Survey of Semantics-Based Recommendation Algorithms

HUANG Zhen-hua; ZHANG Jia-wen; ZHANG Bo; YU Jian; XIANG Yang; HUANG De-shuang

doi:10.3969/j.issn.0372-2112.2016.09.035

您当前的位置：

首页 >

文章列表页 >

Survey of Semantics-Based Recommendation Algorithms

更新时间：2025-07-16

- Survey of Semantics-Based Recommendation Algorithms
- Acta Electronica Sinica Vol. 44, Issue 9, Pages: 2262-2275(2016)
- 作者机构：
  
  1. 同济大学电子与信息工程学院,上海,201804
  2. 上海师范大学信息与机电工程学院,上海,200234
  3. 同济大学电子与信息工程学院,上海,201804
  4. 上海师范大学信息与机电工程学院,上海,200234
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61272268);Shanghai Municipal Youth Science and Technology Star project (No.15QA1403900);Program for New Century Excellent Talents in University of Ministry of Education of China (No.NCET-12-0413);National 973 Project (No.2014CB340404);Application Program of Fok Ying-Tong Education Foundation (No.142002);Funded by Fundamental Research Funds for the Central Universities
- DOI：10.3969/j.issn.0372-2112.2016.09.035
  CLC： TN911.23
- Published Online：25 September 2016，
  
  Published：2016
- 稿件说明：
移动端阅览
HUANG Zhen-hua, ZHANG Jia-wen, ZHANG Bo, et al. Survey of Semantics-Based Recommendation Algorithms[J]. Acta Electronica Sinica, 2016, 44(9): 2262-2275.
DOI：

HUANG Zhen-hua, ZHANG Jia-wen, ZHANG Bo, et al. Survey of Semantics-Based Recommendation Algorithms[J]. Acta Electronica Sinica, 2016, 44(9): 2262-2275. DOI： 10.3969/j.issn.0372-2112.2016.09.035.

摘要

近年来，语义推荐技术已成为信息服务领域的一个研究热点和重点.与传统的推荐算法相比，语义推荐算法在实时性、鲁棒性和推荐质量等方面具有显著的优势.针对语义推荐算法的国内外研究现状、进展，从四个角度进行归纳和总结，即基于语义的内容推荐算法、基于语义的协同过滤推荐算法、基于语义的混合推荐算法以及基于语义的社会化推荐算法，旨在尽可能全面地对语义推荐算法进行细致的介绍与分析，为相关研究人员提供有价值的学术参考.最后，立足于研究现状的分析与把握，对当前语义推荐算法所面临的挑战与发展趋势进行了展望.

Abstract

Semantics-based recommendation technology has recently received a lot of attention in information services community.Compared with traditional recommendation algorithms

semantics-based recommendation algorithms have the marked advantages in the aspects of real-timing

robustness and recommendation quality.From the status and progress of domestic and foreign research

we summarize the following four aspects:semantics-based content recommendation algorithms

semantics-based collaborative filtering recommendation algorithms

semantics-based hybrid recommendation algorithms

and semantics-based social recommendation algorithms.And this paper is expected to provide a worthwhile reference for relevant researchers by detailedly analyzing semantics-based recommendation algorithms.Finally

we show readers the challenges and future research directions in this field.

关键词

Keywords

references

Views

1344

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Progressive Image Content Understanding Based on Multi-Level Image Description Model

A Collaborative Recommendation Algorithm Based on Heuristic Clustering Model and Category Similarity

A Constrained Trust Recommendation Using Probabilistic Matrix Factorization

On the Formal Definition and Analysis of Stereotype in UML

Cross-Domain Recommendation Algorithm Based on Sharing Knowledge Pattern

Related Author

ZHANG Yu-jin

GAO Yong-ying

PAN Jun-chi

WU Yi-tao

ZHANG Xing-ming

WANG Xing-mao

HAN Qi-long

DONG Yu-xin

Related Institution

Department of Electronic Engineering, Tsinghua University

国家数字交换系统工程技术研究中心

College of Computer Science and Technology, Harbin Engineering University

Software Institute, School of Electronics Engineering and Computer Science, Peking University

School of Computer and Information Technology, Beijing Jiaotong University

⁰