Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Social book marking b sites have emerged recently for collecting and sharing of interesting b sites among users. People can add b pages to such sites as bookmarks and allow themselves as ll as others to manipulate them. One of the key features of the social book marking sites is the ability of annotating a b page when it is being bookmarked. The annotation usually contains a set of words or phrases, which are collectively known as tags, that could reveal the semantics of the annotated b page. Efficient and effective search of b pages can then be achieved via such tags. Hover, spam tags that are irrelevant to the content of b pages often appear to deceive other users for malicious or commercial purposes. Various techniques have been devised to tackle such tag spam detection problem. Most of these techniques re able to detect a user that always annotate spam tags. Hover, finer levels of detection are seldom discussed. In this work,  will propose a method based on a text mining approach to discover the relations beten b pages and there tag posts. These relations are then used to compute the similarity beten a b page and its tag post to decide if it is a spam post. Preliminary experiments show that the accuracy of the post-level spam detection task is 83%.
['Hsin-Chang Yang', 'Chung-Hong Lee']
I am writing a research paper on a idea Post-Level Spam Detection for Social Bookmarking Web Sites
[{"from": "human", "value": "I am writing a research paper on a idea Post-Level Spam Detection for Social Bookmarking Web Sites"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Social book marking b sites have emerged recently for collecting and sharing of interesting b sites among users. People can add b pages to such sites as bookmarks and allow themselves as ll as others to manipulate them. One of the key features of the social book marking sites is the ability of annotating a b page when it is being bookmarked. The annotation usually contains a set of words or phrases, which are collectively known as tags, that could reveal the semantics of the annotated b page. Efficient and effective search of b pages can then be achieved via such tags. Hover, spam tags that are irrelevant to the content of b pages often appear to deceive other users for malicious or commercial purposes. Various techniques have been devised to tackle such tag spam detection problem. Most of these techniques re able to detect a user that always annotate spam tags. Hover, finer levels of detection are seldom discussed. In this work,  will propose a method based on a text mining approach to discover the relations beten b pages and there tag posts. These relations are then used to compute the similarity beten a b page and its tag post to decide if it is a spam post. Preliminary experiments show that the accuracy of the post-level spam detection task is 83%."}]