Implementation of Support Vector Machine based ranking metrics
نویسندگان
چکیده
This paper discusses the implementation of Support Vector Machine (SVM) based ranking metrics to compute the similarity and rank the documents based on a user query using Fuzzy Logic. TREC dataset has been used for the same purpose. The dataset is parsed to generate keywords index which is used for the similarity comparison with the user query and ranking is done using SVM. Each query is assigned a score value based on its fuzzy similarity with the index keywords. The performance and accuracy of the proposed retrieval model is compared with TF/IDF similarity model using Precision-Recall curves. The SVM ranking precision and recall are calculated by classifying the documents based on a threshold value by using SVM alpha measures.
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تاریخ انتشار 2015