Automatic Keyword Extraction From Dialogue Text

被引:0
|
作者
Sali, Yusuf [1 ]
Erden, Mustafa [1 ]
机构
[1] Sestek, Istanbul, Turkiye
关键词
keyword extraction; tf-idf; textrank; positionrank;
D O I
10.1109/SIU55565.2022.9864851
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Keyword extraction is the automatic process of extracting keywords or keyphrases that are most relevant to a text using various algorithms. In this study, we have extracted keywords from customer service records of various companies. We reached %70 recall score by supporting tf-idf with textrank and positionrank algorithms. This corresponds to %10 relative improvement to tf-idf alone. This method is created to get accurate results especially from small-medium length and preferably dialogue texts. The system can be applied to different types of texts by optimizing its parameters. Our method also generates minimum three word phrases which is an easily understandable and a very short summary of the dialog, from the extracted keywords.
引用
收藏
页数:4
相关论文
共 50 条
  • [41] A Binomial Heap Extractor For Automatic Keyword Extraction
    Paul, Dimple V.
    Pawar, Jyoti D.
    PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON DATA MINING AND ADVANCED COMPUTING (SAPIENCE), 2016, : 113 - 121
  • [42] Deep Text Mining for Automatic Keyphrase Extraction from Text Documents
    Abulaish, Muhammad
    Jahiruddin
    Dey, Lipika
    JOURNAL OF INTELLIGENT SYSTEMS, 2011, 20 (04) : 327 - 351
  • [43] A Framework for the Automatic Extraction of Rules from Online Text
    Hassanpour, Saeed
    O'Connor, Martin J.
    Das, Amar K.
    RULE-BASED REASONING, PROGRAMMING, AND APPLICATIONS, 2011, 6826 : 266 - 280
  • [44] Automatic Extraction of Semantic Relations from Text Documents
    Ta, Chien D. C.
    Tuoi Phan Thi
    FUTURE DATA AND SECURITY ENGINEERING, FDSE 2016, 2016, 10018 : 344 - 351
  • [45] Automatic extraction of ontological relations from Arabic text
    Al Zamil, Mohammed G. H.
    Al-Radaideh, Qasem
    JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2014, 26 (04) : 462 - 472
  • [46] Automatic extraction of corollaries from semantic structure of text
    Nurtazin, Abyz T.
    Khisamiev, Zarif G.
    OPEN ENGINEERING, 2016, 6 (01): : 353 - 358
  • [47] Automatic extraction of proteins and their interactions from biological text
    Hong, K
    Park, J
    Yang, J
    Paek, E
    DISCOVERY SCIENCE, PROCEEDINGS, 2005, 3735 : 322 - 329
  • [48] An Improved Focused Crawler Based on Text Keyword Extraction
    Zheng, Zhang
    Qian, Du
    PROCEEDINGS OF 2016 5TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT), 2016, : 386 - 390
  • [49] Text Reuse Detection by Keyword Extraction for Telegram Channels
    Saki, Misam
    Faili, Heshaam
    Asadpour, Masoud
    2017 25TH IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE), 2017, : 1481 - 1484
  • [50] Analysis of Text Collections for the Purposes of Keyword Extraction Task
    Vanyushkin, Alexander
    Graschenko, Leonid
    JOURNAL OF INFORMATION AND ORGANIZATIONAL SCIENCES, 2020, 44 (01) : 171 - 184