A Survey of Recommendation Systems

Malik Sushma; Rana Anamika; Bansal Mamta

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A Survey of Recommendation Systems

机译：推荐系统调查

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摘要

Today's internet is able to discover almost any product or piece of information. The large amounts of unfiltered information returned by an internet query calls for filters able to validate and rank the available options. Recommender systems (RSs) are a software tool designed to qualify the options available and make suggestions that align with the user's requirements and expectations. This paper reviews some significant applications of RSS in various areas like videos, music, eCommerce sites, news, and many more. It also reviews various filtering techniques like collaborative, content based, and hybrid.

机译：今天的互联网能够发现几乎任何产品或信息。 Internet查询返回的大量未过滤信息呼叫能够验证和排列可用选项的过滤器。推荐系统（RSS）是一个软件工具，旨在限定可用的选项，并提出与用户的要求和期望保持一致的建议。本文评论了RSS在视频，音乐，电子商务网站，新闻等各种领域的一些重要应用。它还回顾了各种过滤技术，如协作，内容和混合。

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来源
《Information Resources Management Journal》 |2020年第4期|53-73|共21页
作者
Malik Sushma; Rana Anamika; Bansal Mamta;
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作者单位

Deemed Be Univ Shobhit Inst Engn & Technol Meerut Uttar Pradesh India;

Maharaja Surajmal Inst Technol Delhi India;

Shobhit Univ Meerut Uttar Pradesh India;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Collaborative Filtering (CF); Content Based (CB); Knowledge Based (KB); Recommender System (RS);

机译：协同过滤（CF）;基于内容（CB）;基于知识（KB）;推荐系统（RS）;

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A Survey of Recommendation Systems

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