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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/1-4020-5386-x_1openalex-snapshot
End-User Development: An Emerging Paradigm
inferredcites →https://doi.org/10.1007/11748625_16openalex-snapshot
iCAP: Interactive Prototyping of Context-Aware Applications
inferredcites →https://doi.org/10.1007/978-3-540-87479-9_12openalex-snapshot
Improving Maximum Margin Matrix Factorization
inferredcites →https://doi.org/10.1007/978-3-642-45135-5_5openalex-snapshot
Source Code-Based Recommendation Systems
inferredcites →https://doi.org/10.1007/b100615openalex-snapshot
Web mining : from web to semantic web : First European Web Mining Forum, EWMF 2003, Cavtat-Dubrovnik, Croatia, September 22, 2003 : invited and selected revised papers
inferredcites →https://doi.org/10.1007/s10791-009-9112-1openalex-snapshot
Adapting boosting for information retrieval measures
inferredcites →https://doi.org/10.1007/s10994-008-5073-7openalex-snapshot
Improving maximum margin matrix factorization
inferredcites →https://doi.org/10.1007/s10994-010-5205-8openalex-snapshot
Relational retrieval using a combination of path-constrained random walks
inferredcites →https://doi.org/10.1016/j.ijhcs.2018.12.008openalex-snapshot
A high-level semantic approach to End-User Development in the Internet of Things
inferredcites →https://doi.org/10.1016/j.jvlc.2014.03.005openalex-snapshot
Puzzle: A mobile application development environment using a jigsaw metaphor
inferredcites →https://doi.org/10.1017/s026988891100018xopenalex-snapshot
Review of the state of the art: discovering and associating semantics to tags in folksonomies
inferredcites →https://doi.org/10.1109/compsac.2012.11openalex-snapshot
A Source Code Recommender System to Support Newcomers
inferredcites →https://doi.org/10.1109/icdm.2008.22openalex-snapshot
Collaborative Filtering for Implicit Feedback Datasets
inferredcites →https://doi.org/10.1109/icdm.2010.129openalex-snapshot
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations
inferredcites →https://doi.org/10.1109/icdm.2011.134openalex-snapshot
SLIM: Sparse Linear Methods for Top-N Recommender Systems
inferredcites →https://doi.org/10.1109/mc.2016.51openalex-snapshot
Taking the Internet to the Next Physical Level
inferredcites →https://doi.org/10.1109/mc.2017.4041355openalex-snapshot
A Semantic Web Approach to Simplifying Trigger-Action Programming in the IoT
inferredcites →https://doi.org/10.1109/scam.2016.22openalex-snapshot
Collective Intelligence for Smarter API Recommendations in Python
inferredcites →https://doi.org/10.1109/scam30525.2013openalex-snapshot
2013 IEEE 13th International Working Conference on Source Code Analysis and Manipulation (SCAM)
inferredcites →https://doi.org/10.1109/tkde.2014.2327028openalex-snapshot
Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions
inferredcites →https://doi.org/10.1145/1060745.1060754openalex-snapshot
Improving recommendation lists through topic diversification
inferredcites →https://doi.org/10.1145/1278366.1278371openalex-snapshot
Generating semantically enriched user profiles for Web personalization
inferredcites →https://doi.org/10.1145/1639714.1639773openalex-snapshot
Knowledge infusion into content-based recommender systems
inferredcites →https://doi.org/10.1145/191666.191722openalex-snapshot
Repeat and predict—two keys to efficient text editing
inferredcites →https://doi.org/10.1145/2039320.2039324openalex-snapshot
A generic semantic-based framework for cross-domain recommendation
inferredcites →https://doi.org/10.1145/2365952.2365983openalex-snapshot
Sparse linear methods with side information for top-n recommendations
inferredcites →https://doi.org/10.1145/2507157.2507160openalex-snapshot
Evaluation of recommendations
inferredcites →https://doi.org/10.1145/2507157.2507171openalex-snapshot
Hybrid event recommendation using linked data and user diversity
inferredcites →https://doi.org/10.1145/2507157.2507172openalex-snapshot
Top-N recommendations from implicit feedback leveraging linked open data
inferredcites →https://doi.org/10.1145/2556195.2556259openalex-snapshot
Personalized entity recommendation
inferredcites →https://doi.org/10.1145/2556288.2557420openalex-snapshot
Practical trigger-action programming in the smart home
inferredcites →https://doi.org/10.1145/2600428.2609458openalex-snapshot
Exploring recommendations in internet of things
inferredcites →https://doi.org/10.1145/2645710.2645759openalex-snapshot
Using graded implicit feedback for bayesian personalized ranking
inferredcites →https://doi.org/10.1145/2750858.2805830openalex-snapshot
Supporting mental model accuracy in trigger-action programming
inferredcites →https://doi.org/10.1145/2835776.2835837openalex-snapshot
Collaborative Denoising Auto-Encoders for Top-N Recommender Systems
inferredcites →https://doi.org/10.1145/2858036.2858556openalex-snapshot
Trigger-Action Programming in the Wild
inferredcites →https://doi.org/10.1145/2926718openalex-snapshot
Sound and Music Recommendation with Knowledge Graphs
inferredcites →https://doi.org/10.1145/2950290.2950333openalex-snapshot
API code recommendation using statistical learning from fine-grained changes
inferredcites →https://doi.org/10.1145/3057858openalex-snapshot
Exploring End User Programming Needs in Home Automation
inferredcites →https://doi.org/10.1145/3057859openalex-snapshot
Empowering End Users to Customize their Smart Environments
inferredcites →https://doi.org/10.1145/3057861openalex-snapshot
Personalization of Context-Dependent Applications Through Trigger-Action Rules
inferredcites →https://doi.org/10.1145/3240323.3240361openalex-snapshot
Recurrent knowledge graph embedding for effective recommendation
inferredcites →https://doi.org/10.1145/581339.581402openalex-snapshot
Supporting reuse by delivering task-relevant and personalized information
inferredcites →https://doi.org/10.1561/1500000016openalex-snapshot
Learning to Rank for Information Retrieval
inferredcites →https://doi.org/10.18637/jss.v033.i01openalex-snapshot
Regularization Paths for Generalized Linear Models via Coordinate Descent
inferredcites →https://doi.org/10.3233/sw-2011-0025openalex-snapshot
The OWL API: A Java API for OWL ontologies
inferredcites →https://doi.org/10.4018/jswis.2009081901openalex-snapshot
Linked Data - The Story So Far
inferredcites →https://doi.org/10.48550/arxiv.1205.2618openalex-snapshot
BPR: Bayesian Personalized Ranking from Implicit Feedback
inferredcites →https://doi.org/10.5555/1460172.1460184openalex-snapshot
A multilayer ontology-based hybrid recommendation model
inferredcites →https://doi.org/10.5555/2019470.2019471openalex-snapshot
The OWL API: A Java API for OWL ontologies
inferredcites →https://doi.org/10.5555/2820668.2820675openalex-snapshot
Recommending features and feature relationships from requirements documents for software product lines
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.6811openalex-snapshot
Configuration approach for personalized travel mashup
inferred← citeshttps://doi.org/10.1007/978-3-030-64694-3_12openalex-snapshot
Learning to Recommend Trigger-Action Rules for End-User Development
inferred← citeshttps://doi.org/10.1007/978-3-031-34433-6_5openalex-snapshot
Defining Trigger-Action Rules via Voice: A Novel Approach for End-User Development in the IoT
inferred← citeshttps://doi.org/10.1007/978-3-031-34433-6_7openalex-snapshot
Understanding Concepts, Methods and Tools for End-User Control of Automations in Ecosystems of Smart Objects and Services
inferred← citeshttps://doi.org/10.1007/s00779-020-01457-5openalex-snapshot
User-defined semantics for the design of IoT systems enabling smart interactive experiences
inferred← citeshttps://doi.org/10.1016/j.asoc.2024.112163openalex-snapshot
TAP with ease: a generic recommendation system for trigger-action programming based on multi-modal representation learning
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.121065openalex-snapshot
A data fusion framework based on heterogeneous information network embedding for trigger-action programming in IoT
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.126198openalex-snapshot
User intention prediction for trigger-action programming rule using multi-view representation learning
inferred← citeshttps://doi.org/10.1016/j.iot.2023.100922openalex-snapshot
A deep learning model for natural language querying in Cyber–Physical Systems
inferred← citeshttps://doi.org/10.1016/j.procs.2024.09.657openalex-snapshot
Improvement of the rules selection process in FIS with genetic algorithms
inferred← citeshttps://doi.org/10.1080/0144929x.2021.1900396openalex-snapshot
Recommendations for creating trigger-action rules in a block-based environment
inferred← citeshttps://doi.org/10.1080/0144929x.2022.2071169openalex-snapshot
How do end-users program the Internet of Things?
inferred← citeshttps://doi.org/10.1080/0144929x.2026.2711012openalex-snapshot
From natural language to executable filter code: LLM-Assisted behavioural customisation in trigger–Action Platforms
inferred← citeshttps://doi.org/10.1109/icir70631.2026.11628311openalex-snapshot
Controlling Smart Environments with Mobile Augmented Reality and Recommender Systems
inferred← citeshttps://doi.org/10.1109/icme59968.2025.11209243openalex-snapshot
CAMCKG: A Framework for Trigger-Action Recommendation Combining Attention Mechanism and Continuous Kernel Graph Convolution
inferred← citeshttps://doi.org/10.1109/icws60048.2023.00015openalex-snapshot
Generating Scenario-Centric TAP Rules for Smart Homes by Mining Historical Event Logs
inferred← citeshttps://doi.org/10.1109/icws62655.2024.00037openalex-snapshot
Proactive Detection of Physical Inter-rule Vulnerabilities in IoT Services Using a Deep Learning Approach
inferred← citeshttps://doi.org/10.1109/jiot.2025.3532977openalex-snapshot
LLM4TAP: LLM-Enhanced TAP Rule Recommendation
inferred← citeshttps://doi.org/10.1109/jiot.2025.3579920openalex-snapshot
IoT Rule Generation With Cross-View Contrastive Learning and Perplexity-Based Ranking
inferred← citeshttps://doi.org/10.1109/jiot.2026.3693064openalex-snapshot
PaCR: An Agentic Preference-Aligned TAP Conflict Handling
inferred← citeshttps://doi.org/10.1109/tii.2021.3092774openalex-snapshot
Nonnegative Matrix Factorization Based Heterogeneous Graph Embedding Method for Trigger-Action Programming in IoT
inferred← citeshttps://doi.org/10.1109/tsmc.2021.3095524openalex-snapshot
A Data-Driven Method Using BRB With Data Reliability and Expert Knowledge for Complex Systems Modeling
inferred← citeshttps://doi.org/10.1109/vl/hcc60511.2024.00036openalex-snapshot
Beyond TAP: Piggybacking on IFTTT to Connect Triggers and Actions with JavaScript
inferred← citeshttps://doi.org/10.1142/s0218194021500510openalex-snapshot
Context-Aware Conversational Recommendation of Trigger-Action Rules in IoT Programming
inferred← citeshttps://doi.org/10.1145/3399715.3399833openalex-snapshot
A Visual Environment for End-User Creation of IoT Customization Rules with Recommendation Support
inferred← citeshttps://doi.org/10.1145/3447264openalex-snapshot
From Users’ Intentions to IF-THEN Rules in the Internet of Things
inferred← citeshttps://doi.org/10.1145/3524610.3527922openalex-snapshot
Accurate generation of trigger-action programs with domain-adapted sequence-to-sequence learning
inferred← citeshttps://doi.org/10.1145/3526114.3558776openalex-snapshot
iThem: Programming Internet of Things Beyond Trigger-Action Pattern
inferred← citeshttps://doi.org/10.1145/3532204openalex-snapshot
FortClash: Predicting and Mediating Unintended Behavior in Home Automation
inferred← citeshttps://doi.org/10.1145/3540250.3558913openalex-snapshot
RecipeGen++: an automated trigger action programs generator
inferred← citeshttps://doi.org/10.1145/3576842.3582328openalex-snapshot
FedRule: Federated Rule Recommendation System with Graph Neural Networks
inferred← citeshttps://doi.org/10.1145/3675401openalex-snapshot
Hybrid Prompt Learning for Generating Justifications of Security Risks in Automation Rules
inferred← citeshttps://doi.org/10.1145/3734863openalex-snapshot
Personalised Recommendations for Daily Automations Controlled by Mobile Augmented Reality
inferred← citeshttps://doi.org/10.1145/3771882.3771909openalex-snapshot
Human Control of Privacy and Security Aspects in IoT Settings
inferred← citeshttps://doi.org/10.2298/csis241126032sopenalex-snapshot
IoT based personalized online learning systems (Systematic Mapping Study)
inferred← citeshttps://doi.org/10.3390/app9245558openalex-snapshot
Non-Programmers Composing Software Services: A Confirmatory Study of the Mental Models and Design Challenges
inferred← citeshttps://doi.org/10.3390/computers14020063openalex-snapshot
IoT Integration Approaches into Personalized Online Learning: Systematic Review
inferred← citeshttps://doi.org/10.3390/designs8030043openalex-snapshot
Designing Home Automation Routines Using an LLM-Based Chatbot
inferred← citeshttps://doi.org/10.67537/ajnts2901011openalex-snapshot
Personalization Components and Algorithms in IoT Based Personalizing Online Learning Systems (A Systematic Review)
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