Abstract
I present a new text mining approach combined with network analysis to quantify the distribution patterns of the associated geographical names on a transportation network. extract geographical names from user's search queries recorded in search engine query logs and compare the similarities of any pair of geographical names using Jaccard coefficient. I found that a set of associated geographical names for each geographical name shows a specific spatial distribution pattern on transportation network and define a measure for quantifying such characteristics. Furthermore, I discuss its characteristics and application for information navigation.
