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The complex network theory is widely used in the field of keyword extraction. Through analyzing the insufficient of keyword extraction algorithms using traditional complex network, this paper proposes a new method to extract Chinese keyword based on semantically weighted network. On the basis of K-nearest neighbor
Information retrieval techniques play vital role in the era of information technology. Inverted index is one of the technique to retrieve the information/data related with certain keyword. This technique gives faster results to retrieve relevant document from billions of documents, which contains specified keyword. In
-processing of Web search results have been extensively studied to help user effectively obtain useful information. This paper has basically three parts. First part is the review study on how the keyword is expanded through truncation or wildcards (which is a little known feature but one of the most powerful one) by using
context information and semantic similarity together. We searched a series of context structures for keywords in a sentence. Experiment has been carried out to show the effectiveness of our method.
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.