Classification of Citation Sentence for Filtering Scientific References
| Autor: | Masayu Leylia Khodra, Ghoziyah Haitan Rachman, Dwi H. Widyantoro |
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| Rok vydání: | 2019 |
| Předmět: |
Relation (database)
Computer science business.industry 020206 networking & telecommunications 02 engineering and technology computer.software_genre Automatic summarization Bag-of-words model 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Citation business GeneralLiterature_REFERENCE(e.g. dictionaries encyclopedias glossaries) computer Sentence Natural language processing |
| Zdroj: | 2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE). |
| DOI: | 10.1109/icitisee48480.2019.9003736 |
| Popis: | Citation sentence is able to inform readers about relation between scientific articles that cite and are cited by finding its purpose against the research. Besides giving credit to other researchers and recommendation to read other related articles, citation can help readers to know what knowledge they have obtained based on the cited scientific articles they have read. In this research, we try to define citation categories for filtering scientific references which will be initial step in guided summarization of scientific articles. Our goal is to classify citation sentence first into ‘problem’, ‘other’, ‘useModel’, ‘useTool’ and ‘useData’. This category will make it easier to classify scientific articles into more specific topics. Then we use features namely voice, tenses, citation location, meta-discourse and bag of words. Then, we employ SVM Linear for building classification model and sampling technique, namely SMOTE for imbalance dataset. The best result of f-measure for our citation classification is achieved at 61.2% when combining voice& tense, meta-discourse, bag of words and sampling the feature data of UseData category with SMOTE. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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