Keyword suggestions are the basic feature of the search engine and it accesses relevant information. The naive user doesn’t know how to express their queries; keyword suggestion in web search assists users to access relevant information without any prior knowledge of how to express in queries. The keyword suggestion module can use the current location of a user and retrieve documents which are near to user location. The Euclidean distance is measured for user location and the documents locations. Accordingly the edge weight adjustment is done referring initial K-D graph. The keyword-document graph is used to map the keyword queries and the spatial distance between the resulting documents and the user location. The graph is browsed in random walk with restart, for calculating the highest score for better keyword query suggestion. The paper discusses techniques for the keyword suggestions and also about location-aware keyword query suggestion framework and improved partition based algorithm.

Akshay A. Bhujugade and Dattatraya V. Kodavade (2017). A Survey on Keyword Interrogation Implication on Document Vicinity Based on Location. International Journal of Computer Engineering In Research Trends, 4(11), 514-518. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1108.pdf

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