
The search query is a set of words or phrases a user enters when looking for information on a specific topic or subject. Formulating a search query is a challenging task for most of users because they are required to express their anomalous states of knowledge. In the query reformulation stage, users modify their initial queries and submit new ones that more accurately reflect their information needs. Classification and Prediction are two forms of query analysis that can be used to extract models describing frequently used query classes or to predict the reformulation for the query.. An ideal solution might be that the system automatically generates a concise and informative summary for each perspective of the query. In our approach a model is constructed by analyzing queries described by the frequency of search, query is assumed to belong to a predefined class.
| 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). | 0 | |
| 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). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
