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The background of this paper is the issue of how to overview the knowledge of a given query keyword. Especially, we focus on concerns of those who search for Web pages with a given query keyword. The Web search information needs of a given query keyword is collected through search engine suggests. Given a query
The default page sorting algorithm in Nutch which is open source search engine is TF/IDF algorithm, but it's difficult to meet the demand of music page sorting. The paper presents a new page sorting algorithm bases on BM25 model for music users. According word count and keyword frequency in music web pages, the pages
environment are created and attached to such words. In this paper we propose a method for an automatic extension of the content available on the Web by adding annotations to selected terms (keywords) in the text. The method is designed to be able to insert annotations into the text written in Slovak with a potential to be
inherited the probability from multiple fathers. We used N-gram based on Wikipedia words to extract the keywords from web page, and introduce Bayes classifier to estimate the page class probability. Experimental results shown that the proposed method has very good scalability, robustness and reliability for different web pages.
Social book marking services allow users to add bookmarks of web pages with freely chosen keywords as tags. Personalized recommender systems recommend new and useful bookmarks added by other users. We propose a new method to find similar users and to select relevant bookmarks in a social book marking service. Our
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.