Semiology of Graphics: Diagrams Networks Maps.

Mobile tourist guides evolve towards automated personalized tour planning devices. The contribution of this article is to put forward a combined artificial intelligence and metaheuristic approach to solve tourist trip design problems (TTDP). The approach enables fast decision support for tourists on small footprint mobile devices. The orienteering problem, which originates in the operational research literature, is used as a starting point for modelling the TTDP. The problem involves a set of possible locations having a score and the objective is to maximize the total score of the visited locations, while keeping the total time (or distance) below the available time budget. The score of a location represents the interest of a tourist in that location. Scores are calculated using the vector space model, which is a well-known technique from the field of information retrieval. The TTDP is solved using a guided local search metaheuristic. In order to compare the performance of this approach with an algorithm that appeared in the literature, both are applied to a real data set from the city of Ghent. A collection of tourist points of interest with descriptions was indexed and subsequently queried with popular interests, which resulted in a test set of TTDPs. The approach presented in this article turns out to be faster and produces solutions of better quality.

http://wwwis.win.tue.nl/bnaic2009/papers/bnaic2009_paper_6.pdf

A Personalized Tourist Trip Design Algorithm For Mobile Tourist Guides

A personalized tourist trip design algorithm for mobile tourist guides

The Botany of Desire:. Plant's-Eye View of the World. By Michael Pollan. 2001. New York: Random House. 271 pages. $24.95 (hardback). ISBN 0-375-50129-0

The Botany of Desire: A Plant's-Eye View of the World

Interaction is fundamental to data visualization, but what “interaction” means in the context of visualization is ambiguous and confusing. We argue that this confusion is due to a lack of consensual definition. To tackle this problem, we start by synthesizing an inclusive view of interaction in the visualization community – including insights from information visualization, visual analytics and scientific visualization, as well as the input of both senior and junior visualization researchers. Once this view takes shape, we look at how interaction is defined in the field of human-computer interaction (HCI). By extracting commonalities and differences between the views of interaction in visualization and in HCI, we synthesize a definition of interaction for visualization . Our definition is meant to be a thinking tool and inspire novel and bolder interaction design practices. We hope that by better understanding what interaction in visualization is and what it can be, we will enrich the quality of interaction in visualization systems and empower those who use them.

/pdf/what-is-interaction-for-data-visualization-2598p11a13.pdf

What is Interaction for Data Visualization

This paper describes the first phase of user-centred design for a mobile, location-based fair guide which is developed in the research project SAiMotion The user requirements analysis based on a usage scenario and a formalized use case model developed in the beginning A focus group and interviews were conducted to gain empirical insights on the potentials and probable acceptance of a location-based fair guide Among the results of these user participation activities, are the integration and visualization of spatial data, temporal data and user-specific information as well as the support of activity planning On this basis, an interface conception was worked out One of it's central parts are interactive maps Derived principles for visual layout and interaction design of maps on small screens are presented

User Requirement Analysis and Interface Conception for a Mobile, Location-Based Fair Guide

We introduce Venice Unfolding, a case study on tangible geo-visualization on an interactive tabletop to enable the exploration of architectural projects in Venice. Our tangible user interface consists of a large display showing projects on a map, and a polyhedral object to browse these data interactively by selecting and filtering various metadata facets. In this paper we describe a prototype employing new methods to communicate territorial data in visual and tangible ways. The object reduces the barrier between the physical world and virtual data, and eases the understanding of faceted geographical data, enabling urban planners and citizens alike to participate in the discovery and analysis of information referring to the physical world.

/pdf/venice-unfolding-a-tangible-user-interface-for-exploring-2why83dh4c.pdf

Venice unfolding: a tangible user interface for exploring faceted data in a geographical context

Karten dienen seit Jahrtausenden als Reprasentationen raumlichen Wissens. Aufgrund ihrer herausragenden Fahigkeit zur Visualisierung von Geoinformationen gehorten sie allzeit zu den begehrtesten Artefakten der jeweils Herrschenden. Neben der Visualisierung von Geoinformationen dienten sie zur Kommunikation politischer und oftmals ideologischer Standpunkte im Zusammenhang mit dem Raumbezug (Crampton 2010; Meng 2009; Monmonier 1996).

Interaktive Karten und Geovisualisierungen

We have developed a Wizard of Oz simulation tool which allows scenario-based simulation of speech systems for the conduction of empirical studies with future users. This paper focuses on the adequate integration of recognition errors as they are an important feature of speech-based applications. The presented solution considers the aspects of reliability and validity. Both are necessary preconditions for the immediate transferability of simulation results to the real system. 1. SPEECH USER INTERFACE PROTOTYPING In the field of GUI design it has become common practice to test usability in early development stages. By using paper prototypes important design decisions can be met on the empirical basis of tests with future users. In comparison to the vast amount of empirical studies and guidelines concerning the usability of GUIs, we know very little about how to design effective speech user interfaces (SUI). Moreover SUI designers face the essential difficulty of getting a sound feeling for the dialogue flow by merely inspecting a written dialogue specification. For these reasons it is even more important to include prototyping and usability testing early in the design process of user-friendly interactive voice response systems (IVR systems). The speech equivalent to a paper prototype is a Wizard of Oz (WOZ) study (Weinschenk & Barker, 2000), where a human (the wizard) simulates the role of the computer during testing and starts different recorded system prompts dependent on what the user said. Usability testing with the WOZ technique can lead to valuable results regarding the following topics: Designing a user-oriented grammar: In very early development stages WOZ studies can pinpoint the utterances which are typically used in order to control the available functions. Given a sufficient number of subjects the transcriptions of the test sessions can give a representative image of how users would expect the system to understand. The most frequently recorded utterances can serve as a valid basis for a user-centred grammar. This way, the timeconsuming procedure of pilot testing including iterative grammar modifications and recognition tuning can be shortened or even partially avoided (Pearl, 2000). Comparison of different systems / system versions: Alternative design decisions can quickly be acted out and tested with future users. Especially the different effects of alternative prompt versions on the users’ performance and attitudes towards the system can be evaluated. Overall ergonomic evaluation: WOZ experiments can take the traditional role of usability tests in evaluation and troubleshooting. The detection of major problems of use in an early development stage enables iterative redesign and reconception without the otherwise necessary phases of implementation. Necessary precondition for the validity of a WOZ study is that the interaction between user and “machine” (here the wizard) has to be as realistic as possible. Otherwise, the gained results cannot be transferred immediately to the real situation of system use. This means, that on one hand, the subject in a WOZ study must actually belief that she interacts with a real system, which is a matter of adequate instruction. On the other hand, the simulation must not differ from the specified system behaviour in essential aspects. Among others, this refers to the reliability of speech recognition which is treated in detail in the following section, and to the available complexity of the dialogue. With high complexity applications it is necessary to do scenario-based testing in order to reduce the amount of probable user utterances. This supports the wizard’s decision by giving a situation specific pre-selection of probable options for “system” reactions. 2. PROBLEM Speech technology is probabilistic in nature and therefore recognition errors are inherent in any speech-based application. Furthermore, situations of recognition errors are especially crucial to usability variables such as effectiveness and efficiency in task solving and user acceptance (Yankelovich, Levow & Marx, 1995). Therefore, it will be indispensable in most cases to carefully simulate error situations in WOZ studies in order to achieve data about questions like: How frustrating do users experience recognition errors in the application in question? Do the mechanisms of error management actually assist the users in correction? Do the users recognise the occurrence of an error at all? How should recognition errors be included into the simulation design? Even if you had in mind the whole grammar of the recognition system you would never be able to anticipate the system’s behaviour. This unpredictability of recognition errors is still increased if the IVR system is used from a cellular phone. Obviously, a simple rule-based model for simulation of recognition errors is not applicable. On the other hand, bare arbitrariness or intuition as basis for the wizard’s decisions will bias the test results. In order to ensure reliability and validity of a WOZ study the following aspects have to be taken into account: Realistic probabilities for recognition errors: A predefined and realistic probability for correct understandings, substitution errors and rejection errors is a precondition for a sound evaluation of the relevant usability criteria. And it allows controlled examination of the consequences of various confidence thresholds. The confidence threshold defines the minimal probability of correct classification needed to execute an action. Probabilities below the threshold lead to rejection usually accompanied by a prompt like ‘Sorry, I could not understand you. Please repeat.’ Necessary data stem from knowledge of the used recogniser and of relevant parameters of the used classification scheme. Standardised simulation: Without using automatic speech recognition it will never be possible to completely eliminate influences on simulation performance that arise from the wizard’s decisions. These influences cannot be held constant over time, different persons and situations. It is an important goal to achieve a maximum level of objectivity by reducing the possible options, the consequences and the need of human decisions to a manageable minimum. Only under comparable test conditions different systems or system versions and the performance of different user groups can be compared adequately. For the comparison of different prototype versions the simulated recognition performance should be balanced in order to avoid undesired side effects. Interactivity: Although standardisation is an important feature, especially in within-subjects designs of system comparison, interactivity is essential for the validity of the results. That means that, despite standardisation of the simulation system, responses must depend on what the user says. Strict balancing (i.e. constant predefined sequences of correct recognition, substitution error and rejection in both conditions) and randomising (i.e. constant predefined frequencies of correct recognition, substitution error and rejection in both conditions) do not consider occurring training effects in the users’ speech performance which are likely to support higher recognition rates in the version presented in the second position. One method to support the simulation of recognition errors is the use of filters, e.g. vocoders which distort the spoken input, in order to help the wizard perform to the system’s expected level (Bernsen, Dybkaer, and Dybkaer, 1998). Filters suffice the requirements of interactivity and standardisation. But it is questionable if they can support a realistic simulation of errors. Firstly, the relationship between the probability of recognition errors and the physical intensity of the filter is not straightforward and has to be investigated empirically before. Secondly, a deterministic filter that constantly distorts the input signal might be no appropriate model for a highly probabilistic process. Human speech performance is probabilistic. Even if two utterances sound completely identically for another person the acoustic signals will never be totally the same. Environmental noise, recording and transmission are also probabilistic factors that make it impossible to anticipate the acoustic quality of the system input signal. Finally, the procedure of recognition itself is probabilistic in nature as it follows a statistical classification scheme. 3. OUR APPROACH We have developed a software tool that supports WOZ simulations of IVR systems (see figure 1 for the GUI). 3.1 The WOZ-GUI Each button (except those for the scenario selection) on the simulation GUI stands for a set of user utterances, a specific subset of the grammar. For ease of use each button is labelled with the corresponding grammar or at least a part of it. The scenario-based approach makes it possible to simulate even highly complex applications. Any scenario consists of one or more pairs of user utterance and system prompt. When a scenario is started the main frame displays a matrix of buttons each representing an expected user utterance. For illustration, let us take a scenario which includes to call John Smith and after that to change his number entry in the telephone book. The first target user utterance is something like “I’d like to call John Smith” which is represented by the first button in the first column. The other buttons in the first line represent expected variations form the target utterance in this first sub-task, e.g. “I want to place a call” or “Go to telephone book” or “John Smith”. These utterances start other actions, e.g. feed-forward prompts that shall obtain the missing data in order to accomplish a transaction (e.g. “Whom would you like to call?”). When feed-forward prompts are played which are not part of the target path (the first column of the main frame) a child window is popped up displaying buttons representing possible user utterances in the actual sub-dialogu

Simulating recognition errors in speech user interface prototyping

We will explore four plausible futures and experiment on a speculative approach to investigate "wicked problems" [14]. Grounded in the field of design fiction, this work combines insights from the climate impact research community, technology meta trends, and plant science, all of which work as a basis for the exploration of relationships between humans, plants, and technology. Based on scenarios from the climate impact research community, we prototyped four plausible worlds and visualized exemplary scenes in the daily life of the plausible citizens. Sketching and low-fidelity prototyping supported the process of gaining knowledge and iterating on storytelling.

Our Symbiotic Life: An Exploration of Interspecies Relations

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