
The Inverse Document Frequency (IDF) weighting method is based on the hypothesis that in the document collection the lower the frequency of a term is, the more important the term is as a subject word. This well-known hypothesis is, however, somewhat questionable because some low frequency terms turn out to be insufficient subject words. This study suggests the pivoted IDF weighting method for better retrieval effectiveness, on the assumption that medium frequency terms are more important than low frequency terms. We thoroughly evaluated this method on three test collections and it showed performance improvements especially at high ranks.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
