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Figure from:Efficient Hybrid Ranking Algorithm for Search Engine

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The proposed approach uses the combination of various modules to produce a set of ranked documents.

Figure 1 The proposed approach uses the combination of various modules to produce a set of ranked documents.

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improves the overall efficiency and make effective. 5) Next phase in tokenization is stemming. Stemming phase is used to extract the sub-part i.e. called as stem/root of a given word. For example, the words continue, continuously, Continued all can be rooted to the word continue. The main role of stemming is to remove various suffixes as result in the reduction of number of words, to have exactly matching stems, to minimize storage requirement and maximize the efficiency of IR Model.
improves the overall efficiency and make effective. 5) Next phase in tokenization is stemming. Stemming phase is used to extract the sub-part i.e. called as stem/root of a given word. For example, the words continue, continuously, Continued all can be rooted to the word continue. The main role of stemming is to remove various suffixes as result in the reduction of number of words, to have exactly matching stems, to minimize storage requirement and maximize the efficiency of IR Model.