Jump to content

Bing Liu (computer scientist): Difference between revisions

From Wikipedia, the free encyclopedia
Browse history interactively
← Previous editNext edit →
Content deleted Content added
VisualWikitext
Denmum (talk | contribs)
169 edits
Added three articles to Peer-reviewed Article List + citations
Denmum (talk | contribs)
169 edits
Added two articles to Peer-reviewed Article List + citations
Line 39: Line 39:
* Yanhong Zhai and Bing Liu. 2006. “Structured Data Extraction from the Web Based on Partial Tree Alignment.” ''IEEE Transactions on Knowledge and Data Engineering'' 18(12):1614–28.<ref>{{Cite journal|last=Yanhong Zhai|last2=Bing Liu|date=2006-12-XX|title=Structured Data Extraction from the Web Based on Partial Tree Alignment|url=http://ieeexplore.ieee.org/document/1717419/|journal=IEEE Transactions on Knowledge and Data Engineering|volume=18|issue=12|pages=1614–1628|doi=10.1109/TKDE.2006.197|issn=1041-4347}}</ref>
* Yanhong Zhai and Bing Liu. 2006. “Structured Data Extraction from the Web Based on Partial Tree Alignment.” ''IEEE Transactions on Knowledge and Data Engineering'' 18(12):1614–28.<ref>{{Cite journal|last=Yanhong Zhai|last2=Bing Liu|date=2006-12-XX|title=Structured Data Extraction from the Web Based on Partial Tree Alignment|url=http://ieeexplore.ieee.org/document/1717419/|journal=IEEE Transactions on Knowledge and Data Engineering|volume=18|issue=12|pages=1614–1628|doi=10.1109/TKDE.2006.197|issn=1041-4347}}</ref>
* Yu, Huilin, Tieyun Qian, Yile Liang, and Bing Liu. 2020. “AGTR: Adversarial Generation of Target Review for Rating Prediction.” ''Data Science and Engineering'' 5(4):346–59.<ref>{{Cite journal|last=Yu|first=Huilin|last2=Qian|first2=Tieyun|last3=Liang|first3=Yile|last4=Liu|first4=Bing|date=2020-12-XX|title=AGTR: Adversarial Generation of Target Review for Rating Prediction|url=http://link.springer.com/10.1007/s41019-020-00141-1|journal=Data Science and Engineering|language=en|volume=5|issue=4|pages=346–359|doi=10.1007/s41019-020-00141-1|issn=2364-1185}}</ref>
* Yu, Huilin, Tieyun Qian, Yile Liang, and Bing Liu. 2020. “AGTR: Adversarial Generation of Target Review for Rating Prediction.” ''Data Science and Engineering'' 5(4):346–59.<ref>{{Cite journal|last=Yu|first=Huilin|last2=Qian|first2=Tieyun|last3=Liang|first3=Yile|last4=Liu|first4=Bing|date=2020-12-XX|title=AGTR: Adversarial Generation of Target Review for Rating Prediction|url=http://link.springer.com/10.1007/s41019-020-00141-1|journal=Data Science and Engineering|language=en|volume=5|issue=4|pages=346–359|doi=10.1007/s41019-020-00141-1|issn=2364-1185}}</ref>

* Bing Liu. 1997. “Route Finding by Using Knowledge about the Road Network.” ''IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans'' 27(4):436–48.<ref>{{Cite journal|last=Bing Liu|date=1997-07-XX|title=Route finding by using knowledge about the road network|url=http://ieeexplore.ieee.org/document/594911/|journal=IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans|volume=27|issue=4|pages=436–448|doi=10.1109/3468.594911}}</ref>
* Liu, Bing. 1993. “Problem Acquisition in Scheduling Domains.” ''Expert Systems with Applications'' 6(3):257–65.<ref>{{Cite journal|last=Liu|first=Bing|date=1993-07-XX|title=Problem acquisition in scheduling domains|url=https://linkinghub.elsevier.com/retrieve/pii/095741749390054A|journal=Expert Systems with Applications|language=en|volume=6|issue=3|pages=257–265|doi=10.1016/0957-4174(93)90054-A}}</ref>


==References==
==References==

Revision as of 04:40, 25 April 2021

Bing Liu (born 1963) is a Chinese-American professor of computer science who specialized in data mining, machine learning, and natural language processing. In 2002, he became a scholar at University of Illinois at Chicago.[1] He holds a PhD from the University of Edinburgh.[2]

Academic research

He developed a mathematical model which can reveal fake advertising.[3] Also he teaches the course "Data Mining" during the Fall and Spring semesters at UIC. The course usually involves a project and various quiz/examinations as grading criteria.

He is best known for his research on sentiment analysis (also called opinion mining), fake/deceptive opinion detection, and using association rules for prediction. He also made important contributions to learning from positive and unlabeled examples (or PU learning), Web data extraction, and interestingness in data mining.

Two of his research papers published in KDD-1998 and KDD-2004 received KDD Test-of-Time awards in 2014 and 2015. In 2013, he was elected chair of SIGKDD, ACM Special Interest Group on Knowledge Discovery and Data Mining.

Research on Association Rules For Prediction

Association rule-based classification takes into account the relationships between each and all items in a dataset and the class into which one is trying to classify that item.[4] The basis is that there are two classes, a positive class and a negative class, into which one classifies items.[4] Some classification algorithms only check if a case/item is in the positive class, without understanding how much exactly the probability of it being in that class is.[4] Liu and his collaborators described a new association rule-based classification algorithm that takes into account the relationship between items and the positive and negative classes.[4] Each item is given a probability or scoring of being in the positive class or the negative class. It then ranks the items as per which ones would be most likely to be in the positive class.[4]

Research on Sentiment Analysis

In a paper that Liu collaborated on, the authors studied the relationship between opinion lexicons and opinion targets.[5] Opinion lexicons are word sets and opinion targets are topics on which there is an opinion.[5] The authors of that paper discuss how their algorithm uses a limited opinion word set with the topic and through double propagation, one is able to form a more detailed opinion word set on a set of sentences. Double propagation is the back and forth functional process between the word set and topic as the word set updates itself.[5] Some algorithms require set rules and thus are limited in what they can actually do and in what service they provide in providing updated opinion lists.[5] Their algorithm only requires an initial word set (or opinion lexicon), which is updated through finding relations between the words in the set and the target word or vice versa.[5] The algorithm is done on a word population such as a set of sentences or a paragraph.[5]

Honors and awards

  • In 2014, he was named Fellow of IEEE (Institute of Electrical and Electronics Engineers).
  • In 2015, he was named Fellow of ACM "For contributions to knowledge discovery and data mining, opinion mining, and sentiment analysis". [6]
  • In 2016, he was elected Fellow of AAAI "For significant contributions to data mining and development of widely used sentiment analysis, opinion spam detection, and Web mining algorithms." [7]

Publications

Peer-reviewed Article List

  • Liu, Bing, Yiming Ma, Ching Kian Wong, and Philip S. Yu. 2003. “Scoring the Data Using Association Rules.” Applied Intelligence 18(2):119–35.[4]
  • Qiu, Guang, Bing Liu, Jiajun Bu, and Chun Chen. 2011. “Opinion Word Expansion and Target Extraction through Double Propagation.” Computational Linguistics 37(1):9–27.[5]
  • Wu, Xindong et al. 2007. “Top 10 Algorithms in Data Mining.” Knowledge and Information Systems 14(1):1–37.[8]
  • Liu, Bing. 1995. “A Unified Framework for Consistency Check.” International Journal of Intelligent Systems 10(8):691–713.[9]
  • Zhang, Lei, Shuai Wang, and Bing Liu. 2018. “Deep Learning for Sentiment Analysis: A Survey.” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 8(4).[10]
  • Wang, Guan, Sihong Xie, Bing Liu, and Philip S. Yu. 2012. “Identify Online Store Review Spammers via Social Review Graph.” ACM Transactions on Intelligent Systems and Technology 3(4):1–21.[11]
  • Yu, Zeng et al. 2019. “Reconstruction of Hidden Representation for Robust Feature Extraction.” ACM Transactions on Intelligent Systems and Technology 10(2):1–24.[12]
  • Wang, Jing, Clement T. Yu, Philip S. Yu, Bing Liu, and Weiyi Meng. 2015. “Diversionary Comments under Blog Posts.” ACM Transactions on the Web 9(4):1–34.[13]
  • Bing Liu, Wynne Hsu, Lai-Fun Mun, and Hing-Yan Lee. 1999. “Finding Interesting Patterns Using User Expectations.” IEEE Transactions on Knowledge and Data Engineering 11(6):817–32.[14]
  • Yanhong Zhai and Bing Liu. 2006. “Structured Data Extraction from the Web Based on Partial Tree Alignment.” IEEE Transactions on Knowledge and Data Engineering 18(12):1614–28.[15]
  • Yu, Huilin, Tieyun Qian, Yile Liang, and Bing Liu. 2020. “AGTR: Adversarial Generation of Target Review for Rating Prediction.” Data Science and Engineering 5(4):346–59.[16]
  • Bing Liu. 1997. “Route Finding by Using Knowledge about the Road Network.” IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 27(4):436–48.[17]
  • Liu, Bing. 1993. “Problem Acquisition in Scheduling Domains.” Expert Systems with Applications 6(3):257–65.[18]

References

  1. ^ Christy Levy (February 19, 2013). "On the internet, no one knows you're lying". Retrieved January 1, 2015.
  2. ^ https://www.cs.uic.edu/~liub/Bing-Liu-short-CV.html
  3. ^ David Streitfield (January 26, 2012). "For $2 a Star, an Online Retailer Gets 5-Star Product Reviews". The New York Times.
  4. ^ a b c d e f Liu, Bing; Ma, Yiming; Wong, Ching Kian; Yu, Philip S. (2003-03-01). "Scoring the Data Using Association Rules". Applied Intelligence. 18 (2): 119–135. doi:10.1023/A:1021931008240. ISSN 1573-7497.
  5. ^ a b c d e f g Qiu, Guang; Liu, Bing; Bu, Jiajun; Chen, Chun (2011-03-XX). "Opinion Word Expansion and Target Extraction through Double Propagation". Computational Linguistics. 37 (1): 9–27. doi:10.1162/coli_a_00034. ISSN 0891-2017. {{cite journal}}: Check date values in: |date= (help)
  6. ^ "ACM Fellows Named for Computing Innovations that Are Advancing Technology in the Digital Age". ACM. 8 December 2015. Archived from the original on 9 December 2015. Retrieved 9 December 2015.
  7. ^ "AAAI Fellows Elected in 2016". AAAI. 2016. Retrieved 2 February 2016.
  8. ^ Wu, Xindong; Kumar, Vipin; Ross Quinlan, J.; Ghosh, Joydeep; Yang, Qiang; Motoda, Hiroshi; McLachlan, Geoffrey J.; Ng, Angus; Liu, Bing; Yu, Philip S.; Zhou, Zhi-Hua (2008-01-XX). "Top 10 algorithms in data mining". Knowledge and Information Systems. 14 (1): 1–37. doi:10.1007/s10115-007-0114-2. ISSN 0219-1377. {{cite journal}}: Check date values in: |date= (help)
  9. ^ Liu, Bing (1995). "A unified framework for consistency check". International Journal of Intelligent Systems. 10 (8): 691–713. doi:10.1002/int.4550100802.
  10. ^ Zhang, Lei; Wang, Shuai; Liu, Bing (2018-07-XX). "Deep learning for sentiment analysis: A survey". Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 8 (4). doi:10.1002/widm.1253. ISSN 1942-4787. {{cite journal}}: Check date values in: |date= (help)
  11. ^ Wang, Guan; Xie, Sihong; Liu, Bing; Yu, Philip S. (2012-09-XX). "Identify Online Store Review Spammers via Social Review Graph". ACM Transactions on Intelligent Systems and Technology. 3 (4): 1–21. doi:10.1145/2337542.2337546. ISSN 2157-6904. {{cite journal}}: Check date values in: |date= (help)
  12. ^ Yu, Zeng; Li, Tianrui; Yu, Ning; Pan, Yi; Chen, Hongmei; Liu, Bing (2019-02-28). "Reconstruction of Hidden Representation for Robust Feature Extraction". ACM Transactions on Intelligent Systems and Technology. 10 (2): 1–24. doi:10.1145/3284174. ISSN 2157-6904.
  13. ^ Wang, Jing; Yu, Clement T.; Yu, Philip S.; Liu, Bing; Meng, Weiyi (2015-10-26). "Diversionary Comments under Blog Posts". ACM Transactions on the Web. 9 (4): 1–34. doi:10.1145/2789211. ISSN 1559-1131.
  14. ^ Bing Liu; Wynne Hsu; Lai-Fun Mun; Hing-Yan Lee (Nov.-Dec./1999). "Finding interesting patterns using user expectations". IEEE Transactions on Knowledge and Data Engineering. 11 (6): 817–832. doi:10.1109/69.824588. {{cite journal}}: Check date values in: |date= (help)
  15. ^ Yanhong Zhai; Bing Liu (2006-12-XX). "Structured Data Extraction from the Web Based on Partial Tree Alignment". IEEE Transactions on Knowledge and Data Engineering. 18 (12): 1614–1628. doi:10.1109/TKDE.2006.197. ISSN 1041-4347. {{cite journal}}: Check date values in: |date= (help)
  16. ^ Yu, Huilin; Qian, Tieyun; Liang, Yile; Liu, Bing (2020-12-XX). "AGTR: Adversarial Generation of Target Review for Rating Prediction". Data Science and Engineering. 5 (4): 346–359. doi:10.1007/s41019-020-00141-1. ISSN 2364-1185. {{cite journal}}: Check date values in: |date= (help)
  17. ^ Bing Liu (1997-07-XX). "Route finding by using knowledge about the road network". IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans. 27 (4): 436–448. doi:10.1109/3468.594911. {{cite journal}}: Check date values in: |date= (help)
  18. ^ Liu, Bing (1993-07-XX). "Problem acquisition in scheduling domains". Expert Systems with Applications. 6 (3): 257–265. doi:10.1016/0957-4174(93)90054-A. {{cite journal}}: Check date values in: |date= (help)


Stub icon

This biographical article relating to a computer specialist in the United States is a stub. You can help Wikipedia by expanding it.

P ≟ NP 

This biographical article relating to a computer scientist is a stub. You can help Wikipedia by expanding it.

Retrieved from "https://en.wikipedia.org/enwiki/w/index.php?title=Bing_Liu_(computer_scientist)&oldid=1019743740"