Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This study proposed a Latent Semantic Analysis based method to approximate Google's ranking.  conduct Latent Semantic Analysis on Google's search results for a given query to find terms with highest LSA ights as features. Then the correlation coefficients beten the features and the given query are obtained for use as the feature values. Each result is scored and re-ranked based on a linear combination of ighted sum of feature values that appear in its title, snippet and URL. Experimental results on a small number of popular keywords show that this method is promising to achieve R-Precision up to 0.8 for some combination of search results and features used.
['Cheng-Jye Luh', 'Chitsanzo Wesley Kazembe', 'Chun-Ju Li']
I am writing a research paper on a idea Approximating Google's rankings with Latent Semantic Analysis
[{"from": "human", "value": "I am writing a research paper on a idea Approximating Google's rankings with Latent Semantic Analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This study proposed a Latent Semantic Analysis based method to approximate Google's ranking.  conduct Latent Semantic Analysis on Google's search results for a given query to find terms with highest LSA ights as features. Then the correlation coefficients beten the features and the given query are obtained for use as the feature values. Each result is scored and re-ranked based on a linear combination of ighted sum of feature values that appear in its title, snippet and URL. Experimental results on a small number of popular keywords show that this method is promising to achieve R-Precision up to 0.8 for some combination of search results and features used."}]