Advances in Machine Learning and Data Science pp 113-120 | Cite as
Keyphrase and Relation Extraction from Scientific Publications
Conference paper
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Abstract
This paper proposes a detailed view of extracting keyphrases and its relations from scientifically published articles such as research papers using conditional random fields (CRF). Keyphrase is a word or set of words that describe the close relationship of content and context in particular documents (Sharan, International conference on advances in computing communications and informatics (ICACCI), 2014) [1]. Keyphrases may be the topics of the document which represent the key logic of the document. Automatic keyphrase extraction has a major role in automatic systems like independent summarization, query or topic generation, question-answering system, search engine, information retrieval, document classification, etc. The relationships of the keyphrases are also extracted. Two types of relations are considered—synonym and hyponyms. The result shows that our proposed system outperforms the existing systems.
Keywords
Keyphrase extraction Topic extraction Information extraction (IE) Summarization Question answering (QA) Document classificationReferences
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