where the effects of user participation and two other factors, user attitudes and user involvement, on system success occur simultaneously. Other contingency variables considered here are: system impact, system complexity, and development methodology. The theoretical framework and the associated hypotheses are empirically tested by a survey of 32 organizations. Empirical results corroborate the positive link between user participation and user satisfaction and provide evidence on the interplay between user attitudes and user involvement.     

The effect of user characteristics on the efficiency of visual querying

Information systems increasingly provide options for visually inspecting data during the process of information discovery and exploration. Little research has dealt so far with user interactions with these systems, and specifically with the effects of characteristics of the displayed data and the user on performance with such systems. The study reports an experiment on users' performance with a visual exploration system. Participants had to identify target graphs within a large set of candidate graphs by using visual filtering criteria that differed in their efficiency for reducing the number of candidate graphs. A pay-off matrix and a time limit served to motivate users to select filter criteria efficiently. Performance was measured as the number of correct identifications of target graphs within a time-limit, and the number, type and position of filter criteria selected for the search. Efficiency was somewhat biased by users' preference to select filter criteria sequentially, starting from the left to the right. Rational and experiential cognitive styles affected performance, and they interacted with learning and the types of filter criteria chosen. The study shows that not only visual search tools can be used effectively but also that data and user characteristics affect task performance with such systems.     

On input-dependent system identification by Monte Carlo approach

The problem of a weighted least-squares approximation of a memoryless system within a given class of models is discussed, and an identification algorithm leading to the best model when only input-output data are accessible is derived using a concept of random choice of inputs.     

An efficient approach for the maintenance of user behaviours

Mining sequential patterns is to discover sequential purchasing behaviours for most of the customers from a large number of customer transactions. The strategy of mining sequential patterns focuses on discovering frequent sequences. A frequent sequence is an ordered list of the itemsets purchased by a sufficient number of customers. The previous approaches for mining sequential patterns need to repeatedly scan the database so that they take a large amount of computation time to find frequent sequences. The customer transactions will grow rapidly in a short time, and some of the customer transactions may be antiquated. Consequently, the frequent sequences may be changed due to the insertion of new customer transactions or the deletion of old customer transactions from the database. It may require rediscovering all the patterns by scanning the entire updated customer transaction database. In this paper, we propose an incremental updating technique to maintain the discovered sequential patterns when transactions are inserted into or deleted from the database. Our approach partitions the database into some segments and scans the database segment by segment. For each segment scan, our approach prunes those sequences that cannot be frequent sequences any more to accelerate the finding process of the frequent sequences. Therefore, the number of database scans can be significantly reduced by our approach. The experimental results show that our algorithms are more efficient than other algorithms for the maintenance of mining sequential patterns.     

Icon identification in context: the changing role of icon characteristics with user experience

OBJECTIVE: This research examined the relative importance of icon characteristics in determining the speed and accuracy of icon identification. BACKGROUND: Studies to date have focused on the role of one or two icon characteristics when users first experience an icon set. This means that little is known about the relative importance of icon characteristics or how the role of icon characteristics might change as users gain experience with icons. METHODS: Thirty participants carried out an icon identification task over a long series of trials to simulate learning through experience. Icon characteristics investigated included semantic distance, concreteness, familiarity, and visual complexity. RESULTS: Icon characteristics were major determinants of performance, accounting for up to 69% of the variance observed in performance. However, the importance of icon characteristics changed with experience: Semantic distance is crucial initially while icon-function relationships are learned, but familiarity is important later because it has lasting effects on access to long-term memory representations. CONCLUSION: These findings suggest that icon concreteness may not be of primary importance when identifying icons and that semantic distance and familiarity may be more important. APPLICATION: Designers need to take into account icon characteristics other than concreteness when creating icons, particularly semantic distance and familiarity. The precise importance of the latter characteristics will vary depending on whether icons are rarely encountered or frequently used.