While energy conservation is an urgent need, many people still misuse thermostats to control heating systems, resulting in wasted energy. One of the main causes is the lack of immediate thermal feedback. In this work, we investigate how immediate touch-based thermal feedback can be an appropriate interaction modality to improve the thermostat UI for manual control, and allow anticipation of the outcome of setpoint adjustment through user interaction. Based on two mixed-methods experimental user studies, we demonstrate the applicability of immediate thermal feedback to translate and anticipate a sense of thermal comfort that is meaningful and satisfying to the user. We also show the usability of this feedback as an interaction modality for adjusting a temperature setpoint, which is perceived as simple, natural and accurate.

We study in this paper the problem of clustering comparable corpora, building upon the observation that different types of clusters can be present in such corpora: monolingual clusters comprising documents in a single language, and bilingual or multilingual clusters comprising documents written in different languages. Based on a state-of-the-art deep variant of Kmeans, we propose new clustering models fully adapted to comparable corpora and illustrate their behavior on several bilingual collections (in English, French, German and Russian) created from Wikipedia.

Graphical Adaptive Menus are Graphical User Interface menus whose predicted items of immediate use can be automatically rendered in a prediction window. Rendering this prediction window is a key question for adaptivity to enable the end-user to efficiently differentiate predicted items from normal ones and to consequently select appropriate items. Adaptivity for graphical menus has been investigated more for normal screens, such as desktops, than for small screens, such as smartphones, where real estate imposes severe rendering constraints. To address this question, this article defines and explores a design space where graphical adaptive menus are structured based on Bertin’s eight visual variables (i.e., position, size, shape, value, color, orientation, texture, and motion) and their combination by comparing their rendering for small screens with respect to normal screens. Based on this design space, previously introduced graphical adaptive menus are revisited in terms of four stability properties (i.e., spatial, physical, format, and temporal), and new menu designs are introduced and discussed for both normal and small screens. The resulting set of graphical adaptive menu has been subject to a preference analysis from which a particular design emerged: the cloud menu, where predicted items are arranged in an adaptive tag cloud. We investigate empirically the effect of the cloud menu on the item selection time and the error rate with respect to a static menu and an adaptive linear menu. This article then suggests a set of usability guidelines for designers and practitioners to design graphical adaptive menus in general and cloud menus in particular.

This paper presents Cloud Menus, a split adaptive menu for small screens where the predicted menu items are arranged in a circular tag cloud with a location consistent with their corresponding position in the static menu and a font size depending on their prediction level. This layout results from a 3-step design process: (i) defining an initial design space on Bertin's 8 visual variables and 4 quality properties, (ii) identifying the most preferred layout based on agreement rate, and (iii) implementing it into Cloud Menus, a new widget for Android with circular layout. An empirical study suggests that cloud menus reduce item selection time and error rate when prediction is correct without penalizing it when prediction is incorrect, compared to two baselines: a non-adaptive static menu and an adaptive linear menu. From this study, design guidelines for cloud menus are elaborated.

The exploration and discovery of nature through walking, cycling, touring, trekking and hiking are targeted by this work, part of an on-going research on mobile-based persuasive user interaction. Considering HCI solutions dedicated to discover and explore nature, we uncover the concept of persuasive event and several classes of roles that users may endorse during a long-term usage of such interactive solutions. We claim the importance of these events and roles as, leveraging persuasion, they may contribute to improve nature discovery experience and to sustain motivation through user interaction. In this work we share these insights from our studies on the Mhikes platform, designed for such kind of nature-involved activities.

This paper presents a design space for engineering adaptive user interfaces throughout the user interface development life cycle in order to describe any adaptation technique, adaptable or adaptive, to compare two or more techniques, and to generate new, perhaps unprecedented, techniques. Grounded in the theory of psychological perception, this design space structures the adaptation life cycle into two regulation loops between the user and the system: a perception-decision-action (PDA) loop for both the system and the user, and a learning-prediction-adaptation (LPA) for supporting the adaptation, this last being particularly expressive for adaptivity. This PDA-LPA design space enables defining properties for assessing the quality of these loops between the system and the end-user. This design space of is instantiated on two advanced adaptive user interfaces: adaptive user interfaces based on machine learning and adaptive layouts. This design space provides new insights for considering adaptivity design options.

This paper presents a model-based approach for designing Polymodal Menus, a new type of multimodal adaptive menu for small screen graphical user interfaces where item selection and adaptivity are responsive to more than one interaction modality: a menu item can be selected graphically, tactilely, vocally, gesturally, or any combination of them. The prediction window containing the most predicted menu items by assignment, equivalence, or redundancy is made equally adaptive. For this purpose, an adaptive menu model maintains the most predictable menu items according to various prediction methods. This model is exploited throughout various steps defined on a new Adaptivity Design Space based on a Perception-Decision-Action cycle com-ing from cognitive psychology. A user experiment compares four conditions of Polymodal Menus (graphical, vocal, gestural, and mixed) in terms of menu selection time, error rate, user subjective satisfaction and user preference, when item prediction has a low or high level of accuracy. Polymodal Menus offer alternative input/output modalities to select menu items in various contexts of use, especially when graphical modality is constrained.

The Proceedings of the ACM (PACM) was initiated by ACM in 2015 as overarching framework for publishing high quality computer science research. The goal for these new journals is to provide an alternate journal publication model for rigorous research papers that have traditionally been presented at major ACM conferences. PACM titles cross multiple intellectual communities, and each separate PACM is designed to represent a broad, but consistent, reach area. This is the first issue of the Proceedings of the ACM on Human Computer Interaction (PACMHCI), which represents the varied topics and communities that compose the broader study of Human Computer Interaction (HCI). The rich heterogeneity of this field can be expressed as deep ethnographies of information use in context, to experiments showing the effectiveness of interface designs, to the production of new technologies that push the limits of how we interact with computers, and much more. The production of PACMHCI will focus on content associated with major research communities that are supported by the ACM Special Interest Group on Human-Computer Interaction (SIGCHI). Individual issues will be largely associated with separate research communities, who may then also select papers from the issue for presentation at their major conferences. These research communities provide the volunteers and editors necessary to provide the rigorous review and editorial process that will define this journal. Those editors will serve on the overall board for ACMHCI, to help bridge our diverse communities. Leveraging our research communities allows us to provide high-quality reviewing while maintaining the quick processing of work that is important in this quickly moving field. This inaugural issue of PACMHCI represents work from the Engineering Interactive Computing Systems (EICS) community. EICS gathers researchers that aim to improve the ways we build interactive systems. Building interactive systems is a multi-faceted and challenging activity, involving a plethora of different actors and roles. This is particularly true in the domain of HCI, where we continuously push the edge of what is possible, where there is a crucial need for adequate processes, tools and methods to build reliable, useful and usable systems that help people cope with the ever-increasing complexity of work and life. The primary goal of the EICS research community is to create novel and high quality contributions in this direction. Although there are only three articles in this first issue, our pipeline for future issues is promising. In the first submission cycle, 41 papers were submitted and, of those, 22 were asked for major revisions. We expect a good number of those 22 papers to be ultimately accepted over the coming months. We are grateful to our newly-formed Editorial Board consisting of more than 70 experts for lending their support and knowledge to the new journal. More information about PACMHCI can be found at http://pacmhci.acm.org/.

Sociability of companion robots is one of the challenges that the field of human-robot interaction faces. Inspired from research in psychology and sociology dealing with inter-personal relationships, we aim to render robots capable of a behaviour compatible to be among humans. In the context of a companion robot for children, we propose different parenting styles (namely authoritative and permissive) and evaluate their effectiveness and acceptability by parents. We implemented behaviours of different styles played out by two robots, Nao and Reeti, with body and facial channels respectively for communication. 94 parents watched videos of the robots and replied to a questionnaire about the authoritativeness, effectiveness and acceptability of the robots. The results showed that robots can be perceived as dominant and authoritative; however their effectiveness as an authoritative figure is limited to young children and is correlated to the style played when giving an order. When given a choice between authoritative and permissive styles, the parents ended up not always choosing a parenting style similar to their own. This work contributes in formalising context dependent personalisation to parent expectation of a companion robot for children using the concept of styles.

Design and development methods do not meet designers' and developers' needs. They are difficult to learn and to use; they are complex, sequential and rigid and thus far from being adapted, reliable and efficient. This paper presents M2Flex, a process metamodel for highly supporting flexibility. M2Flex is based on a recent definition of flexibility along four dimensions: (1) variability, the existence of equivalent choices, (2) granularability, the existence of different levels of details, (3) completeness, the possibility of defining optional components and pre-defined reusable results, and (4) distensibility, the capacity of the resulting process model to be extended or reduced at runtime. This paper shows how M2Flex is original by the flexibility it offers to designers and developers at runtime.

On September 19th 2011, Facebook introduced "Intelligent Lists" which are Friends Lists (FL) automatically created and pre-filled based on users' and their contacts' profiles information (education, work, city of living, kin, etc.). In early 2011, we conducted a study on contact management in Facebook in order to understand users' real needs. Outcomes from this study suggest several recommendations, some of which can be found today in the Facebook Intelligent Lists.

The International Workshop on Semantic Models for Adaptive Interactive Systems (SEMAIS 2012) aims to identify emerging trends in interactive system design using semantic models.

The International Workshop on Semantic Models for Adaptive Interactive Systems (SEMAIS 2011) aims to identify emerging trends in interactive system design and execution using semantic models.

This paper describes a framework that serves as a reference for classifying user interfaces supporting multiple targets, or multiple contexts of use in the field of context-aware computing. In this framework, a context of use is decomposed into three facets: the end users of the interactive system, the hardware and software computing platform with which the users have to carry out their interactive tasks and the physical environment where they are working. Therefore, a context-sensitive user interface is a user interface that exhibits some capability to be aware of the context (context awareness) and to react to changes of this context. This paper attempts to provide a unified understanding of context-sensitive user interfaces rather than a prescription of various ways or methods of tackling different steps of development. Rather, the framework structures the development life cycle into four levels of abstraction: task and concepts, abstract user interface, concrete user interface and final user interface. These levels are structured with a relationship of reification going from an abstract level to a concrete one and a relationship of abstraction going from a concrete level to an abstract one. Most methods and tools can be more clearly understood and compared relative to each other against the levels of this framework. In addition, the framework expresses when, where and how a change of context is considered and supported in the context-sensitive user interface thanks to a relationship of translation. In the field of multi-target user interfaces is also introduced, defined, and exemplified the notion of plastic user interfaces. These user interfaces support some adaptation to changes of the context of use while preserving a predefined set of usability properties.

This article nqmts our tiection on softsvam amhiteetm modelling for multi-usersystems (or groupware).Fi~w introduce t.k notion of software architecture and make explieit the design steps that most sofl-wam designm in HCI tend to blend in a fizzy way.Building on general concepts and pmetiee fmm main stream soikm engineering, we then present a comparative analysis of the most signifhnt architecture models developed for singleand multi-user systems.We close with the pmentation d PAC*, a new arehitectuml fmmwodc for modelling and designing the sdsvare amhitectm of multi-user systems.PAC* is a motivated combination of existing anAiteetuml models seleeted for the complementarily of their "good properties".These include operational heuristics such as rules for deriving agents in accordance to the task model or criteria for reasoning about replication as well as properties such as support for style heterogeneity, portability, and reusability.