Machine Learning and Knowledge Discovery in Databases: Research Track
European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part II
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14 Result(s)
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Danai Koutra
Computer Science
English
Artificial Intelligence
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Book and Conference Proceedings
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Book and Conference Proceedings
Machine Learning and Knowledge Discovery in Databases: Research Track
European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part I
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Book and Conference Proceedings
Machine Learning and Knowledge Discovery in Databases: Research Track
European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part IV
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Book and Conference Proceedings
Machine Learning and Knowledge Discovery in Databases: Research Track
European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part III
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Book and Conference Proceedings
Machine Learning and Knowledge Discovery in Databases: Research Track
European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part V
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Chapter and Conference Paper
node2bits: Compact Time- and Attribute-Aware Node Representations for User Stitching
Identity stitching, the task of identifying and matching various online references (e.g., sessions over different devices and timespans) to the same user in real-world web services, is crucial for personalizatio...
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Article
Collaborative topic regression for predicting topic-based social influence
The rapid growth of social networks and their strong presence in our lives have attracted many researchers in social networks analysis. Users of social networks spread their opinions, get involved in discussio...
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Chapter and Conference Paper
HashAlign: Hash-Based Alignment of Multiple Graphs
Fusing or aligning two or more networks is a fundamental building block of many graph mining tasks (e.g., recommendation systems, link prediction, collective analysis of networks). Most past work has focused o...
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Article
Graph based anomaly detection and description: a survey
Detecting anomalies in data is a vital task, with numerous high-impact applications in areas such as security, finance, health care, and law enforcement. While numerous techniques have been developed in past y...
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Chapter and Conference Paper
Net-Ray: Visualizing and Mining Billion-Scale Graphs
How can we visualize billion-scale graphs? How to spot outliers in such graphs quickly? Visualizing graphs is the most direct way of understanding them; however, billion-scale graphs are very difficult to visu...
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Chapter and Conference Paper
Influence Propagation: Patterns, Model and a Case Study
When a free, catchy application shows up, how quickly will people notify their friends about it? Will the enthusiasm drop exponentially with time, or oscillate? What other patterns emerge?
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Chapter and Conference Paper
Com2: Fast Automatic Discovery of Temporal (‘Comet’) Communities
Given a large network, changing over time, how can we find patterns and anomalies? We propose Com2, a novel and fast, incremental tensor analysis approach, which can discover both transient and periodic/ repea...
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Chapter and Conference Paper
Patterns amongst Competing Task Frequencies: Super-Linearities, and the Almond-DG Model
If Alice has double the friends of Bob, will she also have double the phone-calls (or wall-postings, or tweets)? Our first contribution is the discovery that the relative frequencies obey a power-law (sub-line...
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Chapter and Conference Paper
Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms
If several friends of Smith have committed petty thefts, what would you say about Smith? Most people would not be surprised if Smith is a hardened criminal. Guilt-by-association methods combine weak signals to de...
