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Computational Time and Space Tradeof...

Regalia, Blake D.

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Computational Time and Space Tradeoffs in Geo Knowledge Graphs.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational Time and Space Tradeoffs in Geo Knowledge Graphs./
作者:	Regalia, Blake D.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	165 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-04, Section: B.
Contained By:	Dissertations Abstracts International82-04B.
標題:	Information science. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27743454
ISBN:	9798678120601

Computational Time and Space Tradeoffs in Geo Knowledge Graphs.
Regalia, Blake D.

Computational Time and Space Tradeoffs in Geo Knowledge Graphs. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 165 p.

Source: Dissertations Abstracts International, Volume: 82-04, Section: B.

Thesis (Ph.D.)--University of California, Santa Barbara, 2020.

This item must not be sold to any third party vendors.

Over the past several years, the Web of Linked Data has continued to grow in size, both in terms of the breadth of domains covered as well as the depth and precision of knowledge. As a consequence to this growth, the community has been led to confront challenges that arise from incorporating large-scale geographic information into knowledge graphs. These challenges include data quality, data storage, data transmission, and the scaling of geospatial query processing. A crucial concern in real-time computing is about striking a balance between the time complexity of algorithms and memory consumption or data storage (i.e., space). Given a computational problem and the domain of its inputs, there are several decisions that researchers, engineers, and practitioners must make based on the constraints of available computational resources, as well as the desired program's `reaction' time for the sake of human-computer interaction. Understanding how to strike such a balance requires a thorough understanding of the data structures and algorithms used to solve a problem. Geospatial data and geospatial queries in particular require innovators to possess deep background knowledge in order to research and develop viable solutions. As a geographic information scientist working with Linked Data, I attempt to improve the quality, accessibility, reliability, and query performance of geographic data in knowledge graphs. In this dissertation, I study three specific trade-offs: (i) whether certain geographic properties and relations should be computed on-demand or materialized beforehand; (ii) whether carefully precomputing topological relations is more useful than providing users with geometries to compute topological relations on-demand; and finally, (iii) whether the challenges of hosting public geographic knowledge graph services on the Web can be mitigated, and at what cost, by a peer-to-peer architecture in which the clients possess more intelligence.

ISBN: 9798678120601Subjects--Topical Terms:

554358
Information science.
Subjects--Index Terms:

GeoSPARQL

Computational Time and Space Tradeoffs in Geo Knowledge Graphs.
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