| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000334329 |
| 005 | | 20250203144715 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438283879 |
| 035 | |
▼a (MiAaPQ)AAI10969871 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a O'Brien, Michael Patrick. |
| 245 | 12 |
▼a A Multifaceted Approach to Improving the Practicality of Structural Graph Algorithms. |
| 260 | |
▼a [S.l.] :
▼b North Carolina State University.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 147 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
| 500 | |
▼a Adviser: Blair D. Sullivan. |
| 502 | 1 |
▼a Thesis (Ph.D.)--North Carolina State University, 2018. |
| 520 | |
▼a Graph algorithms have become an integral part of modern data analytics, but existing approaches have struggled to scale to increasing network sizes. The theoretical computer science community has a rich history of research that circumvents these |
| 520 | |
▼a This dissertation focuses on alleviating practical barriers to the use of structural graph algorithms in large-scale data analytics, addressing problems on multiple different fronts. First, we show that some structural features can still be iden |
| 590 | |
▼a School code: 0155. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a North Carolina State University.
▼b Computer Science. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0155 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15001288
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 정현우 |