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Final year IEEE projects 2016 based on Java Data Mining
  • Final year IEEE projects 2016 based on Java Data Mining

Location Aware Keyword Query Suggestion Based on Document Proximity

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Location Aware Keyword Query Suggestion Based on Document Proximity

In web search, to help the users to access relevant information without having to know how to precisely express their queries keyword suggestion is used. The locations of the users and the query results; i.e., the spatial proximity of a user to the retrieved results is not taken as a factor in the recommendation are not considered by the Existing keyword suggestion techniques.

However, the relevance of search results in many applications (e.g., location-based services) is known to be correlated with their spatial proximity to the query issuer. The proposed system provides a location-aware keyword query suggestion framework.

To capture both semantic relevance between keyword queries and the spatial distance between the resulting documents and the user location a weighted keyword-document graph is proposed. The graph is browsed in a random-walk-with-restart fashion, to select the keyword queries with the highest scores as suggestions.

The partition-based approach outperforms the baseline algorithm by up to an order of magnitude. The appropriateness of proposed framework and the performance of the algorithms are evaluated using real data.Location Aware Keyword Query Suggestion Based on Document Proximity.

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