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In this work we propose Inclusive vector to keep the key words available in natural language database. The inclusive vectors are generated by the process of extraction of words given in the source and the cited items of records published in the ISI Thompson Citation Indexes. The proposed inclusive vector exhibits related words and the degree of their relationships. In this work we present the results...
The main goal of Biomedical Natural Language Processing (BioNLP) is to capture biomedical phenomena from textual data by extracting relevant entities, information and relations between biomedical entities (i.e. proteins and genes). In general, in most of the published papers, only binary relations were extracted. In a recent past, the focus is shifted towards extracting more complex relations in the...
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