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User intention prediction for trigger-action programming rule using multi-view representation learning

EXPERT SYSTEMS WITH APPLICATIONS 2025年 267卷

作者： Wu, Gang Hu, Liang Hu, Yuxiao Xing, Yongheng Wang, Feng Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Minist Educ Engn Res Ctr Network Technol & Applicat Software Changchun 130012 Peoples R China

trigger-action programming (TAP) allows users to create rules for automating smart devices and Internet services, such as "If a person is leaving, then turn off the air conditioner". User intention, as the internal driving force behind rule creation, plays a crucial role in understanding user demands. While existing research can easily identify users' explicit demands, such as turning off the air conditioner, it often fails to recognize implicit intentions, such as energy saving. Predicting user intention presents several challenges, including (1) contextual dependencies between triggers and actions that lead to different intentions when users combine various functions, (2) identifying user intention in short function description texts, and (3) entities with similar functions that do not reflect user intentions due to a lack of domain-specific knowledge. To address these challenges, we propose a multi-view representation learning-based framework, MvTAP, jointly in (1) user view, (2) developer view, and (3) knowledge view. In MvTAP, we first design different methods to learn the representation of the three views, respectively. We then propose a transformer-based method to fuse the representations of these views. User intention prediction is formulated as a multi-label classification task. The effectiveness of MvTAP is validated using a real-world IFTTT dataset. Experimental results show that the proposed framework can effectively predict user intentions in TAP rules.

关键词： Internet of Things trigger-action programming User intention prediction Multi-view representation learning

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trigger-action programming for Personalising Humanoid Robot Behaviour 19

Trigger-Action Programming for Personalising Humanoid Robot ...

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CHI Conference on Human Factors in Computing Systems (CHI)

作者： Leonardi, Nicola Manca, Marco Paterno, Fabio Santoro, Carmen CNR ISTI HIIS Lab Pisa Italy

ISBN: (纸本)9781450359702

In the coming years humanoid robots will be increasingly used in a variety of contexts, thereby presenting many opportunities to exploit their capabilities in terms of what they can sense and do. One main challenge is to design technologies that enable those who are not programming experts to personalize robot behaviour. We propose an end-user development solution based on trigger-action personalization rules. We describe how it supports editing such rules and its underlying software architecture, and report on a user test that involved end user developers. The test results show that users were able to perform the robot personalization tasks with limited effort, and found the trigger-action environment usable and suitable for the proposed tasks. Overall, we show the potential for using trigger-action programming to make robot behaviour personalization possible even to people who are not professional software developers.

关键词： End User Development Robot Personalization trigger-action programming

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trigger-action programming for Context-Aware Elderly Support in Practice 18

Trigger-Action Programming for Context-Aware Elderly Support...

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14th International Conference on Advanced Visual Interfaces (AVI)

作者： Chesta, Cristina Corcella, Luca Manca, Marco Paterno, Fabio Santoro, Carmen Reply SPA Turin Italy CNR ISTI HIIS Lab Pisa Italy

ISBN: (纸本)9781450356169

Remote monitoring services should be strongly personalised to the specific needs, preferences, abilities and motivations of elderly, a population segment whose characteristics can largely vary and even dynamically evolve over time for the same individual, depending on changing needs and usage contexts. We present a demo showing how a platform supporting End User Development (EUD) of context-dependent applications has been customized for remotely assisting elderly people at home. The user-editable personalisation features are specified by using trigger-action rules. The platform has been integrated with various sensors and appliances, and an application for remotely monitoring older adults at home. The resulting environment supports the possibility of creating trigger-action rules that can actually be executed when relevant sensors indicate that specific events or conditions occurred.

关键词： trigger-action programming Elderly EUD

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trigger-action programming in the Wild: An Analysis of 200,000 IFTTT Recipes 16

Trigger-Action Programming in the Wild: An Analysis of 200,0...

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34th Annual CHI Conference on Human Factors in Computing Systems (CHI4GOOD)

作者： Ur, Blase Ho, Melwyn Pak Yong Brawner, Stephen Lee, Jiyun Mennicken, Sarah Picard, Noah Schulze, Diane Littman, Michael L. Brown Univ Providence RI 02912 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA Univ Zurich CH-8006 Zurich Switzerland

ISBN: (纸本)9781450333627

While researchers have long investigated end-user programming using a trigger-action (if-then) model, the website IFTTT is among the first instances of this paradigm being used on a large scale. To understand what IFTTT users are creating, we scraped the 224,590 programs shared publicly on IFTTT as of September 2015 and are releasing this dataset to spur future research. We characterize aspects of these programs and the IFTTT ecosystem over time. We find a large number of users are crafting a diverse set of end-user programs-over 100,000 different users have shared programs. These programs represent a very broad array of connections that appear to fill gaps in functionality, yet users often duplicate others' programs.

关键词： IFTTT End-User programming End-User Composition trigger-action programming Internet of Things (IoT)

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A Semantic Web Approach to Simplifying trigger-action programming in the IoT

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COMPUTER 2017年第11期50卷 18-24页

作者： Corno, Fulvio De Russis, Luigi Roffarello, Alberto Monge Politecn Torino Dept Control & Comp Engn Turin Italy

End-user programming environments for the IoT such as IFTTT rely on a multitude of low-level trigger-action rules that categorize devices and services by technology or brand. EUPont is a Semantic Web ontology that enables users to meet their needs with fewer, higher-level rules that can be adapted to different contextual situations and as-yet-unknown IoT devices and services.

关键词： end-user development Internet of Things IoT Semantic Web trigger-action programming ontology IFTTT EUPont semantic reasoning programming the World

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A Recommendation System for trigger-action programming Rules via Graph Contrastive Learning

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SENSORS 2024年第18期24卷 6151页

作者： Kuang, Zhejun Xiong, Xingbo Wu, Gang Wang, Feng Zhao, Jian Sun, Dawen Changchun Univ Coll Comp Sci & Technol Changchun 130022 Peoples R China Jilin Prov Key Lab Human Hlth Status Identificat F Changchun 130022 Peoples R China Changchun Univ Key Lab Intelligent Rehabil & Barrier Free Disable Minist Educ Changchun 130022 Peoples R China Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China

trigger-action programming (TAP) enables users to automate Internet of Things (IoT) devices by creating rules such as "IF *** is triggered, THEN *** is executed". As the number of IoT devices grows, the combination space between the functions provided by devices expands, making manual rule creation time-consuming for end-users. Existing TAP recommendation systems enhance the efficiency of rule discovery but face two primary issues: they ignore the association of rules between users and fail to model collaborative information among users. To address these issues, this article proposes a graph contrastive learning-based recommendation system for TAP rules, named GCL4TAP. In GCL4TAP, we first devise a data partitioning method called DATA2DIV, which establishes cross-user rule relationships and is represented by a user-rule bipartite graph. Then, we design a user-user graph to model the similarities among users based on the categories and quantities of devices that they own. Finally, these graphs are converted into low-dimensional vector representations of users and rules using graph contrastive learning techniques. Extensive experiments conducted on a real-world smart home dataset demonstrate the superior performance of GCL4TAP compared to other state-of-the-art methods.

关键词： Internet of Things trigger-action programming rule recommendation graph contrastive learning

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DIY Digital Interventions: Behaviour Change with trigger-action programming

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Proceedings of the ACM on Human-Computer Interaction 2024年第MHCI期8卷 1-28页

作者： Scott, Ava Elizabeth Reicherts, Leon Purohit, Aditya Kumar Hossain, Elahi Stefanidi, Evropi Wagener, Nadine Schöning, Johannes Rogers, Yvonne Holzer, Adrian University College London London United Kingdom GmbH Bochum Germany University of Bremen Bremen Germany University of St. Gallen St. Gallen Switzerland University of Neuchâtel Neuchâtel Switzerland

Whether it is sleep, diet, or procrastination, changing behaviours can be challenging. Individuals could design and build their own personalised digital interventions to help them reach their goals, but little is known about this process. Building upon previous research we propose the Behaviour Change with trigger-action programming (BC-TAP) model which describes how individuals could bridge the gap between their current and desired behaviour through the creation of 'Do-It-Yourself' (DIY) digital interventions. We conducted a two-day participatory workshop based on the BC-TAP model with 28 participants. Participants articulated plans to change a behaviour of their choice and represented these plans in mobile device automations. After using their interventions for up to three weeks, participants reflected on their experience. Our findings report opportunities and challenges at each stage of the process. While formulating a digital proxy for certain behaviours was challenging, both failures and successes facilitated participants' awareness of their behaviour, and their ability to change it. © 2024 Owner/Author.

关键词： automations behaviour change computational thinking end-user programming implementation intentions self-reflection trigger-action programming wellbeing

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ImAtHome: Making trigger-action programming easy and fun

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JOURNAL OF VISUAL LANGUAGES AND COMPUTING 2017年 42卷 60-75页

作者： Fogli, Daniela Peroni, Matteo Stefini, Claudia Univ Brescia Dept Informat Engn Via Branze 28 I-25123 Brescia Italy

ImAtHome is an iOS application for smart home configuration and management built over Apple Home-Kit, a framework for communicating with and controlling home automation accessories. This paper describes the design and development of the visual interaction language made available in ImAtHome for empowering end users, without programming skills, to create event-condition-action rules that control home behavior. It can be regarded as an alternative approach to traditional trigger-action programming interfaces, where the user must define such rules by means of "if-then" constructs. Last but not least, attention has been put to make the interaction style as much coherent as possible with other iOS applications. The paper finally presents a user experiment, carried out with 30 participants according to a between-subject protocol, to evaluate the usability of ImAtHome and compare it with the official app for home automation recently released by Apple. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： End-user development Smart home trigger-action programming Event-condition-action rules

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Making the Intelligent Home Smart Through Touch-Control trigger-action programming

Making the Intelligent Home Smart Through Touch-Control Trig...

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International 360 Degree Summit on Applications for Future Internet (AFI360)

作者： Wang, Guan Littman, Michael L. Brown Univ Providence RI 02912 USA

ISBN: (纸本)9783319496221;9783319496214

We introduces a new UI model of trigger-action programming (TAP), that allows users to program through touch-control interfaces to create complicated tasks easily. We present three different user interfaces (UI), for each user interface, we analyze its advantages, limitations, and potential utility. We explain how our UIs can mitigate the problems of TAP caused by ambiguity and demonstrate why our UIs will benefit people without programming backgrounds.

关键词： trigger-action programming Touch-control interface Smart home End-user programming

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Supporting Mental Model Accuracy in trigger-action programming 15

Supporting Mental Model Accuracy in Trigger-Action Programmi...

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ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp)

作者： Huang, Justin Cakmak, Maya Univ Washington Dept Comp Sci & Engn 185 Stevens Way Seattle WA 98195 USA

ISBN: (纸本)9781450335744

trigger-action programming is a simple programming model that enables users to create rules that automate behavior of smart homes, devices, and online services. Existing trigger-action programming systems, such as if-this-then-that (IFTTT), already have millions of users worldwide;however, their oversimplification limits the expressivity of the programs that can be created. While extensions of IFTTT to allow more complex programs have been proposed, previous work neglects a key distinction between different trigger types (states and events) and action types (instantaneous, extended, and sustained actions). In this paper, we systematically study the impact of these differences through two user studies that reveal: (i) inconsistencies in interpreting the behavior of trigger-action programs and (ii) errors made in creating programs with a desired behavior. Based on a characterization of these issues, we offer recommendations for improving the IFTTT interface so as to mitigate issues that arise from mental model inaccuracies.

关键词： trigger-action programming IFTTT smart homes

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