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It is believed that Web search queries are becoming more structurally complex over time. However, there has been no systematic study that quantifies such characteristics. In this thesis, we propose that queries are evolving into a unique linguistic system. We demonstrate proof of this hypothesis by examining the structure of Web queries by applying well-established techniques from natural language understanding. Preliminary results of these experiments show quantitative and qualitative proof that queries are not just some form of text between random sequences of words and natural language - they have distinct properties of their own.
citations 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). | 2 | |
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 |