Venue Classification of Research Papers in Scholarly Digital Libraries

Abstract

Open-access scholarly digital libraries crawl periodically a list of URLs in order to obtain appropriate collections of freely-available research papers. The metadata of the crawled papers, e.g., title, authors, and references, are automatically extracted before the papers are indexed in a digital library. The venue of publication is another important aspect about a scientific paper, which reflects its authoritativeness. However, the venue is not always readily available for a paper. Instead, it needs to be extracted from the references lists of other papers that cite the target paper. We explore a supervised learning approach to automatically classifying the venue of a research paper using information solely available from the content of the paper and show experimentally on a dataset of approximately 44,000 papers that this approach outperforms several baselines and prior work.