December 14, 2017

New Article: Web Robot Detection in Academic Publishing

The following paper (preprint) was recently made available on arXiv.

Title

Web Robot Detection in Academic Publishing

Authors

Athanasios Lagopoulos
Aristotle University of ŒŒThessaloniki

Grigorios Tsoumakas
Aristotle University of ŒŒThessaloniki

Georgios Papadopoulos
Atypon Systems

Source
via arXiv

Abstract

Recent industry reports assure the rise of web robots which comprise more than half of the total web traffic. They not only threaten the security, privacy and efficiency of the web but they also distort analytics and metrics, doubting the veracity of the information being promoted. In the academic publishing domain, this can cause articles to be faulty presented as prominent and influential. In this paper, we present our approach on detecting web robots in academic publishing websites. We use different supervised learning algorithms with a variety of characteristics deriving from both the log files of the server and the content served by the website. Our approach relies on the assumption that human users will be interested in specific domains or articles, while web robots crawl a web library incoherently. We experiment with features adopted in previous studies with the addition of novel semantic characteristics which derive after performing a semantic analysis using the Latent Dirichlet Allocation (LDA) algorithm. Our real-world case study shows promising results, pinpointing the significance of semantic features in the web robot detection problem.

Direct to Full Text
7 pages; PDF.

Gary Price About Gary Price

Gary Price (gprice@mediasourceinc.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. Before launching INFOdocket, Price and Shirl Kennedy were the founders and senior editors at ResourceShelf and DocuTicker for 10 years. From 2006-2009 he was Director of Online Information Services at Ask.com, and is currently a contributing editor at Search Engine Land.

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