Content-aware recommender systems using semantic analysis

每天都有数以百万计的新闻故事在网上被阅读，而且越来越多的读者只为了一篇故事而停留在内容提供商的页面上。这对网站的收入和在线新闻机构保持相关性的能力产生了重大影响。Digital Cavalier Technology Services Inc.（该公司）提供智能个性化企业解决方案，生成内容推荐，鼓励用户阅读更多故事。为了实现这一目标，该公司融合了几种基于协同过滤的方法，并希望将语义分析整合到他们的推荐引擎中，从而产生可申请专利的IP，并创造额外的资金和创收机会。

Every day millions of news stories are read online, and there is an increasing tendency for readers to stay on the content provider's page for only one story. This has significant impact on the revenue for the site, and the ability of online news organizations to stay relevant. Digital Cavalier Technology Services Inc. (the company) provides smart personalization enterprise solutions that generate content recommendations that encourage users to read additional stories. The company fuses several collaborative filtering based approaches in order to accomplish this goal and would like to incorporate semantic analysis to their recommender engine generating patentable IP and creating additional funding and revenue generation opportunities.