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  1. No Access

    Chapter and Conference Paper

    SpecGreedy: Unified Dense Subgraph Detection

    How can we effectively detect fake reviews or fraudulent connections on a website? How can we spot communities that suddenly appear based on users’ interaction? And how can we efficiently find the minimum cut ...

    Wenjie Feng, Shenghua Liu, Danai Koutra… in Machine Learning and Knowledge Discovery i… (2021)

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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...

    Di **, Mark Heimann, Ryan A. Rossi… in Machine Learning and Knowledge Discovery i… (2020)

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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...

    Mark Heimann, Wei Lee, Shengjie Pan… in Advances in Knowledge Discovery and Data M… (2018)

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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...

    U. Kang, Jay-Yoon Lee, Danai Koutra… in Advances in Knowledge Discovery and Data M… (2014)

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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?

    Yibin Lin, Agha Ali Raza, Jay-Yoon Lee… in Advances in Knowledge Discovery and Data M… (2014)

  6. No Access

    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...

    Miguel Araujo, Spiros Papadimitriou… in Advances in Knowledge Discovery and Data M… (2014)

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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...

    Danai Koutra, Vasileios Koutras… in Advances in Knowledge Discovery and Data M… (2013)

  8. 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...

    Danai Koutra, Tai-You Ke, U. Kang… in Machine Learning and Knowledge Discovery i… (2011)

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