L
Lise Getoor
Researcher at University of California, Santa Cruz
Publications - 342
Citations - 22696
Lise Getoor is an academic researcher from University of California, Santa Cruz. The author has contributed to research in topics: Probabilistic logic & Statistical relational learning. The author has an hindex of 69, co-authored 326 publications receiving 20288 citations. Previous affiliations of Lise Getoor include University of California & Ames Research Center.
Papers
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Journal ArticleDOI
Collective Classification in Network Data
TL;DR: This article introduces four of the most widely used inference algorithms for classifying networked data and empirically compare them on both synthetic and real-world data.
Book
Introduction to statistical relational learning
Lise Getoor,Ben Taskar +1 more
TL;DR: In Introduction to Statistical Relational Learning, leading researchers in this emerging area of machine learning describe current formalisms, models, and algorithms that enable effective and robust reasoning about richly structured systems and data.
Journal ArticleDOI
Link mining: a survey
Lise Getoor,Christopher P. Diehl +1 more
TL;DR: While network analysis has been studied in depth in particular areas such as social network analysis, hypertext mining, and web analysis, only recently has there been a cross-fertilization of ideas among these different communities.
Book ChapterDOI
Learning Probabilistic Relational Models
TL;DR: This paper describes both parameter estimation and structure learning -- the automatic induction of the dependency structure in a model and shows how the learning procedure can exploit standard database retrieval techniques for efficient learning from large datasets.
Book ChapterDOI
Link-based classification
Qing Lu,Lise Getoor +1 more
TL;DR: This paper proposes a framework for modeling link distributions, a link-based model that supports discriminative models describing both the link distributions and the attributes of linked objects, and uses a structured logistic regression model, capturing both content and links.