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Internet is becoming an increasingly important platform for ordinary life and work. It is expected that keyword extraction can help people quickly find hot spots on the web, since keywords in a document provide important information about the content of the document. In this paper, we propose to use text clustering
structure of keywords. First, this paper proposes the extraction method of important keywords in their opinions based on the modification relationships. Next, it clusters the respondents interactively on visible space using MDS. Finally, it shows their opinions using HK Graph which can visualize the relationship among words
methods for Indonesian corpus is rather small. Brace well's algorithm has been proven effective in identifying topics in English and Japanese corpora with high accuracy. This paper implements a method for TID based on Brace well's keywords similarity algorithm and the top-n keywords selection for Indonesian news documents
these sites. Current techniques simply filter on the basis of URLs blocking and keyword matching or either rely on a large database of pre-classified web addresses. The problem is how to intelligently filter the negative contents, rather than filtering entire websites using their URLs or applying simple keyword matching
Sentiment analysis in text mining is known to be a challenging task. Sentiment is subtly reflected by the tone, affective state or emotion of a writer's expression in words. Conventional text mining techniques which are based on keyword frequency counting usually run short of accurately detecting such subjective
some problems, they tend to retrieve the information from the Web search engines. Many business search engines are efficient at identifying the best web sites for any given keyword query. Unfortunately, the information on the web is not always correct. Moreover, different web sites often provide different information on a
In this paper, we propose an evolutionary approach to rank association rules for classification. The association rules are ranked by their support, confidence and length in one of the most important associative classification method, Classification based on Multiple Association Rule (CMAR). However, from some empirical studies, we find that if the rules are ranked by some equations first, the classification...
a text database using the filtered results. We further conduct a cache-based adaptation method on the resulting language model, in which keywords in the filtered results are cached and used to boost the word probability. In an experimental evaluation over real lectures, we obtained a significant improvement of ASR
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.