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Let Me Ask You This: How Can a Voice Assistant Elicit Explicit User Feedback?
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Recommender Systems Handbook
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Cognitive Informatics for Biomedicine
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Exploring Privacy Concerns about Personal Sensing
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I Like It... I Like It Not: Evaluating User Ratings Noise in Recommender Systems
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InCarMusic: Context-Aware Music Recommendations in a Car
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Opinion-Driven Matrix Factorization for Rating Prediction
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Evaluating Voice Quality and Speech Synthesis Using Crowdsourcing
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Dialogues with Social Robots
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Is Spoken Language All-or-Nothing? Implications for Future Speech-Based Human-Machine Interaction
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Promoting attitude change and expressed willingness to take action toward climate change in college students
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Designing interfaces for explicit preference elicitation: a user-centered investigation of preference representation and elicitation process
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AI-Based Digital Assistants
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It’s only a computer: Virtual humans increase willingness to disclose
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Recommender system application developments: A survey
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Testing the latent factor structure and construct validity of the Ten-Item Personality Inventory
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Using CrowdFlower to Study the Relationship between Self-reported Violations and Traffic Accidents
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A simple procedure for the assessment of acceptance of advanced transport telematics
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Experience Sampling: Promises and Pitfalls, Strengths and Weaknesses
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Consequences of individual feedback on behavior in organizations.
inferredcites →https://doi.org/10.1080/10447318.2014.986642openalex-snapshot
Privacy Concerns for Use of Voice Activated Personal Assistant in the Public Space
inferredcites →https://doi.org/10.1109/cec.2009.84openalex-snapshot
Collaborative Feature-Combination Recommender Exploiting Explicit and Implicit User Feedback
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Age and gender factors in user acceptance of healthcare robots
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AGE DIFFERENCES IN TECHNOLOGY ADOPTION DECISIONS: IMPLICATIONS FOR A CHANGING WORK FORCE
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Accurately interpreting clickthrough data as implicit feedback
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Collaborative filtering with temporal dynamics
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When users become collaborators
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Comparison of implicit and explicit feedback from an online music recommendation service
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A user-centric evaluation framework for recommender systems
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Designing a scalable crowdsourcing platform
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"Like Having a Really Bad PA"
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Explicit In Situ User Feedback for Web Search Results
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Joint Deep Modeling of Users and Items Using Reviews for Recommendation
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Understanding How People Use Natural Language to Ask for Recommendations
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Accurately Interpreting Clickthrough Data as Implicit Feedback
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Towards an Optimal Dialog Strategy for Information Retrieval Using Both Open- and Close-ended Questions
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Voice Interfaces in Everyday Life
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Understanding the Long-Term Use of Smart Speaker Assistants
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The Impact of User Characteristics and Preferences on Performance with an Unfamiliar Voice User Interface
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Hey Google, Can I Ask You Something in Private?
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Explaining recommendations in an interactive hybrid social recommender
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Giving Voice to Silent Data: Designing with Personal Music Listening History
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Will Deleting History Make Alexa More Trustworthy?
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Understanding Fitness Tracker Users' Security and Privacy Knowledge, Attitudes and Behaviours
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"It's small talk, jim, but not as we know it."
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Interruptibility for In-vehicle Multitasking
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Privacy Norms for Smart Home Personal Assistants
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Measuring the Effectiveness of Privacy Policies for Voice Assistant Applications
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Refining the Test Phase of Usability Evaluation: How Many Subjects Is Enough?
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What the Voice Reveals: Within- and Between-Category Stereotyping on the Basis of Voice
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Does music listening in a social context alter experience? A physiological and psychological perspective on emotion
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Extending the Linear Model With R: Generalized Linear, Mixed Effects and Nonparametric Regression Models
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ESMAC: A Web-Based Configurator for Context-Aware Experience Sampling Apps in Ambulatory Assessment
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Computational Approaches to Dialogue
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Tell Me About Yourself: Using an AI-Powered Chatbot to Conduct Conversational Surveys with Open-ended Questions
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"Play music": User motivations and expectations for non-specific voice queries
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Rapidly exploring application design through speed dating
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures
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Powering an AI Chatbot with Expert Sourcing to Support Credible Health Information Access
inferred← citeshttps://doi.org/10.1145/3613904.3642193openalex-snapshot
Better to Ask Than Assume: Proactive Voice Assistants’ Communication Strategies That Respect User Agency in a Smart Home Environment
inferred← citeshttps://doi.org/10.1145/3613905.3650786openalex-snapshot
A Taxonomy for Human-LLM Interaction Modes: An Initial Exploration
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Interview AI-ssistant: Designing for Real-Time Human-AI Collaboration in Interview Preparation and Execution
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Envisioning AI Support during Semi-Structured Interviews Across the Expertise Spectrum
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What Happened to Scenario-Based Design in HCI?: A Scoping Review
inferred← citeshttps://doi.org/10.1145/3816046.3816218openalex-snapshot
AI Interviews the Interviewers: Practitioner Experience and Evaluation of Conversational AI Interviewing
inferred← citeshttps://doi.org/10.3389/fdata.2022.897381openalex-snapshot
Effects of Feature-Based Explanation and Its Output Modality on User Satisfaction With Service Recommender Systems
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VoiceBack: Design of Artificial Intelligence-Driven Voice-Based Feedback System for Customer-Agency Communication in Online Travel Services
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