Name
Abstract | ||
|---|---|---|
Scientific literature is often fragmented, which implies that certain scientific questions can only be answered by combining information from various articles. In this paper, a new algorithm is proposed for finding associations between related concepts present in literature. To this end, concepts are mapped to a multidimensional space by a Hebbian type of learning algorithm using co-occurrence data as input. The resulting concept space allows exploration of the neighborhood of a concept and finding potentially novel relationships between concepts. The obtained information retrieval system is useful for finding literature supporting hypotheses and for discovering previously unknown relationships between concepts. Tests on artificial data show the potential of the proposed methodology. In addition, preliminary tests on a set of Medline abstracts yield promising results. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1002/asi.10392 | JASIST |
Keywords | Field | DocType |
literature-based discovery,proposed methodology,information retrieval system,artificial data,resulting concept space,scientific literature,multidimensional space,co-occurrence data,new algorithm,associative concept space,related concept,certain scientific question | Data mining,Scientific literature,Concept space,Associative property,Information retrieval,Computer science,Automation,Hebbian theory,Knowledge extraction,Literature-based discovery,MEDLINE | Journal |
Volume | Issue | ISSN |
55 | 5 | 1532-2882 |
Citations | PageRank | References |
32 | 1.65 | 22 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| C. Christiaan Van Der Eijk | 1 | 155 | 10.47 |
| Erik M. Van Mulligen | 2 | 633 | 44.63 |
| Jan A. Kors | 3 | 635 | 37.25 |
| Barend Mons | 4 | 430 | 33.31 |
| Jan Van Den Berg | 5 | 350 | 35.73 |