论文标题
Rivendell：基于项目的学术搜索引擎
Rivendell: Project-Based Academic Search Engine
论文作者
论文摘要
在线数据库中找到相关的研究文献是所有研究人员的熟悉挑战。试图应对这一挑战的一般搜索方法分为两组：一次性搜索和终身搜索。我们观察到两种方法都忽略了研究领域的独特属性，并且受概念漂移的影响。我们认为，在搜索研究论文时，将终身搜索引擎与明确提供的上下文（项目）的结合提供了解决概念漂移问题的解决方案。我们为研究论文开发并部署了基于项目的元搜索引擎，称为Rivendell。使用Rivendell，我们对199个主题进行了实验，将基于项目的搜索性能与一次性和终身搜索引擎进行了比较，与终身搜索相比，基于项目的搜索的提高了高达12.8％。
Finding relevant research literature in online databases is a familiar challenge to all researchers. General search approaches trying to tackle this challenge fall into two groups: one-time search and life-time search. We observe that both approaches ignore unique attributes of the research domain and are affected by concept drift. We posit that in searching for research papers, a combination of a life-time search engine with an explicitly-provided context (project) provides a solution to the concept drift problem. We developed and deployed a project-based meta-search engine for research papers called Rivendell. Using Rivendell, we conducted experiments with 199 subjects, comparing project-based search performance to one-time and life-time search engines, revealing an improvement of up to 12.8 percent in project-based search compared to life-time search.
