?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.relation=https%3A%2F%2Feprints.uet.vnu.edu.vn%2Feprints%2Fid%2Feprint%2F3983%2F&rft.title=Exploiting+document+graphs+for+inter-sentence+relation+extraction&rft.creator=Can%2C+Duy+Cat&rft.subject=Information+Technology+(IT)&rft.description=Background%3A+Most+previous+relation+extraction+(RE)+studies+have+focused+on+intra-sentence+relations+and+haveignored+relations+that+span+sentences%2C+i.e.+inter-sentence+relations.+Such+relations+connect+entities+at+thedocument+level+rather+than+as+relational+facts+in+a+single+sentence.+Extracting+facts+that+are+expressed+acrosssentences+leads+to+some+challenges+and+requires+different+approaches+than+those+usually+applied+in+recentintra-sentence+relation+extraction.+Despite+recent+results%2C+there+are+still+limitations+to+be+overcome.Results%3AWe+present+a+novel+representation+for+a+sequence+of+consecutive+sentences%2C+namely+documentsub-graph%2C+to+extract+inter-sentence+relations.+Experiments+on+the+BioCreative+V+Chemical-Disease+Relationcorpus+demonstrate+the+advantages+and+robustness+of+our+novel+system+to+extract+both+intra-+andinter-sentence+relations+in+biomedical+literature+abstracts.+The+experimental+results+are+comparable+tostate-of-the-art+approaches+and+show+the+potential+by+demonstrating+the+effectiveness+of+graphs%2C+deeplearning-based+model+and+other+processing+techniques.+Experiments+were+also+carried+out+to+verify+therationality+and+impact+of+various+additional+information+and+model+components.Conclusions%3AOur+proposed+graph-based+representation+helps+to+extract%E2%88%BC50%25+of+inter-sentence+relations+andboosts+the+model+performance+on+both+precision+and+recall+compared+to+the+baseline+model.&rft.publisher=BMC+Journal+of+Biomedical+Semantics&rft.date=2020&rft.type=Technical+Report&rft.type=NonPeerReviewed&rft.format=application%2Fpdf&rft.language=en&rft.identifier=https%3A%2F%2Feprints.uet.vnu.edu.vn%2Feprints%2Fid%2Feprint%2F3983%2F1%2FBMC_Journal_of_Biomedical_Semantics___manuscript__Copy_.pdf&rft.identifier=++Can%2C+Duy+Cat++(2020)+Exploiting+document+graphs+for+inter-sentence+relation+extraction.++Technical+Report.+BMC+Journal+of+Biomedical+Semantics.++++(Submitted)++