Name
Abstract | ||
|---|---|---|
In this article we present a study which demonstrates the ability of the method RaJoLink to uncover candidate hypotheses for future discoveries from rare terms in existing literature. The method is inspired by Swanson's ABC model approach to finding hidden relations from a set of articles in a given domain. The main novelty is in a semi-automated way of suggesting which relations might have more potential for new discoveries and are therefore good candidates for further investigations. In our previous articles we reported on a successful application of the method RaJoLink in the autism domain. To support the evaluation of the method with a well-known example from the literature, we applied it to the migraine domain, aiming at reproducing Swanson's finding of magnesium deficiency as a possible cause of migraine. Only literature which was available at the time of the Swanson's experiment was used in our test. As described in this study, in addition to actually uncovering magnesium as a candidate for formulating the hypothesis, RaJoLink pointed also to interferon, interleukin and tumor necrosis factor as candidates for potential discoveries connecting them with migraine. These connections were not published in the titles contemporary to the ones used in the experiment, but have been recently reported in several scientific articles. This confirms the ability of the RaJoLink method to uncover seeds of future discoveries in existing literature by using rare terms as a beacon. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-04125-9_16 | ISMIS |
Keywords | Field | DocType |
migraine domain,candidate hypothesis,rare term,future discovery,autism domain,magnesium deficiency,rajolink method,good candidate,nowadays literature,future discoveries,method rajolink,reproducing swanson,magnesium,tumor necrosis factor,knowledge discovery | Autism,Data mining,Computer science,Knowledge extraction,Novelty | Conference |
Volume | ISSN | Citations |
5722 | 0302-9743 | 5 |
PageRank | References | Authors |
0.53 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tanja Urbančič | 1 | 50 | 4.33 |
| Ingrid Petrič | 2 | 49 | 3.62 |
| Bojan Cestnik | 3 | 716 | 262.57 |