Abstract
Blog search engines and general search engines automatically crawl Web pages from the Internet and generate search results to users. One difference between the two is that blog search engines focus on blog posts and filter general pages. This difference allows bloggers to focus only on page results for posts rather than other types of page results. Another difference is that posts involve more time-related issues than general pages. For general pages, the general search engine can only show the last update time for the page. However, for posts, the blog search engine can show all possible time clues for the post. For some frequently updated posts, time clues help bloggers find information more efficiently. In this paper, we first use some well-known semantic analysis models to analyze the performance of Google Blog Search. Next, we apply a hybrid strategy that considers the document link and time clue relationships between posts to further improve its retrieval performance. Finally, we present several experiments to simulate various possible scenarios to confirm the effectiveness of our strategy.
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