Name
Abstract | ||
|---|---|---|
The paper presents an approach to computational knowledge discovery through the mechanism of bisociation. Bisociative reasoning is at the heart of creative, accidental discovery (e.g., serendipity), and is focused on finding unexpected links by crossing contexts. Contextu- alization and linking between highly diverse and distributed data and knowledge sources is therefore crucial for the implementation of bisocia- tive reasoning. In the paper we explore these ideas on the problem of analysis of microarray data. We show how enriched gene sets are found by using ontology information as background knowledge in semantic sub- group discovery. These genes are then contextualized by the computation of probabilistic links to diverse bioinformatics resources. Preliminary ex- periments with microarray data illustrate the approach. |
Year | Venue | Field |
|---|---|---|
2010 | ICCC | Ontology,Information retrieval,Computer science,Microarray analysis techniques,Knowledge extraction,Probabilistic logic,Contextualization,Serendipity |
DocType | Citations | PageRank |
Conference | 6 | 0.59 |
References | Authors | |
10 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Igor Mozetiÿc | 1 | 6 | 0.59 |
| Nada Lavraÿc | 2 | 6 | 0.59 |
| Vid Podpeÿcan | 3 | 6 | 0.59 |
| Petra Kralj Novak | 4 | 228 | 12.75 |
| Helena Motaln | 5 | 15 | 1.08 |
| Marko Petek | 6 | 18 | 2.82 |
| Kristina Gruden | 7 | 34 | 5.49 |
| Hannu Toivonen | 8 | 4261 | 776.95 |
| Kimmo Kulovesi | 9 | 65 | 3.88 |