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Keyword extraction is an important application in the area of information technology. Automatic keyword extraction can help people know what is the article primarily talking about without reading the long passage carefully. This paper mainly introduced a keyword extraction algorithm using pagerank on Synonym. Firstly
multilingual information where backend will be English database and front-end uses local languages like Hindi, Marathi or Gujrathi. Our system provides an interface to enter a keyword in local language, the keyword will be parsed, query will be formed and display the result in local language. We had developed an efficient
utilizes text-mining, Web service technologies and domain knowledge, in order to extract keywords, to retrieve related records from an external source, and to filter the extracted keywords list. This study meets a practical challenge encountered at the School of Veterinary and Biomedical Sciences at Murdoch University. The
agent that targets a particular topic and visits and gathers only relevant web pages. In this dissertation I had worked on design and working of web crawler that can be used for copyright infringement. We will take one seed URL as input and search with a keyword, the searching result is based on keyword and it will fetch
structured patterns in semistructured Web documents. A tag tree pattern is an edge labeled tree with ordered children and structured variables. An edge label of a tag tree pattern is a tag or a keyword in Web documents, or a wildcard for any string. Each variable, which matches any subtree, represents a field of a Web document
There are huge numbers of valuable information resources resided on Invisible Web. However, it is hard to use for us. In this paper we propose a system called NewsReaper that is capable of making Invisible Web to be visible, especially the huge number of real-time information, which update frequently and are time-sensitive. NewsReaper makes use of information extraction, text classification, full...
use a set of parallel corpora to train the map and apply a discovering process to identify the semantic groups and hierarchical structures of keywords for these languages. The discovered knowledge can then be applied to tasks such as multilingual information retrieval and automatic multilingual thesaurus construction.
automatically constructs a navigational structure for the WWW to help information finding. A self-organizing map is constructed to train the Web pages and obtain two feature maps, which reveal the relationships among Web pages and thematic keywords respectively. We then use these maps to develop a structure that may assist the
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.