• V.REVATHI
• Dr.K.SARASWATHI

Emerging needs lead to detect user’s location for providing the various targeted services to the user. Location detection of the user has become important and it has indulged many researched in this field. Application uses the location information to provide the targeted service to the user accurately. The clustering of location data based on frequent position deviation, leads to discrete large cluster with huge gap, which is considered as challenging issue. In order to reduce the inter distance between the clusters, in this paper, a new locale detection approach is proposed. This is based on subspace clustering model on the location traces. The proposed clustering model removes irrelevant location information by reducing the dimensionality of data point. Further the gap between the clusters is reduced by using cooperative discovery model such as fingerprint matching and activity matching. In addition, proximity of the user is computed to gather the location data between users in order to reduce the inner cluster distance. Finally Spatio Temporal clustering is employed on the generated location data to produce the targeted service to user on place of interest. The experimental analysis of the proposed approaches on the simulated dataset proves that it is reliable and accurate against performance computed with existing solutions.

Targeted Services, User patterns, Location Mining, Spatio Temporal Clustering.

"A NOVEL LOCALE DETECTION APPROACH FOR LOCATION BASED SERVICES USING SUBSPACE CLUSTERING OF THE LOCATION TRACES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 11, page no.372-375, November-2019, Available :http://www.jetir.org/papers/JETIR1907T25.pdf

"A NOVEL LOCALE DETECTION APPROACH FOR LOCATION BASED SERVICES USING SUBSPACE CLUSTERING OF THE LOCATION TRACES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 11, page no. pp372-375, November-2019, Available at : http://www.jetir.org/papers/JETIR1907T25.pdf