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effective in terms of better precision. Proposed method makes use of keyword clusters for query expansion. Visual features are used for detecting duplicate images in proposed method. Removing duplicates leads to further improve in precision and recall in retrieval result
user aims, as query without proper intent processing retrieves irrelevant information pattern discovery has ability to solve in limitations of keyword and image disambiguates with phrase learning ie, pattern discovery. Today's search machines are based on ranking model eliminating Boolean retrieval constraint and boosting
Traditional Web search engines do not use the images in the HTML pages to find relevant documents for a given query. Instead, they typically operate by computing a measure of agreement between the keywords provided by the user and only the text portion of each page. In this paper we study whether the content
posted by over 740,070 users who discussed about trafficking crimes and issues. CyTraSS supports keyword search, sentiment analysis, message statistics summarization, and influential leader identification. Emotion expressed in social media messages is extracted and aggregated quantitatively to indicate community mood. We
Images that used to characterize high-definition Images from web is very difficult task. So, In this paper we propose unique web Image re-ranking framework that offline and online learned Images visual and semantic meaning regarding with numerous query keywords. These visual and semantic meaning of Images extended to visual
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.