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Schema- and Data-aware Query Reformulation in Knowledge Graphs
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Schema- and Data-aware Query Reformulation in Knowledge Graphs. |
| 개인저자 | Kannan, Amar Viswanathan. |
| 단체저자명 | Rensselaer Polytechnic Institute. Computer Science. |
| 발행사항 | [S.l.]: Rensselaer Polytechnic Institute., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 146 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438206892 |
| 학위논문주기 | Thesis (Ph.D.)--Rensselaer Polytechnic Institute, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: James Alexander Hendler. |
| 요약 | 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 |
| 요약 | 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 |
| 일반주제명 | Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
