Entity Recognition and Disambiguation for Natural-Language Spatial Search Queries

In our modern world, search engines have been proposed as one of the challenging research areas. One of the main issues in search engines studies is human computer interaction, which its aim is to understand user's needs. If there is no right query processing approach, the results will be invalid in most cases. Therefore, in this paper we present a new approach to process and analyze the queries for spatial search engines. Our algorithm is implemented in the three steps, including: iterative segmentation of the query, sub-queries processing by finding appropriate candidates for the location-names, the location-types and spatial relationships and finally checking the relationships among these candidates in validation phase. Generally using our method has two major advantages as the search engines can provide the capability of spatial analysis based on the specific process which leads to a better interaction between the users and the search application in geospatial realm and secondly because of the disambiguation technique, user reaches the more desirable result.