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- Work in ProgressApril 2023
Tacit Knowledge Elicitation for Shop-floor Workers with an Intelligent Assistant
CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing SystemsApril 2023, Article No.: 266, Pages 1–7https://doi.org/10.1145/3544549.3585755Many industries face the challenge of capturing workers’ knowledge to share it, particularly tacit knowledge. The operation of complex systems such as a manufacturing line is knowledge-intensive. Considering this knowledge’s breadth and dynamic nature, ...
- research-articleMarch 2022
“Mhm...” – Conversational Strategies For Product Search Assistants
CHIIR '22: Proceedings of the 2022 Conference on Human Information Interaction and RetrievalMarch 2022, Pages 36–46https://doi.org/10.1145/3498366.3505809Online retail has become a popular alternative to in-store shopping. However, unlike in traditional stores, users of online shops need to find the right product on their own without support from expert salespersons. Conversational search could provide ...
- research-articleOctober 2021
"Learn, Use, and (Intermittently) Abandon": Exploring the Practices of Early Smart Speaker Adopters in Urban India
Proceedings of the ACM on Human-Computer Interaction (PACMHCI), Volume 5, Issue CSCW2Article No.: 351, Pages 1–28https://doi.org/10.1145/3479495Since smart speakers were introduced to the Indian markets at the end of 2017, they have been adopted by hundreds of thousands households in India. While the scholarship has examined the long-term use of voice-based devices in western contexts, little is ...
- research-articleMay 2021
Guided Exploration: A Method for Guiding Novice Users in Interactive Memory Monitoring Tools
Proceedings of the ACM on Human-Computer Interaction (PACMHCI), Volume 5, Issue EICSArticle No.: 209, Pages 1–34https://doi.org/10.1145/3461731Many monitoring tools that help developers in analyzing the run-time behavior of their applications share a common shortcoming: they require their users to have a fair amount of experience in monitoring applications to understand the used terminology and ...
- research-articleFebruary 2021
A Review of Cognitive Assistants for Healthcare: Trends, Prospects, and Future Directions
- Sarah Masud Preum,
- Sirajum Munir,
- Meiyi Ma,
- Mohammad Samin Yasar,
- David J. Stone,
- Ronald Williams,
- Homa Alemzadeh,
- John A. Stankovic
ACM Computing Surveys (CSUR), Volume 53, Issue 6Article No.: 130, Pages 1–37https://doi.org/10.1145/3419368Healthcare cognitive assistants (HCAs) are intelligent systems or agents that interact with users in a context-aware and adaptive manner to improve their health outcomes by augmenting their cognitive abilities or complementing a cognitive impairment. ...
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- research-articleOctober 2020
Embracing Companion Technologies
NordiCHI '20: Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping SocietyOctober 2020, Article No.: 31, Pages 1–11https://doi.org/10.1145/3419249.3420134As an increasing number of interactive devices offer human-like assistance, there is a growing need to understand our experience of interactive agents. When interactive artefacts become intertwined in our everyday experience, we need to make sure that ...
- short-paperSeptember 2020
Learning software assistant that support senior citizen in creating contributions for a community app
MuC '20: Proceedings of Mensch und Computer 2020September 2020, Pages 449–453https://doi.org/10.1145/3404983.3410023Participation and inclusion in social life, as well as social exchange and sharing, often take place on the Internet. The community app meinDorf55+ is designed to support senior citizens to strengthen their social participation. It has been shown that ...
- research-articleJuly 2020
Effects of Proactive Dialogue Strategies on Human-Computer Trust
UMAP '20: Proceedings of the 28th ACM Conference on User Modeling, Adaptation and PersonalizationJuly 2020, Pages 107–116https://doi.org/10.1145/3340631.3394840Intelligent computer systems aim at providing user-assistance for challenging tasks, like decision-making, planning, or learning. For offering optimal assistance, it is essential for such systems to decide when to be reactive or proactive and how active ...
- research-articleJune 2020
Intelligent Task Recognition: Towards Enabling Productivity Assistance in Daily Life
- Jonathan Liono,
- Mohammad Saiedur Rahaman,
- Flora D. Salim,
- Yongli Ren,
- Damiano Spina,
- Falk Scholer,
- Johanne R. Trippas,
- Mark Sanderson,
- Paul N. Bennett,
- Ryen W. White
ICMR '20: Proceedings of the 2020 International Conference on Multimedia RetrievalJune 2020, Pages 472–478https://doi.org/10.1145/3372278.3390703We introduce the novel research problem of task recognition in daily life. We recognize tasks such as project management, planning, meal-breaks, communication, documentation, and family care. We capture Cyber, Physical, and Social (CPS) activities of 17 ...
- research-articleMay 2019
Chatbots, Humbots, and the Quest for Artificial General Intelligence
CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing SystemsMay 2019, Paper No.: 209, Pages 1–11https://doi.org/10.1145/3290605.3300439What began as a quest for artificial general intelligence branched into several pursuits, including intelligent assistants developed by tech companies and task-oriented chatbots that deliver more information or services in specific domains. Progress ...
- research-articleMarch 2019
Learning About Work Tasks to Inform Intelligent Assistant Design
- Johanne R. Trippas,
- Damiano Spina,
- Falk Scholer,
- Ahmed Hassan Awadallah,
- Peter Bailey,
- Paul N. Bennett,
- Ryen W. White,
- Jonathan Liono,
- Yongli Ren,
- Flora D. Salim,
- Mark Sanderson
CHIIR '19: Proceedings of the 2019 Conference on Human Information Interaction and RetrievalMarch 2019, Pages 5–14https://doi.org/10.1145/3295750.3298934Intelligent assistants can serve many purposes, including entertainment (e.g. playing music), home automation, and task management (e.g. timers, reminders). The role of these assistants is evolving to also support people engaged in work tasks, in ...
- research-articleJanuary 2019
Characterizing and Predicting Email Deferral Behavior
- Bahareh Sarrafzadeh,
- Ahmed Hassan Awadallah,
- Christopher H. Lin,
- Chia-Jung Lee,
- Milad Shokouhi,
- Susan T. Dumais
WSDM '19: Proceedings of the Twelfth ACM International Conference on Web Search and Data MiningJanuary 2019, Pages 627–635https://doi.org/10.1145/3289600.3291028Email triage involves going throughunhandled emails and deciding what to do with them. This familiar process can become increasingly challenging as the number of unhandled email grows. During a triage session, users commonlydefer handling emails that ...
- research-articleApril 2018
Detecting Absurd Conversations from Intelligent Assistant Logs by Exploiting User Feedback Utterances
WWW '18: Proceedings of the 2018 World Wide Web ConferenceApril 2018, Pages 147–156https://doi.org/10.1145/3178876.3185992Intelligent assistants, such as Siri, are expected to converse comprehensibly with users. To facilitate improvement of their conversational ability, we have developed a method that detects absurd conversations recorded in intelligent assistant logs by ...
- research-articleJune 2017
Designing Intelligent Assistant through User Participations
DIS '17: Proceedings of the 2017 Conference on Designing Interactive SystemsJune 2017, Pages 173–177https://doi.org/10.1145/3064663.3064733Today, intelligent assistants, such as Apple's Siri, becoming a part of our everyday life. While there have been many studies focused on technologies, there are no studies dealing with design issues at the initial stage of the design, the stage prior to ...
- research-articleJanuary 2017
A Multi-model Approach in Developing an Intelligent Assistant for Diagnosis Recommendation in Clinical Health Systems
Procedia Computer Science (PROCS), Volume 121, Issue CJanuary 2017, Pages 534–541https://doi.org/10.1016/j.procs.2017.11.071Clinical health information systems capture massive amounts of unstructured data from various health and medical facilities. This study utilizes unstructured patient clinical text data to develop an intelligent assistant that can identify possible ...
- invited-talkOctober 2016
Duer: Intelligent Personal Assistant
CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge ManagementOctober 2016, Page 427https://doi.org/10.1145/2983323.2983372Intelligent personal assistant is widely recognized as a more natural and efficient way of human-computer interaction, which has attracted extensive interests from both academia and industry. In this talk, I describe Duer, Baidu's intelligent personal ...
- research-articleJuly 2016
Analyzing and Predicting Task Reminders
UMAP '16: Proceedings of the 2016 Conference on User Modeling Adaptation and PersonalizationJuly 2016, Pages 7–15https://doi.org/10.1145/2930238.2930239Automated personal assistants such as Siri, Cortana, and Google Now provide services to help users accomplish tasks, including tools to set reminders. We study how people specify and use reminders. Our study analyzes a sample of six months of logs of ...
- research-articleJuly 2016
Predicting User Satisfaction with Intelligent Assistants
SIGIR '16: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information RetrievalJuly 2016, Pages 45–54https://doi.org/10.1145/2911451.2911521There is a rapid growth in the use of voice-controlled intelligent personal assistants on mobile devices, such as Microsoft's Cortana, Google Now, and Apple's Siri. They significantly change the way users interact with search systems, not only because of ...
- research-articleMarch 2016
Understanding User Satisfaction with Intelligent Assistants
- Julia Kiseleva,
- Kyle Williams,
- Jiepu Jiang,
- Ahmed Hassan Awadallah,
- Aidan C. Crook,
- Imed Zitouni,
- Tasos Anastasakos
CHIIR '16: Proceedings of the 2016 ACM on Conference on Human Information Interaction and RetrievalMarch 2016, Pages 121–130https://doi.org/10.1145/2854946.2854961Voice-controlled intelligent personal assistants, such as Cortana, Google Now, Siri and Alexa, are increasingly becoming a part of users' daily lives, especially on mobile devices. They introduce a significant change in information access, not only by ...
- short-paperNovember 2015
Leveraging Behavioral Patterns of Mobile Applications for Personalized Spoken Language Understanding
ICMI '15: Proceedings of the 2015 ACM on International Conference on Multimodal InteractionNovember 2015, Pages 83–86https://doi.org/10.1145/2818346.2820781Spoken language interfaces are appearing in various smart devices (e.g. smart-phones, smart-TV, in-car navigating systems) and serve as intelligent assistants (IAs). However, most of them do not consider individual users' behavioral profiles and ...