Rivendell: Project-Based Academic Search Engine
Teddy Lazebnik, Hanna Weitman, Yoav Goldberg, Gal A. Kaminka

TL;DR
Rivendell is a project-based meta-search engine designed to improve research literature retrieval by incorporating explicit project context, addressing concept drift, and outperforming traditional search methods in user experiments.
Contribution
This paper introduces Rivendell, a novel project-based search engine that combines domain-specific context with meta-search techniques to enhance research paper retrieval.
Findings
Up to 12.8% improvement in search performance over life-time search engines.
Effective handling of concept drift through project-based context.
Validated with 199 user experiments.
Abstract
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.
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Taxonomy
TopicsData Stream Mining Techniques · Mobile Crowdsensing and Crowdsourcing · Web Data Mining and Analysis
