Abstract

Ethnopharmacology experts face several challenges when identifying and retrieving documents and resources related to their scientific focus. The volume of sources that need to be monitored, the variety of formats utilized, and the different quality of language use across sources present some of what we call “big data” challenges in the analysis of this data. This study aims to understand if and how experts can be supported effectively through intelligent tools in the task of ethnopharmacological literature research. To this end, we utilize a real case study of ethnopharmacology research aimed at the southern Balkans and the coastal zone of Asia Minor. Thus, we propose a methodology for more efficient research in ethnopharmacology. Our work follows an “expert–apprentice” paradigm in an automatic URL extraction process, through crawling, where the apprentice is a machine learning (ML) algorithm, utilizing a combination of active learning (AL) and reinforcement learning (RL), and the expert is the human researcher. ML-powered research improved the effectiveness and efficiency of the domain expert by 3.1 and 5.14 times, respectively, fetching a total number of 420 relevant ethnopharmacological documents in only 7 h versus an estimated 36 h of human-expert effort. Therefore, utilizing artificial intelligence (AI) tools to support the researcher can boost the efficiency and effectiveness of the identification and retrieval of appropriate documents.

Highlights

  • Ethnopharmacology is an interdisciplinary field of research based on both anthropological and scientific approaches [1]

  • From the beginning of the 19th century, the Balkans were transformed from protectorates of foreign empires into independent countries, but the cultural amalgam was so intertwined that it was embodied in the borders of these nation-states even after many generations

  • Even if hundreds of different ethnic groups exist in these countries, they are incorporated into the local societies in such a way that it is very difficult to investigate their origin [38]

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Summary

Introduction

Ethnopharmacology is an interdisciplinary field of research based on both anthropological and scientific approaches [1]. The development of a standard scientific approach to retrieve information from empirical use and define a pharmacological value from traditional preparations is considered a highly complex and challenging task, strongly filtered by the evolution of human history [2]. The challenge of discovering and enriching a body of knowledge with pre-existing scientific research has been a persistent need of the scientific community. Intelligent systems, known as “focused crawlers” [4], support domain experts in personalized searches. Such approaches combine the power of search engines with the user’s explicit feedback to identify the documents that maximally relate to the interest of the expert.

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