In this paper, a novel approach is introduced for building semantic networks from scientific publ... more In this paper, a novel approach is introduced for building semantic networks from scientific publication abstracts. With a seed statement as input, the approach generates a semantic network using Recursive Object Modeling (ROM), Skip-gram language modelling, and semantic similarity methods. Semantic Scholar API was used to retrieve data for building the ROM-based Semantic Networks (RomNet) following Environment-Based Design (EBD) methodology. The RomNet is then applied to an aircraft braking system design. The work includes two major contributions: a ROM-based phrase extractor and a Skip-gram model trained on automatically collected publication abstracts data. The phrase extractor was compared with two existing off-the-shelf key phrase extraction algorithms, namely TextRank and Rake. The ROM-based phrase extractor is capable of extracting most key phrases from target domains and shows higher precision, recall, and F-1 scores than other methods. The Skip-gram language model was evalu...
In this paper, a novel approach is introduced for building semantic networks from scientific publ... more In this paper, a novel approach is introduced for building semantic networks from scientific publication abstracts. With a seed statement as input, the approach generates a semantic network using Recursive Object Modeling (ROM), Skip-gram language modelling, and semantic similarity methods. Semantic Scholar API was used to retrieve data for building the ROM-based Semantic Networks (RomNet) following Environment-Based Design (EBD) methodology. The RomNet is then applied to an aircraft braking system design. The work includes two major contributions: a ROM-based phrase extractor and a Skip-gram model trained on automatically collected publication abstracts data. The phrase extractor was compared with two existing off-the-shelf key phrase extraction algorithms, namely TextRank and Rake. The ROM-based phrase extractor is capable of extracting most key phrases from target domains and shows higher precision, recall, and F-1 scores than other methods. The Skip-gram language model was evalu...
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Papers by Amin Bayatpour