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depend probabilistically both on other properties of that object and on properties of related objects. In this paper an attempt is made to heed keywords extraction. The keywords are not only essential for academic papers but also important for web page retrieval, text mining, and document classification. In this paper, a C
One of the most serious problems that conventional knowledge management (KM) encompasses has been pointed out tardy and ineffective acquisition of knowledge. To resolve this problem, knowledge must be autonomously acquired according to its context of use by applying the technique of keyword extraction in machine
livelihoods, how to deal with its negative impacts, and which mitigation or adaptation policies to support. A line of related work has used bag of words and word-level features to detect frames automatically in text. Such works face limitations since standard keyword based features may not generalize well to accommodate surface
This paper aims to analyze affective expressions in articles of popular science by text mining with the keywords “Cancer” and “Immunity”. This study selects 145 articles from the website of a magazine and segmented them into 410,919 terms. And the study uses an automatic system to classify the terms into vocabulary
trigger keywords and contextual cues. The system was tested on multiple large collections of Dutch tweets. Our experimental results show that our system can successfully analyze messages and recognize threatening content.
approach is a rule-based system. Rules are built based on the predefined crime indicator list that contains some important keywords. Even though the system is still under development, the initial results are promising.
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