Indexing hs code- a hybrid indexer for an optimized search of geotagged data

초록

In case of unstructured data processing current technologies have developed a lot of solutions to process and provide insight into it, which has become paramount today due to the permeation of social media. Social media analytics extract data points by searching the most relevant textual reference and isolating textual data with location information. This increase the complexity of modern social media search engines. The indexer is imperative towards the performance of these engines. Geotagged data generated via modern social media technologies has augmented the need to enhance such search mechanisms designed for spatial data.Conventional spatial indexers designed to handle such data can accurately search spatial objects but with a considerable increase in seek time. This paper presents a hybrid spatial indexer based on "Hs-I" tree for the "Social Media Spatial Analytical (SMSA)" model. The purposed indexer is 17.768% faster when compared with the "Geo-hash" indexer. The model refers "CBDFI" model for base architecture and deploys the advantage of the "hs" code. The paper presents the comparison of the purposed indexer with various other spatial indexers and highlights its key points in terms of execution time.

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