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Text analysis of a web page is more difficult than the analysis of the text of normal document due to the presence of additional information, such as HTML structure, styling codes, irrelevant text, and presence of hyperlinks. In this paper, we propose an unsupervised method to extract keywords from a web page. The
using automatically extracted keywords. Given an ambiguous personal name, first, we download text snippets for the given name from a Web search engine. We then represent each instance of the ambiguous name by a term‐entity model (TEM), a model that we propose to represent the Web appearance of an individual. A TEM
processing. The main results of this work are related to an effective prediction of the aggregated patterns of real usage, which reaching near about 87%. Moreover, this approach obtains a quantitative representation of the keywords from the content data that influence the sessions. The proposed work and innovative research is
The problem of obtaining relevant results in web searching has been tackled with several approaches. Although very effective techniques are currently used by the most popular search engines when no a priori knowledge on the user's desires beside the search keywords is available, in different settings it is conceivable
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.