paper-with-me

Papers

A Unified Knowledge Representation and Context-aware Recommender System in Internet of Things

2018-05-10 · Yinhao Li, Awa Alqahtani, Ellis Solaiman, Charith Perera, Prem Prakash Jayaraman, Boualem Benatallah, Rajiv Ranjan

Within the rapidly developing Internet of Things (IoT), numerous and diverse physical devices, Edge devices, Cloud infrastructure, and their quality of service requirements (QoS), need to be represented within a unified specification in order to enable rapid IoT application development, monitoring, and dynamic reconfiguration. But heterogeneities among different configuration knowledge representation models pose limitations for acquisition, discovery and curation of configuration knowledge for coordinated IoT applications. This paper proposes a unified data model to represent IoT resource configuration knowledge artifacts. It also proposes IoT-CANE (Context-Aware recommendatioN systEm) to facilitate incremental knowledge acquisition and declarative context driven knowledge recommendation.

📄 PDF Abstract BibTeX arXiv:1805.04007

Code (0)

등록된 구현이 없습니다.

Tasks

Recommendation Systems

Similar Papers 제목 키워드 기반

Learn More from Less: Improving Conversational Recommender Systems via Contextual and Time-Aware Modeling

2021-11-16 · ACL ARR November 2021 11 · Anonymous

Conversational Recommender Systems (CRS) aims to perform recommendations through interactive conversations. Prior work on CRS tends to incorporate more external knowledge to enhance performance. Given the fact that too m…

Recommendation Systems

Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning

2022-06-19 · Xiaolei Wang, Kun Zhou, Ji-Rong Wen, Wayne Xin Zhao

Conversational recommender systems (CRS) aim to proactively elicit user preference and recommend high-quality items through natural language conversations. Typically, a CRS consists of a recommendation module to predict …

Language ModellingPrompt LearningRecommendation SystemsText Generation

CRFR: Improving Conversational Recommender Systems via Flexible Fragments Reasoning on Knowledge Graphs

2021-11-01 · EMNLP 2021 11 · Jinfeng Zhou, Bo wang, Ruifang He, Yuexian Hou

Although paths of user interests shift in knowledge graphs (KGs) can benefit conversational recommender systems (CRS), explicit reasoning on KGs has not been well considered in CRS, due to the complex of high-order and i…

Knowledge GraphsRecommendation SystemsText Generation

Improving Conversational Recommender System via Contextual and Time-Aware Modeling with Less Domain-Specific Knowledge

2022-09-23 · Lingzhi Wang, Shafiq Joty, Wei Gao, Xingshan Zeng 외

Conversational Recommender Systems (CRS) has become an emerging research topic seeking to perform recommendations through interactive conversations, which generally consist of generation and recommendation modules. Prior…

Recommendation Systems

DLRREC: Denoising Latent Representations via Multi-Modal Knowledge Fusion in Deep Recommender Systems

2025-11-29 · Jiahao Tian, Zhenkai Wang arxiv

Modern recommender systems struggle to effectively utilize the rich, yet high-dimensional and noisy, multi-modal features generated by Large Language Models (LLMs). Treating these features as static inputs decouples them…

Dimensionality ReductionCollaborative FilteringContrastive Learning