Kvasir: Seamless Integration of Latent Semantic Analysis-Based Content Provision into Web Browsing

被引：2

作者：

Wang, Liang ^{[1
]}

Tasoulis, Sotiris ^{[1
]}

Roos, Teemu ^{[1
]}

Kangasharju, Jussi ^{[1
]}

机构：

[1] Univ Helsinki, Dept Comp Sci, FIN-00014 Helsinki, Finland

来源：

WWW'15 COMPANION: PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB | 2015年

关键词：

Information Retrieval; Content-based Filter; Web Browsing; Latent Semantic Analysis; Random Projection; Big Data;

D O I：

10.1145/2740908.2742825

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The Internet is overloading its users with excessive information flows, so that effective content-based filtering becomes crucial in improving user experience and work efficiency. We build Kvasir, a semantic recommendation system, atop latent semantic analysis and other state-of-art technologies to seamlessly integrate an automated and proactive content provision service into web browsing. We utilize the power of Apache Spark to scale up Kvasir to a practical Internet service. Herein we present the architecture of Kvasir, along with our solutions to the technical challenges in the actual system implementation.

引用

页码：251 / 254

页数：4

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