NDLI: Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs

Please wait, while we are loading the content...

Graphons and Machine Learning: Modeling and Estimation of Sparse Massive Networks

Big Data Needs Big Dreamers: Lessons from Successful Big Data Investors

Designing Policy Recommendations to Reduce Home Abandonment in Mexico

Can You Teach the Elephant to Dance? AKA: Culture Eats Data Science for Breakfast

MAP: Frequency-Based Maximization of Airline Profits based on an Ensemble Forecasting Approach

Compact and Scalable Graph Neighborhood Sketching

Optimal Reserve Prices in Upstream Auctions: Empirical Application on Online Video Advertising

Scalable Data Analytics Using R: Single Machines to Hadoop Spark Clusters

Learning to Learn and Compositionality with Deep Recurrent Neural Networks: Learning to Learn and Compositionality

Aircraft Trajectory Prediction Made Easy with Predictive Analytics

How Machine Learning has Finally Solved Wanamaker's Dilemma

Gemello: Creating a Detailed Energy Breakdown from Just the Monthly Electricity Bill

Streaming-LDA: A Copula-based Approach to Modeling Topic Dependencies in Document Streams

Burstiness Scale: A Parsimonious Model for Characterizing Random Series of Events

Lifelong Machine Learning and Computer Reading the Web

The Evolving Meaning of Information Security

Matrix Computations and Optimization in Apache Spark

Learning Sparse Models at Scale

CaSMoS: A Framework for Learning Candidate Selection Models over Structured Queries and Documents

Assessing Human Error Against a Benchmark of Perfection

MANTRA: A Scalable Approach to Mining Temporally Anomalous Sub-trajectories

IoT Big Data Stream Mining

People, Computers, and The Hot Mess of Real Data

Predicting Disk Replacement towards Reliable Data Centers

Profiling Users from Online Social Behaviors with Applications for Tencent Social Ads

Domain Adaptation in the Absence of Source Domain Data

Inferring Network Effects from Observational Data

From Prediction to Action: A Closed-Loop Approach for Data-Guided Network Resource Allocation

Mining Reliable Information from Passively and Actively Crowdsourced Data

A VC View of Investing in ML

Developing a Data-Driven Player Ranking in Soccer Using Predictive Model Weights

The Wisdom of Crowds: Best Practices for Data Prep & Machine Learning Derived from Millions of Data Science Workflows

Kam1n0: MapReduce-based Assembly Clone Search for Reverse Engineering

Communication Efficient Distributed Kernel Principal Component Analysis

Towards Robust and Versatile Causal Discovery for Business Applications

Streaming Analytics

The Legislative Influence Detector: Finding Text Reuse in State Legislation

Bayesian Optimization and Embedded Learning Systems

Joint Optimization of Multiple Performance Metrics in Online Video Advertising

Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns

Deep Visual-Semantic Hashing for Cross-Modal Retrieval

Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining

Identifying Police Officers at Risk of Adverse Events

Accelerating the Race to Autonomous Cars

Convolutional Neural Networks for Steady Flow Approximation

The Limits of Popularity-Based Recommendations, and the Role of Social Ties

Predicting Socio-Economic Indicators using News Events

Collective Sensemaking via Social Sensors: Extracting, Profiling, Analyzing, and Predicting Real-world Events

Data-Driven Metric Development for Online Controlled Experiments: Seven Lessons Learned

Large-Scale Machine Learning at Verizon: Theory and Applications

Computational Drug Repositioning Using Continuous Self-Controlled Case Series

Positive-Unlabeled Learning in Streaming Networks

City-Scale Map Creation and Updating using GPS Collections

Extracting Optimal Performance from Dynamic Time Warping

Catch Me If You Can: Detecting Pickpocket Suspects from Large-Scale Transit Records

Computational Social Science: Exciting Progress and Future Challenges

How to Get Them a Dream Job?: Entity-Aware Features for Personalized Job Search Ranking

FASCINATE: Fast Cross-Layer Dependency Inference on Multi-layered Networks

Compressing Convolutional Neural Networks in the Frequency Domain

Scalable Learning of Graphical Models

Email Volume Optimization at LinkedIn

Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis

Predicting Matchups and Preferences in Context

Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments

Leveraging Propagation for Data Mining: Models, Algorithms and Applications

Large-Scale Item Categorization in e-Commerce Using Multiple Recurrent Neural Networks

CompanyDepot: Employer Name Normalization in the Online Recruitment Industry

XGBoost: A Scalable Tree Boosting System

Multi-layer Representation Learning for Medical Concepts

CNTK: Microsoft's Open-Source Deep-Learning Toolkit

Online Dual Decomposition for Performance and Delivery-Based Distributed Ad Allocation

Understanding Behaviors that Lead to Purchasing: A Case Study of Pinterest

Robust Influence Maximization

Finding Gangs in War from Signed Networks

Healthcare Data Mining with Matrix Models

Minimizing Legal Exposure of High-Tech Companies through Collaborative Filtering Methods

Images Don't Lie: Transferring Deep Visual Semantic Features to Large-Scale Multimodal Learning to Rank

Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations

Efficient Processing of Network Proximity Queries via Chebyshev Acceleration

Business Applications of Predictive Modeling at Scale

Ranking Universities Based on Career Outcomes of Graduates

Text Mining in Clinical Domain: Dealing with Noise

Towards Conversational Recommender Systems

Latent Space Model for Road Networks to Predict Time-Varying Traffic

Predictors without Borders: Behavioral Modeling of Product Adoption in Three Developing Countries

Detecting Devastating Diseases in Search Logs

TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size

Compressing Graphs and Indexes with Recursive Graph Bisection

Repeat Buyer Prediction for E-Commerce

When Recommendation Goes Wrong: Anomalous Link Discovery in Recommendation Networks

A Subsequence Interleaving Model for Sequential Pattern Mining

Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test

Audience Expansion for Online Social Network Advertising

Deploying Analytics with the Portable Format for Analytics (PFA)

Efficient Frequent Directions Algorithm for Sparse Matrices

Recurrent Marked Temporal Point Processes: Embedding Event History to Vector

From Online Behaviors to Offline Retailing

Singapore in Motion: Insights on Public Transport Service Level Through Farecard and Mobile Data Analytics

node2vec: Scalable Feature Learning for Networks

Learning Cumulatively to Become More Knowledgeable

Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta

EMBERS AutoGSR: Automated Coding of Civil Unrest Events

Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification in Flu Virus Data

Squish: Near-Optimal Compression for Archival of Relational Datasets

DopeLearning: A Computational Approach to Rap Lyrics Generation

Compute Job Memory Recommender System Using Machine Learning

Joint Community and Structural Hole Spanner Detection via Harmonic Modularity

Fast Component Pursuit for Large-Scale Inverse Covariance Estimation

EMBERS at 4 years: Experiences operating an Open Source Indicators Forecasting System

Scalable Time-Decaying Adaptive Prediction Algorithm

Robust Influence Maximization

Meta Structure: Computing Relevance in Large Heterogeneous Information Networks

Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs

Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques

FRAUDAR: Bounding Graph Fraud in the Face of Camouflage

Robust and Effective Metric Learning Using Capped Trace Norm: Metric Learning via Capped Trace Norm

Engagement Capacity and Engaging Team Formation for Reach Maximization of Online Social Media Platforms

Crime Rate Inference with Big Data

Temporal Order-based First-Take-All Hashing for Fast Attention-Deficit-Hyperactive-Disorder Detection

Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations

Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments

Improving the Sensitivity of Online Controlled Experiments: Case Studies at Netflix

When Social Influence Meets Item Inference

Online Optimization Methods for the Quantification Problem

Dynamic and Robust Wildfire Risk Prediction System: An Unsupervised Approach

Talent Circle Detection in Job Transition Networks

Privacy-preserving Class Ratio Estimation

Smart Broadcasting: Do You Want to be Seen?

Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features

Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising

Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications

How to Compete Online for News Audience: Modeling Words that Attract Clicks

Question Independent Grading using Machine Learning: The Case of Computer Program Grading

CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors

Causal Clustering for 1-Factor Measurement Models

Contextual Intent Tracking for Personal Assistants

Smart Reply: Automated Response Suggestion for Email

Optimally Discriminative Choice Sets in Discrete Choice Models: Application to Data-Driven Test Design

An Empirical Study on Recommendation with Multiple Types of Feedback

Mining Subgroups with Exceptional Transition Behavior

Interpretable Decision Sets: A Joint Framework for Description and Prediction

An Engagement-Based Customer Lifetime Value System for E-commerce

Point-of-Interest Recommendations: Learning Potential Check-ins from Friends

Lightweight Monitoring of Distributed Streams

Identifying Earmarks in Congressional Bills

QUINT: On Query-Specific Optimal Networks

Bayesian Inference of Arrival Rate and Substitution Behavior from Sales Transaction Data with Stockouts

Evaluating Mobile Apps with A/B and Quasi A/B Tests

Dynamic Clustering of Streaming Short Documents

Parallel Lasso Screening for Big Data Optimization

Ranking Relevance in Yahoo Search

Rebalancing Bike Sharing Systems: A Multi-source Data Smart Optimization

A Multi-Task Learning Formulation for Survival Analysis

Identifying Decision Makers from Professional Social Networks

Unified Point-of-Interest Recommendation with Temporal Interval Assessment

A Real Linear and Parallel Multiple Longest Common Subsequences (MLCS) Algorithm

Batch Model for Batched Timestamps Data Analysis with Application to the SSA Disability Program

AnyDBC: An Efficient Anytime Density-based Clustering Algorithm for Very Large Complex Datasets

Multi-Task Feature Interaction Learning

Collaborative Knowledge Base Embedding for Recommender Systems

Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs

Infinite Ensemble for Image Clustering

GLMix: Generalized Linear Mixed Models For Large-Scale Response Prediction

Regime Shifts in Streams: Real-time Forecasting of Co-evolving Time Sequences

Scalable Pattern Matching over Compressed Graphs via Dedensification

A Non-parametric Approach to Detect Epileptogenic Lesions using Restricted Boltzmann Machines

Skinny-dip: Clustering in a Sea of Noise

Scalable Betweenness Centrality Maximization via Sampling

Recruitment Market Trend Analysis with Sequential Latent Variable Models

Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems

User Identity Linkage by Latent User Space Modelling

Days on Market: Measuring Liquidity in Real Estate Markets

Continuous Experience-aware Language Model

Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining

Structural Neighborhood Based Classification of Nodes in a Network

Predict Risk of Relapse for Patients with Multiple Stages of Treatment of Depression

Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning

Lossless Separation of Web Pages into Layout Code and Data

Asymmetric Transitivity Preserving Graph Embedding

Unbounded Human Learning: Optimal Scheduling for Spaced Repetition

PTE: Enumerating Trillion Triangles On Distributed Systems

Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding

Robust Large-Scale Machine Learning in the Cloud

Reconstructing an Epidemic Over Time

"Why Should I Trust You?": Explaining the Predictions of Any Classifier

Improving Survey Aggregation with Sparsely Represented Signals

ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages

Dynamics of Large Multi-View Social Networks: Synergy, Cannibalization and Cross-View Interplay

Sampling of Attributed Networks from Hierarchical Generative Models

Data-driven Automatic Treatment Regimen Development and Recommendation

Goal-Directed Inductive Matrix Completion

Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices

Graph Wavelets via Sparse Cuts

From Truth Discovery to Trustworthy Opinion Discovery: An Uncertainty-Aware Quantitative Modeling Approach

Lexis: An Optimization Framework for Discovering the Hierarchical Structure of Sequential Data

The Million Domain Challenge: Broadcast Email Prioritization by Cross-domain Recommendation

Towards Optimal Cardinality Estimation of Unions and Intersections with Sketches

Transfer Knowledge between Cities

Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure

Probabilistic Robust Route Recovery with Spatio-Temporal Dynamics

Just One More: Modeling Binge Watching Behavior

A Truth Discovery Approach with Theoretical Guarantee

Structural Deep Network Embedding

Towards Confidence in the Truth: A Bootstrapping based Truth Discovery Approach

Targeted Topic Modeling for Focused Analysis

Online Feature Selection: A Limited-Memory Substitution Algorithm and Its Asynchronous Parallel Variation

Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix

Absolute Fused Lasso and Its Application to Genome-Wide Association Studies

A Multiple Test Correction for Streams and Cascades of Statistical Hypothesis Tests

Diversified Temporal Subgraph Pattern Mining

Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability

Distributing the Stochastic Gradient Sampler for Large-Scale LDA

Robust Extreme Multi-label Learning

FUSE: Full Spectral Clustering

Taxi Driving Behavior Analysis in Latent Vehicle-to-Vehicle Networks: A Social Influence Perspective

A Text Clustering Algorithm Using an Online Clustering Scheme for Initialization

DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks

Convex Optimization for Linear Query Processing under Approximate Differential Privacy

GMove: Group-Level Mobility Modeling Using Geo-Tagged Social Media

Beyond Sigmoids: The NetTide Model for Social Network Growth, and Its Applications

Approximate Personalized PageRank on Dynamic Graphs

Online Context-Aware Recommendation with Time Varying Multi-Armed Bandit

Annealed Sparsity via Adaptive and Dynamic Shrinking

Accelerated Stochastic Block Coordinate Descent with Optimal Sampling

Partial Label Learning via Feature-Aware Disambiguation

Collaborative Multi-View Denoising

FINAL: Fast Attributed Network Alignment

Online Asymmetric Active Learning with Imbalanced Data

Come-and-Go Patterns of Group Evolution: A Dynamic Model

FLASH: Fast Bayesian Optimization for Data Analytic Pipelines

NetCycle: Collective Evolution Inference in Heterogeneous Information Networks

Portfolio Selections in P2P Lending: A Multi-Objective Perspective

Accelerating Online CP Decompositions for Higher Order Tensors

Hierarchical Incomplete Multi-source Feature Learning for Spatiotemporal Event Forecasting

Efficient Shift-Invariant Dictionary Learning

Topic Modeling of Short Texts: A Pseudo-Document View

Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs

Content Provider	ACM Digital Library
Author	Milajerdi, Sadegh M. Manzoor, Emaad Akoglu, Leman
Abstract	Given a stream of heterogeneous graphs containing different types of nodes and edges, how can we spot anomalous ones in real-time while consuming bounded memory? This problem is motivated by and generalizes from its application in security to host-level advanced persistent threat (APT) detection. We propose StreamSpot, a clustering based anomaly detection approach that addresses challenges in two key fronts: (1) heterogeneity, and (2) streaming nature. We introduce a new similarity function for heterogeneous graphs that compares two graphs based on their relative frequency of local substructures, represented as short strings. This function lends itself to a vector representation of a graph, which is (a) fast to compute, and (b) amenable to a sketched version with bounded size that preserves similarity. StreamSpot exhibits desirable properties that a streaming application requires: it is (i) fully-streaming; processing the stream one edge at a time as it arrives, (ii) memory-efficient; requiring constant space for the sketches and the clustering, (iii) fast; taking constant time to update the graph sketches and the cluster summaries that can process over 100,000 edges per second, and (iv) online; scoring and flagging anomalies in real time. Experiments on datasets containing simulated system-call flow graphs from normal browser activity and various attack scenarios (ground truth) show that StreamSpot is high-performance; achieving above 95% detection accuracy with small delay, as well as competitive time and memory usage.
Starting Page	1035
Ending Page	1044
Page Count	10
File Format	PDF MP4
ISBN	9781450342322
DOI	10.1145/2939672.2939783
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-08-13
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Evolving graphs Dynamic networks Typed graphs Graph sketches Temporal networks Heterogenous graphs Streamspot Anomaly detection
Content Type	Audio Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in