The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, we propose a novel strategy at an abstract level by combining textual and visual clustering results to retrieve images using semantic keywords and auto-annotate images based on similarity with existing keywords. Our main hypothesis is that images that fall in to the same text-cluster can be described
Inspired by classical text document analysis employing the concept of (key) words, this paper presents an unsupervised approach to discover (key) audio elements in general audio documents. The (key) audio elements can be considered the equivalents of the text (key) words, and enable content-based audio analysis and retrieval following the analogy to the proven text analysis theories and methods. Since...
keywords from the Web pages. The system first identifies the section of the Web page that contains the multimedia file to be extracted and then extracts it by using clustering techniques and other tools of statistical origin. Experimental results on real-world image sharing Web sites are presented and discussed in this paper
In this paper, we propose a novel strategy at an abstract level by combining textual and visual clustering results to retrieve images using semantic keywords and auto-annotate images based on similarity with existing keywords. Our main hypothesis is that images that fall in to the same textcluster can be described
We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize
Many e-commerce web sites such as online book retailers or specialized information hubs such as online movie databases make use of recommendation systems where users are directed to items of interests based on past user interactions. While keyword based approaches are naive and do not take content or context into
the document tags is considered as cluster name. Thus in short, web search results that are fetched from the prevailing web search engines grouped under phrases that contain one or more search keywords. This paper aims at organizing web search results into clusters facilitating quick browsing options to the browser
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.