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Aims and Scope

Journal Issues

Editorial Team





Role of Special Issues

As a supplement to its stream of regular articles, TiiS publishes special issues on selected topics for which it can be expected that several articles can be accepted that meet the traditional high standards of ACM journals.

A special issue has the benefit of offering readers a concentration of related articles on an important or emerging topic.

Since a journal issue that includes a special issue will typically include one or more regular articles as well, the publication of regular articles is not delayed by special issues.


Big Personal Data in Interactive Intelligent Systems (Submissions Being Reviewed)

Aims and Scope

Increasingly vast amounts of data about people’s interaction with the social and physical world are generated when people use social media, personal tracking devices, and the internet of things. How can big personal data be collected, analyzed, and exploited so as to provide new or improved forms of interaction with intelligent systems; and what new issues have to be taken into account?

The question of how to process big personal data is challenging because of their sheer quantity, their heterogeneous and sometimes contradictory nature, and the large semantic distance between the data and the conclusions that can be drawn from them.

Big personal data can serve users in various novel ways, but the question of what goals to pursue and how to pursue them is open-ended and not easy to answer.

Exploiting big personal data in interactive systems raises a range of questions concerning usability and acceptance, ranging from privacy issues to those of system comprehensibility and controllability.

This special issue aims to publish the best current work on questions like these, not only presenting technical solutions but also discussing explicitly the consequences of these solutions for users of interactive intelligent systems, from both a design and an engineering point of view.

Topic Dimensions

The following topic dimensions indicate the range of work that is relevant to the special issue. Each dimension is a question that can be asked about a possible submission to the special issue, accompanied by several possible answers to that question. A manuscript is probably relevant to the special issue if you can give meaningful answers to most of these questions (including possibly answers that are not listed here).

What is the origin of the big personal data considered in this work?

  • Users’ behavior on social media sites
  • Users’ traces (e.g., comments) and microtraces (e.g., likes) left on the web
  • People’s use of wearable monitoring devices
  • Users’ interaction with objects that are part of the internet of things
  • ...

What benefits of big personal data processing for end users are considered in this work?

  • Support for users’ choice and decision making
  • New forms of personalization
  • Prediction of user trajectories (e.g., with regard to career, health, or activities)
  • Novel services (e.g., concerning smart buildings or intelligent transportation systems) that require big personal data
  • ...

What issues of usability and acceptance are considered?

  • Users’ understanding of how big personal data are processed
  • Predictability and comprehensibility of interactive system behavior
  • New forms of privacy threat
  • Suitability of novel input methods for collecting big personal data
  • Suitability of methods for visualizing big personal data
  • ...

What user-related challenges in terms of computing technology are addressed?

  • How to combine historical and streaming big personal data
  • How to personalize the collection and storage of big personal data
  • How to capture the semantics of big personal data
  • ...

Special Issue Associate Editors

  • Federica Cena, University of Turin (cena[at]
  • Cristina Gena, University of Turin (gena[at]
  • Geert-Jan Houben, Delft University of Technology (g.j.p.m.houben[at]
  • Markus Strohmaier, GESIS and University of Koblenz-Landau (strohmaier[at]


  • By July 14th, 2015: Submission of manuscripts
  • By October 12th, 2015: Notification about decisions on initial submissions
  • By January 10th, 2016: Submission of revised manuscripts
  • By March 10th, 2016: Notification about decisions on revised manuscripts
  • By April 9th, 2016: Submission of manuscripts with final minor changes
  • By May, 2016: Announcement of accepted articles on the TiiS website
  • July, 2016: Publication of accepted articles in the ACM Digital Library

Except for the initial submission deadline, these dates are indicative rather than definitive. Some submissions will be processed more quickly, while others may require more reviewing and revision. Each accepted article will be announced on the TiiS website shortly after its acceptance and published in the ACM Digital Library within 2-3 months, even if other articles for the special issue are not yet ready for publication.


Human Interaction With Artificial Advice Givers (Manuscripts Being Revised)

Aims and Scope

Some types of system that support people in making choices and decisions can be viewed as artificial advice givers: They propose options and help to evaluate them while involving their human user in the decision making process. These systems differ in terms of their degree of autonomy and the extent to which users can influence reasoning processes and conclusions. For example, a system that supports exploratory search for products will in general leave much of the judgment and decision making to the user, whereas a system that executes semiautonomous maneuvers in a car may offer the driver only the possibility of overriding the system’s choices. In all such situations, there can be benefits and challenges to keeping the human decision makers in the loop, enabling them not only to understand the system’s advice and reasoning but also to call it into question and to influence the system’s reasoning. In particular, over time such a collaboration can support the evolution of the decision makers’ understanding and requirements concerning the domain in question, as well as the evolution of the advice-giving system.

This special issue addresses the asymmetries and synergies that exist between human decision makers and artificial advice givers. It considers how an agent of each type can influence and understand the reasoning, working models, and conclusions of the other agent, especially with the help of recent advances such as novel forms of interaction and advanced methods for generating explanations.

By designing and testing improved forms of support for interactive collaboration between human decision makers and artificial advice givers, we can enable decision making processes that better leverage the strengths of both collaborators.

Topic Dimensions

The following topic dimensions indicate the range of work that is relevant to the special issue. Each dimension is a question that can be asked about a possible submission to the special issue, accompanied by several possible answers to that question. A manuscript is probably relevant to the special issue if you can give meaningful answers to most of these questions (including possibly answers that are not listed here).

What type of advice-giving system does the research concern?

  • Recommender systems
  • Interactive decision support systems (e.g., for medicine or finance)
  • Systems that help mediate group decision making
  • Semiautonomous control systems (e.g., in factories or vehicles)
  • ...

What aspects of the interaction between system and user does the research concern?

  • Ways in which the user understands the system’s reasoning, or vice-versa
  • Ways in which the user influences the system’s reasoning, or vice-versa

What support is there for the user's understanding of the system's reasoning?

  • Visualization of the system’s reasoning
  • Explanations of the system’s reasoning (textual, example-based, adaptive, ...)
  • Design of the system’s reasoning processes to be inherently understandable
  • ...

What techniques does the system employ to understand the user's reasoning?

  • Process tracing
  • Preference modeling
  • Cognitive modeling
  • Error analysis
  • ...

How does the user influence the system's reasoning?

  • (Implicit or explicit) provision by the user of relevant information or requirements
  • Provision by the user of procedural guidance to the system (e.g., concerning the algorithm to be used)
  • Critiquing by the user of the system’s advice, procedures, or models
  • ...

How does the system influence the user's reasoning?

  • By giving access to information or experience
  • Through its representation of the choice situation
  • By offering tools that support a particular type of reasoning
  • By offering procedural advice
  • By suggesting evaluations or choices
  • ...

Is the goal of the interaction to explore a domain or to make a decision?

  • Explore a domain
  • Make a decision
  • A goal intermediate between these

By what criteria is the advice-giving process evaluated?

  • Quality of the outcome
  • Time and effort required
  • Quality of the user’s subjective experience while deciding
  • Extent of the user’s learning with regard to future choices
  • User’s acceptance of the system’s advice
  • User’s general trust in the system
  • ...

Special Issue Associate Editors

  • Nava Tintarev, University Of Aberdeen, UK
    (contact: n[dot]tintarev[at]abdn[dot]ac[dot]uk)
  • John O’Donovan, University of California, Santa Barbara, USA
  • Alexander Felfernig, Graz University of Technology, Austria


  • By June 23rd, 2015: Submission of manuscripts
  • By September 21st, 2015: Notification about decisions on initial submissions
  • By December 20th, 2015: Submission of revised manuscripts
  • By February 18th, 2016: Notification about decisions on revised manuscripts
  • By March 19th, 2016: Submission of manuscripts with final minor changes
  • By April, 2016: Announcement of accepted articles on the TiiS website
  • July, 2016: Publication of accepted articles in the ACM Digital Library

Except for the initial submission deadline, these dates are indicative rather than definitive. Some submissions will be processed more quickly, while others may require more reviewing and revision. Each accepted article will be announced on the TiiS website shortly after its acceptance and published in the ACM Digital Library within 2-3 months, even if other articles for the special issue are not yet ready for publication.


New Directions in Eye Gaze for Interactive Intelligent Systems (Revisions Being Reviewed / Accepted)

Aims and Scope

Eye gaze has been used broadly in interactive intelligent systems: as an input method with which a user can control an interactive system; as a cue for estimating a human’s internal states; as a communication signal that a robot or virtual agent can use when communicating to humans; .... The research area has grown in recent years to cover emerging topics that go beyond the traditional focus on interaction between a single user and an interactive system. For example, some systems analyze eye gaze in communication among two or more humans and in multiparty communication including a computer; others use eye gaze to understand the behavior of a person in a complex real-world environment such as a car. In some of these situations, eye gaze may need to be interpreted in conjunction with other behaviors. This research is providing a foundation for an increasing variety of applications that make use of eye gaze, such as systems for remote communication, drivers’ assistants, and assistive robots. Basic research on computational techniques related to eye gaze is also necessary as the basis of such applications. This special issue aims to publish the best current work in this area, with special emphasis on emerging and novel ways of interpreting and using eye gaze in intelligent interactive systems.

The dimensions listed below indicate the range of work that is relevant to the special issue. Each submission should also fit into the general scope of ACM TiiS as described on the journal website. In case of doubt about the relevance of your topic, please contact the special issue associate editors.

Topic Dimensions

Functions of Eye Gaze

  • Use as an “input device” for controlling a system
  • Part of natural communicative behaviors
  • Natural reflection of internal states
  • Part of perception of the environment (e.g., by a robot)
  • ...

Consideration of Related Behaviors

  • Focus only on eye gaze
  • Focus on eye gaze in conjunction with other communication modalities
  • Focus on eye gaze in conjunction with noncommunicative behaviors (e.g., driving)

Computational Techniques Associated With Eye Gaze

  • Methods for recognizing and classifying eye gaze
  • Methods for generating eye gaze in virtual characters and robots
  • Methods for analyzing eye gaze data off-line

Purposes of Interpreting Human Eye Gaze

  • To understand humans’ actions and communication behavior
  • To interpret a human’s communicative behaviors (e.g., floor management, grounding, and engagement)
  • To assess a human’s internal states (intentions, attitude, interest, emotion, and cognitive state)
  • To evaluate a system (or other artifact) that a user is interacting with
  • Where human-human interaction is (also) involved:
    • To analyze interaction between a computer and multiple humans
    • To support analysis of face-to-face dialogs and group discussions

Types of Interactive Intelligent System that Make Use of Eye Gaze

  • Virtual e-commerce agents
  • Assistive robots
  • Drivers’ assistants that provide guidance based on analysis of eye gaze
  • Guide robots (e.g., in museums)
  • Systems that interact simultaneously with multiple humans
  • Systems supporting human-human communication at a distance
  • Systems supporting users unable to use traditional input devices
  • ...

Special Issue Associate Editors

  • Yukiko Nakano, Seikei University, Japan
    (contact: y[dot]nakano[at]st[dot]seikei[dot]ac[dot]jp)
  • Roman Bednarik, University of Eastern Finland, Finland
  • Kristiina Jokinen, University of Helsinki, Finland
  • Hung-Hsuan Huang, Ritsumeikan University, Japan


  • By December 8th, 2014: Submission of manuscripts
  • By March 22nd, 2015: Notification about decisions on initial submissions
  • By June 20th, 2015: Submission of revised manuscripts
  • By August 19th, 2015: Notification about decisions on revised manuscripts
  • By September 18th, 2015: Submission of manuscripts with final minor changes
  • By October, 2015: Announcement of accepted articles on the TiiS website
  • December, 2015: Publication of accepted articles in the ACM Digital Library

Except for the initial submission deadline, these dates are indicative rather than definitive. Some submissions will be processed more quickly, while others may require more reviewing and revision. Each accepted article will be announced on the TiiS website shortly after its acceptance and published in the ACM Digital Library within 2-3 months, even if other articles for the special issue are not yet ready for publication.


Behavior Understanding for Arts and Entertainment (Published in TiiS 5-2 and 5-3)

Aims and Scope

Techniques for understanding human behavior have become an important technology for interactive intelligent systems. New challenges arise when the behavior being analyzed involves engagement with arts and/or entertainment.

The subject of the behavior understanding may be either a creator, such as a visual artist or a performer; or a person who engages with a (possibly interactive) work of art or entertainment. A system can support these types of interaction in novel and interesting ways through real-time behavior analysis.

The same types of behavior can also be analyzed off-line, to support research in areas like interaction design and social psychology.

The creativity that is involved makes it less likely that the behavior conforms to known patterns and norms, and it makes evaluation less straightforward.

This special issue aims to encourage and publish research about the challenges and opportunities associated with human behavior understanding in arts and entertainment. In accordance with the scope of ACM TiiS, each submission should include a discussion of the implications of the research for some type of interactive system. The specific topics of submitted manuscripts can differ along the dimensions listed below.

Topic Dimensions

Nature of the Behavior Being Analyzed

  • Creative performance and/or responses to it
  • Creation of an artifact and/or interaction with it
  • Game playing

Unit of Behavioral Analysis

  • Individual behavior
  • Group behavior

System Actions Taken on the Basis of On-Line Behavior Understanding

  • Support for creative performance
  • Enhancement of interaction with a game or interactive work of art
  • Increasing the effectiveness of edutainment or persuasion
  • Personalization and adaptation

Functions of Off-Line Behavior Understanding

  • Laying a foundation for improving interaction design
  • Gaining insights into human behavior in creative contexts

Computational Techniques for Human Behavior Understanding

  • Action and activity recognition
  • Affective and social signal analysis
  • Face analysis
  • Analysis of postures, gestures, and haptic interaction
  • Voice and speech analysis
  • Analysis of gaze and attention
  • Biosignal analysis
  • Techniques for benchmarking and evaluation

Application Domains

  • Visual and digital arts
  • Entertainment
  • Education and edutainment
  • Computer games
  • Healthcare and well-being
  • Creativity training

Special Issue Associate Editors

  • Albert Ali Salah, Boğaziçi University, Turkey (salah[at]
  • Hayley Hung, Delft University of Technology, The Netherlands
  • Oya Aran, Idiap Research Institute, Switzerland
  • Hatice Gunes, Queen Mary University of London, UK
  • Matthew Turk, University of California Santa Barbara, USA


Activity Recognition for Interaction (Published in TiiS 4-4)

Aims and Scope

Automatic recognition of human activities has emerged as a key area of research for intelligent interaction between humans, computers, and robots. One goal of activity recognition is to provide information on users’ behaviour and intentions that allows computing systems to assist users proactively with their tasks. Over the last 20 years, researchers have investigated a large number of methods, techniques, and sensors for automatic recognition of activities and gestures. The success of activity recognition has led to activity-aware applications, the commercial launch of a variety of products in the entertainment sector, and wearable technology that measures and analyses human activity.

Advances in activity recognition have opened up many new forms of interaction, most of which have barely been explored to date. This special issue aims to help fill this gap by encouraging and publishing binocular articles on interactive systems that include activity recognition as part of a cycle of interaction between users and computing systems.

The dimensions listed below indicate the range of work that is relevant to the special issue. Each article will normally make a significant scientific contribution along one or more of these dimensions. In case of doubt about the relevance of your topic, please contact the special issue associate editors.

Topic Dimensions

Types of Sensing System

  • Inertial sensors and vision-based systems
  • Wearable and ambient sensing systems
  • Body sensor networks
  • ...

Computational Techniques

  • Signal processing
  • Computer vision
  • Plan recognition, reasoning, and planning
  • Machine learning (e.g., scalable learning)
  • ...

Ways of Getting People Into the Loop of Activity Recognition Design and Development

  • Reality mining
  • Crowdsourcing
  • User interaction (e.g., with active learning)
  • ...

Methods for Design and Evaluation

  • Ethnography and requirements gathering
  • Model-based interaction design and evaluation
  • Formative and summative user studies
  • ...

Functions of Activity Recognition

  • Learning by demonstration
  • Enabling of new interaction techniques
  • Visualisation of human activities
  • Intelligent assistance
  • Recommendation and persuasion
  • ...

Parties Involved in the Interaction

  • Humans and computers
  • Humans and robots
  • Humans and humans

Special Issue Associate Editors

  • Andreas Bulling, Max Planck Institute for Informatics, Germany
    (contact: andreas[dot]bulling[at]acm[dot]org)
  • Ulf Blanke, Swiss Federal Institute of Technology (ETH) Zurich, Switzerland
    (contact: blankeu[at]ethz[dot]ch)
  • Desney Tan, Microsoft Research, United States and China
  • Jun Rekimoto, The University of Tokyo, Japan
  • Gregory Abowd, Georgia Tech, United States


Machine Learning for Multiple Modalities in Interactive Systems and Robots (Published in TiiS 4-3)

Aims and Scope

This special issue will highlight research that applies machine learning to robots and other systems that interact with users through more than one modality, such as speech, touch, gestures, and vision.

Interactive systems such as multimodal interfaces, robots, and virtual agents often use some combination of these modalities to communicate meaningfully. For example, a robot may coordinate its speech with its actions, taking into account visual feedback during their execution. Alternatively, a multimodal system can adapt its input and output modalities to the user’s goals, workload, and surroundings. Machine learning provides interactive systems with opportunities to improve performance not only of individual components but also of the system as a whole. However, machine learning methods that encompass multiple modalities of an interactive system are still relatively hard to find. This special issue aims to help fill this gap.

The dimensions listed below indicate the range of work that is relevant to the special issue. Each article will normally represent one or more points on each of these dimensions. In case of doubt about the relevance of your topic, please contact the special issue associate editors.

Topic Dimensions

System Types

  • Interactive robots
  • Embodied virtual characters
  • Avatars
  • Multimodal systems

Machine Learning Paradigms

  • Reinforcement learning
  • Active learning
  • Supervised learning
  • Unsupervised learning
  • Any other learning paradigm

Functions to Which Machine Learning Is Applied

  • Multimodal recognition and understanding in dialog with users
  • Multimodal generation to present information through several channels
  • Alignment of gestures with verbal output during interaction
  • Adaptation of system skills through interaction with human users
  • Any other functions, especially combining two or all of speech, touch, gestures, and vision

Special Issue Associate Editors

  • Heriberto Cuayahuitl, Heriot-Watt University, UK (contact: h.cuayahuitl[at]gmail[dot]com)
  • Lutz Frommberger, University of Bremen, Germany
  • Nina Dethlefs, Heriot-Watt University, UK
  • Antoine Raux, Honda Research Institute, USA
  • Matthew Marge, Carnegie Mellon University, USA
  • Hendrik Zender, Nuance Communications, Germany


Interactive Computational Visual Analytics (Published in TiiS 4-1)

Aims and Scope

Visual analytics is defined as “the science of analytical reasoning facilitated by visual interactive interfaces.” Since its inception in 2006, the field has grown to encompass a wide array of topics relating to the theory, design, and development of interactive visual interfaces for the purposes of data exploration, data analysis, sense making, and decision making.

While the scope of visual analytics is broad, one principle that has emerged over the years is the need for visual analytics systems to leverage computational methods in data mining, knowledge discovery, and machine learning for large-scale data analysis. In these systems, the human operator works alongside the computational processes in an integrated fashion - the computer can sift through large amounts of data and identify the relevant information, while the human interactively explores the reduced data space to discover trends and patterns and make informed decisions. The two components operate in coordination, allowing for a continuous and cooperative analytical loop.

This special issue will publish papers that address how computational methods can be integrated into interactive visualization systems from a variety of perspectives. The dimensions listed below indicate the range of work that is relevant to the special issue. In case of doubt about the relevance of your topic, please contact the guest editors.

Topic Dimensions

Models, Theory, and Methods for Interactive Computational Visual Analytics

  • Mathematical foundations of data transformations
  • Data management and knowledge representation
  • Integration of multiple or disparate simulation models
  • Interaction, analytical discourse, and sensemaking
  • Analytic provenance and quantification and storage of interactions
  • ...

Real-World Applications Using Interactive Computational Visual Analytics

  • Large-scale (real-world scale) data
  • High-dimensional data
  • Real-time data
  • Streaming data
  • Geospatial data
  • ...

Evaluation of Interactive Computational Visual Analytics

  • Empirical and observational studies
  • User studies with general implications
  • Novel evaluation techniques
  • ...

Special Issue Associate Editors

  • Remco Chang, Tufts University (contact: remco[at]cs[dot]tufts[dot]edu)
  • David Ebert, Purdue University
  • Daniel Keim, University of Konstanz


Human Decision Making and Recommender Systems (Published in TiiS 3-3)

Aims and Scope

A primary function of recommender systems is to help people make good choices and decisions. But in research on recommender systems, surprisingly little attention has been devoted to the decision making processes of users. Instead, it has focused mainly on (a) ways of eliciting and modeling users’ preferences and (b) algorithms for identifying items that a user is likely to evaluate positively. Even systems that do explicitly aim to support the decision making process could benefit from greater use of knowledge about human decision making. And the growing amount of research on users’ interaction with recommender systems, which aims to enhance their usability and acceptance, can be expanded to consider support for specific aspects of decision making.

This special issue will highlight research that explicitly considers ways in which an understanding of human choice and decision making can benefit research and practice on recommender systems. The dimensions listed below indicate the range of work that is relevant to the special issue. In case of doubt about the relevance of your topic, please contact the special issue associate editors.

Topic Dimensions

Types of Decision Made by Users of Recommender Systems

  • Decisions about items in some domain (e.g., products, documents, ...)
  • Decisions about actions performed as part of the domain-level decision making process (e.g., what information to divulge or to acquire)

Aspects of the Recommendation Process

  • Acquiring information about users’ preferences
  • Modeling users’ preferences
  • Provision of decision-relevant information
  • Presentation and explanation of recommendations
  • Adaptation to the interaction context
  • Special characteristics of recommendation to groups
  • ...

Aspects of Human Choice and Decision Making

  • What people desire in a decision making process
  • Roles of justification and argumentation in decision making
  • Descriptive models of choice
  • Heuristics and biases
  • The nature of preferences
  • Temporal aspects of decision making
  • Forms of social influence
  • Roles of emotion and mood
  • Effects of learning from experience
  • Negotiation in decision making
  • Factors that influence decision making (e.g., culture, mood, time pressure ...)
  • ...

Evaluation Criteria for Recommender Systems

  • Decision quality
  • Minimization of effort and stress
  • Trust and confidence
  • ...

Nature of the Research Contribution

  • Novel functionality inspired by an understanding of human decision making
  • Empirical results concerning decision making with recommender systems
  • Innovation in research methodology (e.g., concerning ways of evaluating recommender systems or observing users’ decision making processes)
  • ...

Special Issue Associate Editors

  • Alexander Felfernig, Graz University of Technology, Austria (afelfern[at]ist[dot]tugraz[dot]at)
  • Francesco Ricci, Free University of Bozen-Bolzano, Italy (francesco[dot]ricci[at]unibz[dot]it)
  • Li Chen, Hong Kong Baptist University, China
  • Giovanni Semeraro, Marco de Gemmis, and Pasquale Lops, University of Bari Aldo Moro, Italy


Interaction with Smart Objects (Published in TiiS 3-2)

Aims and Scope

“Smart objects” refers to the rapidly growing trend of introducing computing capabilities into everyday objects and places. Well-known examples range from smart kitchen appliances and objects (smart coffee machines, smart knives and cutting boards, ...) to smart meeting rooms and even city-wide infrastructures. Smart objects are mostly fully functional on their own, but value is added by capabilities for communication and distributed reasoning.

While a lot of research has focused on the many technical challenges involved in implementing smart objects, far less research has been conducted on the question of how interaction of users with these objects can be improved, either by leveraging the intelligence in the objects or by other means. Smart objects raise unique challenges and opportunities for designing interaction with intelligent systems: coping with the mostly limited interaction capabilities, exploiting context information to provide more natural interaction, helping the user to understand the behavior and capabilities of the objects ....

This special issue will publish papers that address these issues from a variety of perspectives. The dimensions listed below indicate the range of work that is relevant to the special issue. In case of doubt about the relevance of your topic, please contact the guest editors.

Topic Dimensions

Paradigms for Interaction With Smart Objects

  • Multimodal interaction
  • Adaptive interaction
  • Context-awareness
  • Embodied and tangible interaction
  • Interacting with ensembles of smart objects
  • ...

Models for Human / Smart Object Interaction

  • Conceptual models of interaction with smart objects
  • Relevant psychological models
  • Design principles and guidelines
  • ...

Intelligibility of Smart Objects

  • Self-explanatory smart objects
  • Natural means for controlling smart objects
  • Intelligibility of smart object ensembles and the Internet of Things
  • ...

Empirical Studies of Human / Smart Object Interaction

  • Novel evaluation techniques
  • ...

Special Issue Associate Editors

  • Max Mühlhäuser, Technische Universität Darmstadt
    (contact: info[at]smart-objects[dot]org)
  • Kris Luyten, Hasselt University, Expertise Centre for Digital Media (EDM)
  • Oliver Brdiczka, PARC
  • Daniel Schreiber, Technische Universität Darmstadt
  • Melanie Hartmann, AGT Group (R&D) GmbH


Internet-Scale Human Problem Solving (Published in TiiS 3-1)

Aims and Scope

Advances in social computing, collective intelligence, and a number of related areas have opened up new prospects for internet-scale human problem solving: technology-supported collaboration of widely distributed people who contribute in diverse roles to the solution of complex, multifaceted problems.

Many further interdisciplinary advances are required if the exploitation of these possibilities is to mature beyond its current state of infancy. Large-scale national and international initiatives are being built up to accelerate this maturation.

This special issue will contribute to progress in this area by publishing articles that ...

  • report on some substantial achievement in a relevant area; and
  • provide a well-founded analysis of the limits of the work done so far and of the next steps that need to be taken.

The list of topic dimensions below structures (nonexhaustively) the space of relevant topics. Articles will differ in the dimensions that they primarily focus on, but each article will make an identifiable contribution to the goal of internet-scale human problem solving.

Topic Dimensions

Support at the social level for ...

  • enhancing awareness and communication
  • allocating tasks to participants
  • motivating participation
  • integrating problem solving ideas
  • testing hypotheses and solutions
  • dealing with differences among participants
  • ...

Support at the individual level for ...

  • eliciting, recognizing, or learning ...
    • data and judgments
    • claims and arguments
    • procedures
    • relevant features of the context
    • ...
  • presenting results of problem-solving activities
  • executing problem-solving actions
  • ...

Ways of dealing with threats concerning ...

  • privacy violations
  • changes over time that impact the problem solving process
  • system breakdowns
  • ...

Research and design methods for ...

  • generating and testing design ideas
  • analyzing and evaluating the use of deployed systems
  • generalizing research results
  • leveraging existing scientific theories
  • integrating contributions from different disciplines
  • ...

Use of intelligent technology for ...

  • knowledge capture
  • learning of procedures
  • sensemaking
  • knowledge integration
  • multiagent communication and coordination
  • information retrieval
  • natural language processing
  • multimodal interaction
  • visualization
  • recommendation and decision support
  • interface adaptation
  • ...

Problem domains:

  • Sustainability
  • Healthcare and quality of life
  • Safety and security
  • Disaster response
  • Production of goods and services
  • Innovation in business
  • Lifelong learning
  • ...

Special Issue Associate Editors

  • Fausto Giunchiglia, University of Trento
    (contact: fausto[at]dit[dot]unitn[dot]it)
  • David Robertson, University of Edinburgh


Highlights of the Decade in Interactive Intelligent Systems (Published in TiiS 2-4)

Aims and Scope

The closing of the first decade of the 21st century saw the launch of a top-tier journal devoted to research on all types of interactive intelligent systems: the ACM Transactions on Interactive Intelligent Systems.

It is fitting that ACM TiiS should publish a special issue comprising papers that showcase some of the most important work of the past decade in this area.

The submissions to this special issue can concern any of the research areas that fall within the scope of the journal. Their difference from articles in other issues of the journal will lie in their unusual importance and impact as representatives of research from the first decade of this century: They will describe the sort of work that someone might refer to when explaining to a person from another field why intelligent interactive systems are an important area to pay attention to.

The research will probably have given rise to a number of publications during the past decade. The “Highlights ...” submission should add value to any such previous publications, for example ...

  • ... by providing a comprehensive publication on the research, whereas previous publications have focused on particular aspects of the work;
  • ... by reporting on results and insights that were not covered in previous publications;
  • ... by including a discussion of the impact that the work has had since the original publications appeared.


Since this special issue is not restricted to a particular topic area, it will be edited by the editors-in-chief of ACM TiiS. Each submission will be managed by one of the associate editors of TiiS and reviewed by three experienced reviewers. Final decisions about inclusion of accepted papers in the “Highlights ...” special issue will be made by a jury comprising several TiiS associate editors who are not associated with any of the submissions.


Common Sense for Interactive Systems (Published in TiiS 2-3)

Aims and Scope

Ideally, computers should be able to interact with users at a higher level than they do now, by understanding our goals, our problems, and the social procedures by which we live. But to do so, they must have access to a wealth of information about the world that we take for granted: common sense knowledge, or world knowledge.

Common sense knowledge can give rise to a richer user experience with a wide variety of interactive systems, from recommenders to storytelling platforms.

Since everyone possesses common sense knowledge, volunteers represent a significant source of common sense for computers. A well-designed intelligent user interface can guide a volunteer in a subjectively rewarding way to add the knowledge that is most needed.

Alternatively, world knowledge may be provided by a domain expert, or a game or story world may be created by an artist; in these cases, an interface must be designed to pass this knowledge from the expert to a common sense knowledge base.

This special issue aims to advance understanding of both sides of this symbiotic relationship: How can common sense enable computers to understand and serve their human users better? How can interfaces effectively support the elicitation of common sense knowledge?


  • Using common sense to understand and predict users’ ...
    • intentions, preferences,
    • goals, plans,
    • context, affect,
    • beliefs, ...
  • Exploiting common sense for ...
    • adaptation of interfaces
    • debugging
    • interpreting data about users
    • “sanity checking”
    • robustly dealing with unusual situations
    • ...
  • Leveraging common sense in systems ...
    • with goal-oriented interfaces
    • for story understanding and generation
    • for open-world gaming
    • for recommendation
    • for text understanding
    • ...
  • Design of intelligent interfaces for elicitation of common sense knowledge ...
    • from experts
    • from nonexpert users
    • using games
    • ...

Special Issue Associate Editors

  • Henry Lieberman, MIT Media Lab, U.S.A.
  • Catherine Havasi, MIT Media Lab, U.S.A.
    (contact: havasi[at]media[dot]mit[dot]edu)


Personalization and Persuasion (Published in TiiS 2-2)

Aims and Scope

Personalized systems aim to enhance users’ experience by taking into account the individual user’s interests, needs, or other relevant properties. Systems based on persuasive technologies aim to modify users’ attitudes, motivation, intentions, or behavior through persuasion and social influence. The coupling of personalization and persuasion has great potential to enhance the impact of both types of technology.

Most persuasive applications employ a “one-size-fits-all” approach to persuasive delivery, but their impact can be increased if characteristics of users are taken into account (e.g., their preferences for particular forms of persuasion). Similarly, the acceptance and effectiveness of personalization (e.g., recommendation of interface adaptations) may be increased if it is supported with state-of-the-art persuasive technology.

This special issue invites submissions in the intersection of the areas of personalization and persuasion, which examine some combination of these two types of technology. Such combinations can be realized in a variety of domains and applications: from natural language techniques for personalized generation of persuasive content through persuasive explanations in recommender systems and e-commerce services to personalized and persuasive aspects of user interfaces and application functionalities.

The dimensions listed below indicate the range of work that is relevant to the special issue.

Topic Dimensions

Relationships Between Persuasion and Personalization

  • Personalization in the service of persuasive technology
  • Persuasive technology in the service of personalization
  • ...

Ways in Which Personalization Can Enhance Persuasion

  • Automatic matching of persuasive techniques to particular users
  • Tailoring of persuasion to the user’s current context
  • ...

Forms of Personalization That Can Be Enhanced With Persuasive Technologies

  • User interface adaptation, recommendation, personalized content generation, personalized information presentation or visualization ...

Application Domains

  • E-commerce, e-learning and intelligent learning environments, multimedia, user support, cultural heritage, health care, ...


  • Web-based systems, mobile systems, smart environments, pervasive/wearable computing , ...

Aspects of Personalized Persuasive Systems

  • Advances in either personalization or persuasive technology required by their combination
  • User experience: explanation, privacy, ethical issues, predictability, and user control
  • Evaluations in research or practice

Special Issue Associate Editors

  • Shlomo Berkovsky, CSIRO, Australia
    (contact: Shlomo.Berkovsky[at]csiro[dot]au)
  • Jill Freyne, CSIRO, Australia
  • Harri Oinas-Kukkonen, University of Oulu, Finland


Eye Gaze in Intelligent Human-Machine Interaction (Published in TiiS 1-2)

Aims and Scope

Partly because of the increasing availability of nonintrusive and high-performance eye tracking devices, recent years have seen a growing interest in incorporating human eye gaze in intelligent user interfaces. Eye gaze has been used as a pointing mechanism in direct manipulation interfaces, for example, to assist users with “locked-in syndrome”. It has also been used as a reflection of information needs in web search and as a basis for tailoring information presentation. Detection of joint attention as indicated by eye gaze has been used to facilitate computer-supported human-human communication. In conversational interfaces, eye gaze has been used to improve language understanding and intention recognition. On the output side, eye gaze has been incorporated into the multimodal behavior of embodied conversational agents. Recent work on human-robot interaction has explored eye gaze in incremental language processing, visual scene processing, and conversation engagement and grounding.

This special issue will report on state-of-the-art computational models, systems, and studies that concern eye gaze in intelligent and natural human-machine communication. The nonexhaustive list of topics below indicates the range of appropriate topics; in case of doubt, please contact the guest editors.

Papers that focus mainly on eye tracking hardware and software as such will be relevant (only) if they make it clear how the advances reported open up new possibilities for the use of eye gaze in at least one of the ways listed above.


  • Empirical studies of eye gaze in human-human communication that provide new insight into the role of eye gaze and suggest implications for the use of eye gaze in intelligent systems. Examples include new empirical findings concerning eye gaze in human language processing, in human-vision processing, and in conversation management.
  • Algorithms and systems that incorporate eye gaze for human-computer interaction and human-robot interaction. Examples include gaze-based feedback to information systems; gaze-based attention modeling; exploiting gaze in automated language processing; and controlling the gaze behavior of embodied conversational agents or robots to enable grounding, turn-taking, and engagement.
  • Applications that demonstrate the value of incorporating eye gaze in practical systems to enable intelligent human-machine communication.

Special Issue Associate Editors

  • Elisabeth André, University of Augsburg, Germany

    (contact: andre[at]informatik[dot]

  • Joyce Chai, Michigan State University, USA


Affective Interaction in Natural Environments (Published in TiiS 1-1 and 1-3)

Aims and Scope

A vital requirement for social robots, virtual agents, and human-centered multimodal interfaces is the ability to infer the affective and mental states of humans and provide appropriate, timely output during sustained social interactions.

Examples include ensuring that the user is interested in maintaining the interaction or providing suitable empathic responses through the display of facial expressions, gesture, or generation of speech.

This special issue will cover computational techniques for the recognition and interpretation of human multimodal verbal and nonverbal behavior, models of mentalizing and empathizing for interaction, and multimedia techniques for the synthesis of believable social behavior supporting human-agent and human-robot interaction.

A key aim of the special issue is the identification and investigation of important open issues in real-time, affect-aware applications “in the wild” and especially in embodied interaction, i.e., with robots and embodied conversational agents. We encourage the submission of studies that provide new insights into the use of multimodal and multimedia techniques for enabling interaction between humans, robots, and virtual agents in naturalistic settings.

The special issue especially welcomes submission of contributions that focus on innovative intelligent technology and the way it is successfully integrated into the interaction cycle between users and virtual agents and robots, in line with the binocular view encouraged by TiiS.

Submissions can come from a variety of research areas, including naturalistic human-robot and human-computer interaction and multimedia human-computer interaction. The categories below cover most of the relevant topics, but they are not exhaustive. In case of doubt about the relevance of your topic, please contact the guest editors.


Focus on Recognition

  • Multimodal human affect and social behavior recognition, including:
  • Facial expressions
  • Body language
  • Speech
  • Physiological signals
  • Other modalities
  • Cognitive and affective “mentalizing”
  • Recognition of human behavior for implicit tagging

Focus on Generation

  • Multimedia expression generation in robots and virtual agents, including:
  • Gaze
  • Gestures
  • Facial expressions
  • Speech
  • Other modalities

Focus on Interaction

  • Emotion and cognitive state representation
  • Perception-action loops in agents/robots
  • Visual attention / user engagement with robots and embodied conversational agents
  • Social context-awareness and adaptation
  • Applications of methods and results in the above areas to interactive games, robots, and virtual agents


  • Multimodal corpora for training recognition systems
  • Multimodal corpora for modeling the behavior of agents and robots

Special Issue Associate Editors

  • Ginevra Castellano, Queen Mary University of London, UK

    (contact: ginevra[at]dcs[dot]qmul[dot]ac[dot]uk)

  • Kostas Karpouzis, National Technical University of Athens, Greece
  • Jean-Claude Martin, LIMSI-CNRS, France
  • Louis-Philippe Morency, University of Southern California, USA
  • Christopher Peters, Coventry University, UK
  • Laurel Riek, University of Cambridge, UK