Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The target of a focused crawler (FC) is to retrieve pages related to a specific domain of interest (DOI). Hover, FCs may be hasted if bad links re injected into their crawling queue. Hence, they will be gradually sked away from their DOI.  introduces an effective modification on the behavior of FCs by adding a domain distiller. Hence, before passing the retrieved page to the indexer or embedding its links into the crawling queue, the page must pass through a domain distiller. The proposed domain distiller relies on an Optimized Naive Bayes (ONB) classifier, which combines naive Bayes (NB) and Support Vector Machines (SVM). Initially, genetic algorithm (GA) is used to optimize the soft margins of SVM. Then the optimized SVM is employed to eliminate the outliers from the available training examples. Next, the pruned examples are used to train the traditional NB classifier. Moreover, ONB employs word sense disambiguation (WSD) to identify the accurate sense of each domain keyword extracted from the input page. This is accomplished by using a proposed domain ontology, which is called Disambiguation Domain Ontology (D2O). ONB has been tested against recent classification techniques. Experimental results have proven the effectiveness of ONB as it introduces the maximum classification accuracy. Also, results indicate that the proposed distiller improves the performance of focused crawling in terms of crawling harvest rate.
['Ahmed I. Saleh', 'Arwa E. Abulwafa', 'Mohammed F. Al Rahmawy']
I am writing a research paper on a idea A web page distillation strategy for efficient focused crawling based on optimized Naïve bayes (ONB) classifier
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