Heterogeneous Information Network Analysis and Applications
Seiten
2017
|
1st ed. 2017
Springer International Publishing (Verlag)
978-3-319-56211-7 (ISBN)
Springer International Publishing (Verlag)
978-3-319-56211-7 (ISBN)
This book offers researchers an understanding of the fundamental issues and a good starting point to work on this rapidly expanding field. It provides a comprehensive survey of current developments of heterogeneous information network. It also presents the newest research in applications of heterogeneous information networks to similarity search, ranking, clustering, recommendation.
This information will help researchers to understand how to analyze networked data with heterogeneous information networks. Common data mining tasks are explored, including similarity search, ranking, and recommendation. The book illustrates some prototypes which analyze networked data.
Professionals and academics working in data analytics, networks, machine learning, and data mining will find this content valuable. It is also suitable for advanced-level students in computer science who are interested in networking orpattern recognition.
This information will help researchers to understand how to analyze networked data with heterogeneous information networks. Common data mining tasks are explored, including similarity search, ranking, and recommendation. The book illustrates some prototypes which analyze networked data.
Professionals and academics working in data analytics, networks, machine learning, and data mining will find this content valuable. It is also suitable for advanced-level students in computer science who are interested in networking orpattern recognition.
1. Introduction.- 2. Summarization of the developments.- 3.Uniform relevance measure of heterogeneous objects.- 4. Path based Ranking.- 5. Ranking based Clustering.- 6. Recommendation with heterogeneous information.- 7. Information fusion with heterogeneous network.- 8. Prototype system.- 9. Future research directions.- 10. Conclusion.
Erscheinungsdatum | 10.06.2017 |
---|---|
Reihe/Serie | Data Analytics |
Zusatzinfo | IX, 227 p. 62 illus., 53 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 526 g |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Mathematik / Informatik ► Informatik ► Netzwerke | |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Technik ► Nachrichtentechnik | |
Schlagworte | Artificial Intelligence • artificial intelligence (incl. robotics) • Clustering • Communications Engineering, Networks • Communications engineering / telecommunications • Computer Communication Networks • Computer Science • Data Mining • data mining and knowledge discovery • Expert systems / knowledge-based systems • Heterogeneous information network • Homogeneous information network • machine learning • Meta path • Networked data • network hardware • Network schema • pattern recognition • Ranking • Recommendation • Robotics • Similarity Search • social network analysis • Social Networks |
ISBN-10 | 3-319-56211-8 / 3319562118 |
ISBN-13 | 978-3-319-56211-7 / 9783319562117 |
Zustand | Neuware |
Haben Sie eine Frage zum Produkt? |
Mehr entdecken
aus dem Bereich
aus dem Bereich
Datenanalyse für Künstliche Intelligenz
Buch | Softcover (2024)
De Gruyter Oldenbourg (Verlag)
74,95 €
Auswertung von Daten mit pandas, NumPy und IPython
Buch | Softcover (2023)
O'Reilly (Verlag)
44,90 €