Optimal Enhancement of Location Aware Spatial Keyword Cover

Simran Lalwani, Tanmay Dixit, Ghandhrva Malhotra, Abhimanyu ., Shrikala Deshmukh, Snehal Chaudhary, Priyanka Paygude


Spatial Database more the uncommon word more is it associated to the life of every individual in several different ways. These spatial databases have objects that have certain keywords associated to represent their businesses, services provided or any specific features. Closest Keywords Search an associated problem is to process objects known as keyword cover, that together surrounds a set of query keywords that have a minimum inter – object distance and also are closer to the search location. Keyword Rating can affect various decision making situations that evaluate objects. Best Keyword Cover the most common version of Closest Keywords Search takes into consideration the minimum inter – object distance and the respective keyword ratings. The Baseline Algorithm tends to combine objects from different query keywords to exhibit candidate keyword cover. But the baseline algorithm fails to exhibit its performance level when query keywords increase in number. To overcome this drawback we use more scalable algorithm called keyword nearest neighbour expansion (keyword-NNE) that comparatively is more superior and shows a significant decrease in the number of candidate covers generated. To optimize the solution even more we use the distance of the query objects from the current location. Optimal Enhancement involves considering not only the user’s current location but also the actual travel path and time rather than the Euclidean distance.


Keyword search, k-NNE, Spatial database, user-ratings.


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