scholarly journals Supervised approach for keyword extraction from Persian documents using lexical chains

2019 ◽  
Vol 15 (4) ◽  
pp. 95-110
Author(s):  
Atieh Sharifi ◽  
M.Amin Mahdavi ◽  
◽  
Keyword(s):  
Keyword Extraction ◽  
Lexical Chains

Keyword Extraction Based on Lexical Chains and Word Co-occurrence for Chinese News Web Pages

2008 ◽  
Author(s):  
Xinghua Li ◽  
Xindong Wu ◽  
Xuegang Hu ◽  
Fei Xie ◽  
Zhaozhong Jiang
Keyword(s):  
Keyword Extraction ◽  
Web Pages ◽  
Lexical Chains

Semi Supervised Graph Based Keyword Extraction Using Lexical Chains and Centrality Measures

2018 ◽  
Vol 22 (4) ◽  
Author(s):  
Ayush Aggarwal ◽  
Chhavi Sharma ◽  
Minni Jain ◽  
Amita Jain
Keyword(s):  
Centrality Measures ◽  
Keyword Extraction ◽  
Lexical Chains

scholarly journals Using lexical chains for keyword extraction

2007 ◽  
Vol 43 (6) ◽  
pp. 1705-1714 ◽  
Author(s):  
Gonenc Ercan ◽  
Ilyas Cicekli
Keyword(s):  
Keyword Extraction ◽  
Lexical Chains

PNFS: PERSONALIZED WEB NEWS FILTERING AND SUMMARIZATION

2013 ◽  
Vol 22 (05) ◽  
pp. 1360007 ◽  
Author(s):  
XINDONG WU ◽  
FEI XIE ◽  
GONGQING WU ◽  
WEI DING
Keyword(s):  
Extraction Method ◽  
Word Sense Disambiguation ◽  
Keyword Extraction ◽  
Word Sense ◽  
User Interest ◽  
Web Intelligence ◽  
Intelligence System ◽  
Lexical Chains ◽  
Summarization System ◽  
Web News

Information on the World Wide Web is congested with large amounts of news contents. Recommending, filtering, and summarization of Web news have become hot topics of research in Web intelligence, aiming to find interesting news for users and give concise content for reading. This paper presents our research on developing the Personalized News Filtering and Summarization system (PNFS). An embedded learning component of PNFS induces a user interest model and recommends personalized news. Two Web news recommendation methods are proposed to keep tracking news and find topic interesting news for users. A keyword knowledge base is maintained and provides real-time updates to reflect the news topic information and the user's interest preferences. The non-news content irrelevant to the news Web page is filtered out. A keyword extraction method based on lexical chains is proposed that uses the semantic similarity and the relatedness degree to represent the semantic relations between words. Word sense disambiguation is also performed in the built lexical chains. Experiments on Web news pages and journal articles show that the proposed keyword extraction method is effective. An example run of our PNFS system demonstrates the superiority of this Web intelligence system.

scholarly journals Keyword extraction method for machine reading comprehension based on natural language processing

2021 ◽  
Vol 1955 (1) ◽  
pp. 012072
Author(s):  
Ruiheng Li ◽  
Xuan Zhang ◽  
Chengdong Li ◽  
Zhongju Zheng ◽  
Zihang Zhou ◽  
...  
Keyword(s):  
Reading Comprehension ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Extraction Method ◽  
Keyword Extraction ◽  
Machine Reading
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