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important words or phrases in the text to other pages, thereby letting users quickly access additional information. An automatic text-annotation system combines keyword extraction and word-sense disambiguation to identify relevant links to Wikipedia pages.
, irrelevant tweets were further segregated by means of a unigram dictionary containing education-oriented keywords. The Apriori algorithm was then applied to the dataset thus obtained resulting in characteristic markers or patterns of these institutes.
the websites into their most appropriate category. Several parameters like the weight applied to each feature and the keywords used to classify the websites were tuned to yield better results. The experimental evaluation revealed that the method implemented provides very high accuracy. In particularly, we obtained an
adaptive algorithm uses concept space and keywords in English. However, the content is available in Czech, Turkish and English languages. Multilingual content is presented in language-corresponding user interface. The first statistical results seem to be good, navigational pattern analysis found usual patterns of the
take advantage of the accurate description of concept as well as the definition of the relationship of the concepts, to expand keywords and improve the accuracy and recall rates.
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