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In this paper, we propose a novel image search scheme is contextual image search with keyword input. It is different from conventional image search schemes. it consist of three step process, first one is context extraction to distinguish the image entities of the same name, second step is conceptualization to convert
It's important to eliminate noisy data for information extraction on the deep web. In this paper, we propose a new approach called ENDW(Eliminating Noisy Data in Web pages) based on query keywords and DOM tools to eliminate noisy data. Query keywords submitted to backend databases always appear in deep web pages. The
The traditional layout of news websites, the combination of classified hierarchical browsing, headline recommendation and keyword-based search, has been used for many years. The keyword-based search is considered to be the most powerful tool for news browsing and retrieval. Unfortunately, the keyword-based query
Traditional information gathering systems are mostly keyword-based that are lack of semantic comprehension and analysis ability and can't guarantee the comprehensiveness and accuracy of information gathering. This paper proposes Chinese patent information gathering model based on domain ontology, which can visualize
More and more abundant Web images on the Internet make clients difficult seek the information they really need so that how to quickly and accurately retrieve their interested Web images is one of the most challenging tasks. The kernel idea of the model is that the text keyword features, visual content features, link
topic, object and attribute dictionaries. Eight kinds of text are extracted as image semantic source from Web pages. Combining with semantic dictionaries, image semantic keywords can be extracted from the eight kinds of text. The strategy of extracting image semantics is better than existing technique, which is better than
Current classification techniques use word matching and clustering techniques to classify webpages. These techniques use ad hoc approach of checking and matching the entire keywords in a webpage for classification. These methods are efficient but not without problems. In general, they suffer from the following
visualize the lattice structure of web pages and keywords as line diagram. This system is implemented on the computer (CPU=2.83GHz! $MM=2GB), by using Python, which is an object-oriented programming language, Application Program Interface (API), and one of the GUI libraries, Tkinter. Through the subjective evaluation and sign
algorithms, web image information is extracted from textual sources such as image file names, anchor texts, existing keywords and, of course, surrounding text. However, the systems that attempt to mine information for images using surrounding text suffer from several problems, such as the inability to correctly assign all
similar product images on shopping websites, ranking product tags by text aggregation, and re-search textual items consisting of semantic meaningful tags to make a recommendation. In addition, users can choose automatically suggested keywords to reflect their intentions. Subjective evaluation has demonstrated the
distinctive keywords used in Web pages or URLs in order to detect new phishing sites that are not yet listed in blacklists. However, these kinds of heuristics can be easily circumvented by phishers once their mechanism is revealed. In order to overcome this weakness, visual similarity-based detection techniques have been
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.