Name
Abstract | ||
|---|---|---|
In literature-based creative knowledge discovery the goal is to identify interesting terms or concepts which relate different domains. We propose to support this cross-context link discovery process by inspecting outlier documents which are not in the mainstream domain literature. We have explored the utility of outlier documents, discovered by combining three classification-based outlier detection methods, in terms of their potential for bridging concept discovery in the migraine-magnesium cross-domain discovery problem and in the autism-calcineurin domain pair. Experimental results prove that outlier documents present a small fraction of a domain pair dataset that is rich on concept bridging terms. Therefore, by exploring only a small subset of documents, where a great majority of bridging terms are present and more frequent, the effort needed for finding cross-domain links can be substantially reduced. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-22218-4_44 | AIME '87 |
Keywords | Field | DocType |
cross-context link discovery process,literature-based creative knowledge discovery,autism-calcineurin domain pair,classification-based outlier detection method,concept discovery,domain pair dataset,mainstream domain literature,migraine-magnesium cross-domain discovery problem,outlier document,different domain | Data science,Data mining,Anomaly detection,Computer science,Bridging (networking),Outlier,Knowledge extraction,Artificial intelligence,Business process discovery,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Borut Sluban | 1 | 84 | 7.94 |
| Matjaž Juršič | 2 | 10 | 0.72 |
| Bojan Cestnik | 3 | 716 | 262.57 |
| Nada Lavrač | 4 | 989 | 72.19 |