Name
Abstract | ||
|---|---|---|
Recent progress in information extraction has shown how to automatically build large ontologies from high-quality sources like Wikipedia. But knowledge evolves over time; facts have associated validity intervals. Therefore, ontologies should include time as a first-class dimension. In this paper, we introduce Timely YAGO, which extends our previously built knowledge base YAGO with temporal aspects. This prototype system extracts temporal facts from Wikipedia infoboxes, categories, and lists in articles, and integrates these into the Timely YAGO knowledge base. We also support querying temporal facts, by temporal predicates in a SPARQL-style language. Visualization of query results is provided in order to better understand of the dynamic nature of knowledge. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1145/1739041.1739130 | EDBT |
Keywords | Field | DocType |
timely yago knowledge base,wikipedia infoboxes,sparql-style language,knowledge evolves,dynamic nature,knowledge base yago,temporal predicate,temporal aspect,temporal fact,temporal knowledge,timely yago,information extraction,knowledge base,ontology,wikipedia,knowledge management | Ontology (information science),Data mining,Ontology,Information retrieval,Visualization,Computer science,Information extraction,Knowledge base,Database | Conference |
Citations | PageRank | References |
42 | 1.72 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yafang Wang | 1 | 134 | 13.56 |
| Mingjie Zhu | 2 | 89 | 4.32 |
| Lizhen Qu | 3 | 197 | 12.80 |
| Marc Spaniol | 4 | 897 | 61.13 |
| Gerhard Weikum | 5 | 12710 | 2146.01 |