?url_ver=Z39.88-2004&rft_id=arXiv%3A1612.07636&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.relation=http%3A%2F%2Feprints.imtlucca.it%2F4030%2F&rft.title=ScienceWISE%3A+Topic+Modeling+over+Scientific+Literature+Networks&rft.creator=Martini%2C+Andrea&rft.creator=Lutov%2C+Artem&rft.creator=Gemmetto%2C+Valerio&rft.creator=Magalich%2C+Andrii&rft.creator=Cardillo%2C+Alessio&rft.creator=Constantin%2C+Alex&rft.creator=Palchykov%2C+Vasyl&rft.creator=Khayati%2C+Mourad&rft.creator=Cudre-Mauroux%2C+Philippe&rft.creator=Boyarsky%2C+Alexey&rft.creator=Ruchayskiy%2C+Oleg&rft.creator=Garlaschelli%2C+Diego&rft.creator=Rios%2C+Paolo+De+De&rft.creator=Aberer%2C+Karl&rft.subject=QC+Physics&rft.description=We+provide+an+up-to-date+view+on+the+knowledge+management+system+ScienceWISE+(SW)+and+address+issues+related+to+the+automatic+assignment+of+articles+to+research+topics.+So+far%2C+SW+has+been+proven+to+be+an+effective+platform+for+managing+large+volumes+of+technical+articles+by+means+of+ontological+concept-based+browsing.+However%2C+as+the+publication+of+research+articles+accelerates%2C+the+expressivity+and+the+richness+of+the+SW+ontology+turns+into+a+double-edged+sword%3A+a+more+fine-grained+characterization+of+articles+is+possible%2C+but+at+the+cost+of+introducing+more+spurious+relations+among+them.+In+this+context%2C+the+challenge+of+continuously+recommending+relevant+articles+to+users+lies+in+tackling+a+network+partitioning+problem%2C+where+nodes+represent+articles+and+co-occurring+concepts+create+edges+between+them.+In+this+paper%2C+we+discuss+the+three+research+directions+we+have+taken+for+solving+this+issue%3A+i)+the+identification+of+generic+concepts+to+reinforce+inter-article+similarities%3B+ii)+the+adoption+of+a+bipartite+network+representation+to+improve+scalability%3B+iii)+the+design+of+a+clustering+algorithm+to+identify+concepts+for+cross-disciplinary+articles+and+obtain+fine-grained+topics+for+all+articles.&rft.publisher=arXiv&rft.date=2017&rft.type=Working+Paper&rft.type=NonPeerReviewed&rft.format=application%2Fpdf&rft.language=en&rft.rights=cc_by_nc&rft.identifier=http%3A%2F%2Feprints.imtlucca.it%2F4030%2F1%2F1612.07636.pdf&rft.identifier=++Martini%2C+Andrea+and+Lutov%2C+Artem+and+Gemmetto%2C+Valerio+and+Magalich%2C+Andrii+and+Cardillo%2C+Alessio+and+Constantin%2C+Alex+and+Palchykov%2C+Vasyl+and+Khayati%2C+Mourad+and+Cudre-Mauroux%2C+Philippe+and+Boyarsky%2C+Alexey+and+Ruchayskiy%2C+Oleg+and+Garlaschelli%2C+Diego+and+Rios%2C+Paolo+De+De+and+Aberer%2C+Karl++ScienceWISE%3A+Topic+Modeling+over+Scientific+Literature+Networks.++Working+Paper+++arXiv+++++++(Submitted)+++&rft.relation=http%3A%2F%2Farxiv.org%2Fpdf%2F1612.07636&rft.relation=arXiv%3A1612.07636