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A Query Classification System based on Snippet Similarity for a One-Click Search
2013
International Journal of Computer Applications
This paper proposes a query classification system for a one-click search system that uses feature vectors based on snippet similarity. The proposed system targets the NTCIR-10 1CLICK-2 query classification subtask and classifies queries in Japanese and English into eight predefined classes by using support vector machines (SVMs). In the NTCIR-9 and NTCIR-10 tasks, most participants used complex features or rules that depend strongly on language characteristics. The authors propose a new method
doi:10.5120/14077-2146
fatcat:uxcjxvwpqvhatm77o4ilxl4ehy