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Improved TF-IDF Keyword Extraction Algorithm *
| Content Provider | Semantic Scholar |
|---|---|
| Author | Wang, Xiaolin Yang, Lin Wang, Dong Zhen, Lihua |
| Copyright Year | 2013 |
| Abstract | nd , 2012; revised: Dec. 16 th , 2012; accepted: Dec. 25 th , 2012 Abstract: According to the TF-IDF extract algorithm, this paper proposes a new extraction algorithm based on the words frequency statistics. Combining with sections mark technology, this algorithm assigns corresponding position weight to the words located in different position and calculates the words similarities with the same parts of speech which have a high counter in the result of the word segmentation, then merge the words with a higher similarity, finally we get the keyword sorted by the weight via the TF-IWF algorithm. This method optimized the traditional Chinese keyword extract algorithm, which take little notice of the higher similarity words, and lead to low-accuracy. The results show the new approach has better algorithm performance compared with the previous TF-IDF algorithm and the key- words set extracted can generally express the content of the article. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.hanspub.org/journal/PaperDownload.aspx?DOI=10.12677/CSA.2013.31012 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
