Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The number of features required to depict an image can be very large. Using all features simultaneously to measure image similarity and to learn image query-concepts can suffer from the problem of dimensionality curse, which degrades both search accuracy and search speed. Regarding search accuracy, the presence of irrelevant features with respect to a query can contaminate similarity measurement, and hence decrease both the recall and precision of that query. To remedy this problem,  present a mining method that learns online users' query concepts and identifies important features quickly. Regarding search speed, the presence of a large number of features can slow down query-concept learning and indexing performance.  propose a divide-and-conquer method that divides the concept-learning task into G subtasks to achieve speedup.  notice that a task must be divided carefully, or search accuracy may suffer.  thus propose a genetic-based mining algorithm to discover good feature groupings. Through analysis and mining results,  observe that organizing image features in a multi-resolution manner and minimizing intra-group feature correlation, can speed up query-concept learning substantially while maintaining high search accuracy.
['Beitao Li', 'Wei-Cheng Lai', 'Edward Y. Chang', 'Kwang-Ting Cheng']
I am writing a research paper on a idea Mining image features for efficient query processing
[{"from": "human", "value": "I am writing a research paper on a idea Mining image features for efficient query processing"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The number of features required to depict an image can be very large. Using all features simultaneously to measure image similarity and to learn image query-concepts can suffer from the problem of dimensionality curse, which degrades both search accuracy and search speed. Regarding search accuracy, the presence of irrelevant features with respect to a query can contaminate similarity measurement, and hence decrease both the recall and precision of that query. To remedy this problem,  present a mining method that learns online users' query concepts and identifies important features quickly. Regarding search speed, the presence of a large number of features can slow down query-concept learning and indexing performance.  propose a divide-and-conquer method that divides the concept-learning task into G subtasks to achieve speedup.  notice that a task must be divided carefully, or search accuracy may suffer.  thus propose a genetic-based mining algorithm to discover good feature groupings. Through analysis and mining results,  observe that organizing image features in a multi-resolution manner and minimizing intra-group feature correlation, can speed up query-concept learning substantially while maintaining high search accuracy."}]