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Jeniya_Dissertation_final.pdf (3.05 MB)

ETD Abstract Container

Abstract Header

Information Extraction From User Generated Noisy Texts

Tabassum Binte Jafar, Jeniya
http://rave.ohiolink.edu/etdc/view?acc_num=osu1606315356821532

Abstract Details

2020, Doctor of Philosophy, Ohio State University, Computer Science and Engineering.
Social media websites provide an ideal environment for people to express their experiences on the latest events and share their knowledge about the current technologies along with research advancements. This presents an opportunity for Natural Language Processing (NLP) and Information Extraction (IE) technology to facilitate large scale data-analysis applications by extracting machine-processable information from user generated unstructured texts. However, information extraction from social media is particularly challenging due to the inherent noise induced by different writing styles of its users and their writing errors such as: typos and non-grammatical sentences. In this thesis, we explore the supervised and semi-supervised approaches to extract structured information from the noisy user generated texts of three widely used social web spaces: Twitter, StackOverflow and ProtocolIO.
Wei Xu (Advisor)
Alan Ritter (Advisor)
Feng Qin (Advisor)
115 p.
Artificial Intelligence; Computer Engineering; Computer Science; Linguistics
Natural Language Processing; Information Retrieval; Machine Learning; Social Media Analysis

Recommended Citations

Citations

  • Tabassum Binte Jafar, J. (2020). Information Extraction From User Generated Noisy Texts [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1606315356821532

    APA Style (7th edition)

  • Tabassum Binte Jafar, Jeniya. Information Extraction From User Generated Noisy Texts. 2020. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1606315356821532.

    MLA Style (8th edition)

  • Tabassum Binte Jafar, Jeniya. "Information Extraction From User Generated Noisy Texts." Doctoral dissertation, Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1606315356821532

    Chicago Manual of Style (17th edition)

osu1606315356821532
438
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This open access ETD is published by The Ohio State University and OhioLINK.