Technical Papers Session I: Citation analysis of research articles (CARA)
Abstract/Description
In a research paper multiple citations and authors opinion about them are mentioned. Our primary focus is to identify which opinion is given on which citation and secondly to identify the exact sentence due to which citation has occurred in the citing paper. We have worked on two parallel approaches one is sentence level similarity, in which we try identifying the sentence(s) due to which citation has occurred. Other approach is article level similarity in which we identify the citation category and map anchor text to its citing article. We are able to show that an automated system can be created for identifying whether a sentence (without citation mark) is part of the citation text. In future we wish to extend this work with larger corpus and more sophisticated techniques.
Location
Lecture Hall A (Aman Tower, 12th floor)
Session Theme
Technical Papers Session I - Data Science
Session Type
Parallel Technical Session
Session Chair
Dr Shahid Shaikh
Start Date
16-11-2019 3:30 PM
End Date
16-11-2019 3:50 PM
Recommended Citation
Butt, B. H., Faquih, D., Hammad, M., & Nasir, S. (2019). Technical Papers Session I: Citation analysis of research articles (CARA). International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2019/2019/9
COinS
Technical Papers Session I: Citation analysis of research articles (CARA)
Lecture Hall A (Aman Tower, 12th floor)
In a research paper multiple citations and authors opinion about them are mentioned. Our primary focus is to identify which opinion is given on which citation and secondly to identify the exact sentence due to which citation has occurred in the citing paper. We have worked on two parallel approaches one is sentence level similarity, in which we try identifying the sentence(s) due to which citation has occurred. Other approach is article level similarity in which we identify the citation category and map anchor text to its citing article. We are able to show that an automated system can be created for identifying whether a sentence (without citation mark) is part of the citation text. In future we wish to extend this work with larger corpus and more sophisticated techniques.
