Gal A. Kaminka: Publications

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Rivendell: Project-Based Academic Search Engine

Teddy Lazebnik, Hanna Weitman, Yoav Goldberg, and Gal A. Kaminka. Rivendell: Project-Based Academic Search Engine. Technical Report 10.48550/ARXIV.2206.12926, arXiv, 2022.

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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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BibTeX

@techreport{rivendell22,
  doi = {10.48550/ARXIV.2206.12926},
  url = {https://arxiv.org/abs/2206.12926},
  number = {10.48550/ARXIV.2206.12926},
  author = {Lazebnik, Teddy and Weitman, Hanna and Goldberg, Yoav and Kaminka, Gal A.},
  OPTkeywords = {Information Retrieval (cs.IR), FOS: Computer and information sciences, FOS: Computer and information sciences},
  title = {Rivendell: Project-Based Academic Search Engine},
  institution = {arXiv},
  year = {2022},
  wwwnote = {}, 
  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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