An online retrieval method of an unstructured network database based on a discrete supervised hash algorithm
Due to the weak correlation of unstructured network data and poor data convergence characteristics,it is difficult to guarantee the retrieval accuracy when searching relevant databases.Therefore,the online retrieval method of unstructured network database based on discrete supervised hash algorithm is proposed.First,the explicit semantic label of the unstructured network data sample is represented using the corresponding binary code,and discretized with the help of Lagrange multipliers,so that the hash function can quickly converge for learning the explicit semantic correlation of the unstructured network data.Then,all the data and query requests are encoded in the same way.Finally,the data with the highest match with the query request hash encoding is used as the priority retrieval output.In the test results,the average retrieval accuracy of the design retrieval method under the im-age query text instruction and the text query image instruction is always stable at a high level,and the highest retrieval time is only 7 s,which is practical.
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