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020 ▼a 9780438206892
035 ▼a (MiAaPQ)AAI10790816
035 ▼a (MiAaPQ)rpi:11313
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 004
1001 ▼a Kannan, Amar Viswanathan.
24510 ▼a Schema- and Data-aware Query Reformulation in Knowledge Graphs.
260 ▼a [S.l.]: ▼b Rensselaer Polytechnic Institute., ▼c 2018.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2018.
300 ▼a 146 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: James Alexander Hendler.
5021 ▼a Thesis (Ph.D.)--Rensselaer Polytechnic Institute, 2018.
520 ▼a In today's age of Linked Data and Knowledge Graph proliferation, complex SPARQL queries returning results in the billions are ubiquitous. However, when such a query does not return the intended answers, the onus is on the user to resolve the sch
520 ▼a In this approach an input SPARQL query that contains schema or taxonomic concepts and instance data (entity data) is reformulated to give alternate ranked reformulations that are similar to the original query. Viewing a query as a conjunction of
590 ▼a School code: 0185.
650 4 ▼a Computer science.
690 ▼a 0984
71020 ▼a Rensselaer Polytechnic Institute. ▼b Computer Science.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0185
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997607 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 201812 ▼f 2019
990 ▼a ***1012033