September 2024
Intermediate to advanced
290 pages
8h 19m
German
Content preview from Wissensgraphen aufbauen
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Kapitel 6. Anreicherung von Wissensgraphenmit Data Science
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In diesem Kapitel lernst du Graph Data Science kennen. Das Ziel von Graph Data Science ist es, mithilfe von Graphalgorithmen Einblicke in deinen Wissensgraphen zu gewinnen. Um dieses Ziel zu erreichen, erfährst du auf , welche Arten von Graphalgorithmen es gibt und welche Erkenntnisse sie liefern. erfährst du, wie Neo4j Graph Data Science eine einfache Plattform für das Experimentieren mit Graphalgorithmen, deren Austausch und die Entwicklung von Produkten bietet. Du lernst auch, wie du Graphalgorithmen auf realen Wissensgraphen ausführst und erfährst, wie das System einen Großteil der Arbeit für dich übernimmt.
Wie Kapitel 3 soll auch dieses Kapitel nicht umfassend sein, sondern dir die Grundlagen für den Rest des Buches vermitteln. Für diejenigen, die mehr in die Tiefe gehen wollen, gibt es viele gute Bücher, die sich speziellen technischen Themen widmen, z. B. Graph Data Science for Dummies von Dr. Alicia Frame und Zach Blumenfeld (Wiley).
Warum Graph-Algorithmen?
Graphenalgorithmen liefern Erkenntnisse über die Struktur eines Wissensgraphen. Dabei kann es sich um einflussreiche Personen in einem sozialen Graphen, um kritische Knotenpunkte in einem Schienennetz, um Zellen von Betrügern oder um einen gemeinsamen Erreger in einem Krankheitsverlauf handeln. Während der Entwurf und die Implementierung ...
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