closed discovery, the A and C are given to the approach which seeks to find the Bs which can link the two, thus testing a hypothesis about A and C. A number of systems to perform literature-based discovery have been developed over the years, extending the original idea of Don Swanson, and the evaluation of the quality of such systems is an active area of research. Some systems include web versions for increased user-friendliness. A common approach to many systems is the use of MeSH terms to represent scientific articles. This is used by the systems Manjal, BITOLA and LitLinker. One well-known system within the field is called Arrowsmith and is tailored to find connections between two disjoint sets of articles, an approach labeled "two-node" search. Another well-known system, LION LBD, uses PubTator for annotating PubMed scientific articles with concepts such as chemicals, genes/proteins, mutations, diseases and species; as well as sentence-level annotation of cancer hallmarks that describe fundamental cancer processes and behaviour. It uses co-occurrence metrics to rank relations between concepts and performs both open and closed discovery. While LBD systems are based on traditional statistical methods, other systems leverage sophisticated machine learning methods, like neural networks. Some LBD systems represent the connection between concepts as a knowledge graph, and thus employ techniques of graph theory. The graph-based representation is also the foundation for LBD systems that employ graph databases like Neo4J, enabling discovery via graph query languages such as Cypher. Graph-based LBD systems represent the relations between concepts using a different relation types, such as those in the UMLS Semantic Network. Some approaches go further and try to apply contextualized relations, an approach also used by the Gene Ontology for their Causal Activity Modeling (GO-CAM). Use of databases Besides extracting information from the body of scientific articles, LBD systems often employ structured knowledge from biocurated biological resources, like the Online Mendelian Inheritance in Men (OMIM). List of systems These are the published LBD systems, ordered by date of publication: 1986 - Arrowsmith 2000 - BITOLA V1 2001 - DAD 2003 - LitLinker 2004 - ACS 2004 - Manjal 2004 - IRIDESCENT 2005 - BITOLA V2 2006 - LitLinker V2 2007 - Arrowsmith V2 2008 - Anni 2.0 2008 - CoPub Discovery 2009 - RajoLink 2010 - Sem-BT 2015 - Obvio 2016 - Spark 2017 - Mine the gap 2019 - LION LBD Semantic typing A common task in