SIGKDD(KDD) 2011 论文列表
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 21-24, 2011.
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Web information extraction using markov logic networks.
User-level sentiment analysis incorporating social networks.
User-click modeling for understanding and predicting search-behavior.
Towards bounding sequential patterns.
ThermoCast: a cyber-physical forecasting model for datacenters.
Temporal multi-hierarchy smoothing for estimating rates of rare events.
Spatially regularized logistic regression for disease mapping on large moving populations.
Serendipitous learning: learning beyond the predefined label space.
Scalable kNN search on vertically stored time series.
Sampling hidden objects using nearest-neighbor oracles.
Revisiting sequential pattern hiding to enhance utility.
Real-time bidding algorithms for performance-based display ad allocation.
Ranking-based classification of heterogeneous information networks.
Protecting location privacy using location semantics.
Prominent streak discovery in sequence data.
Probabilistic topic models with biased propagation on heterogeneous information networks.
Privacy-preserving social network publication against friendship attacks.
Personal privacy vs population privacy: learning to attack anonymization.
Ontology enhancement and concept granularity learning: keeping yourself current and adaptive.
On the privacy of anonymized networks.
On dynamic data-driven selection of sensor streams.
MultiRank: co-ranking for objects and relations in multi-relational data.
Multi-view transfer learning with a large margin approach.
Mining partially annotated images.
Mining mobility user profiles for car pooling.
Mining mobility data to minimise travellers' spending on public transport.
Mining closed episodes with simultaneous events.
Meta optimization and its application to portfolio selection.
Logical-shapelets: an expressive primitive for time series classification.
Latent graphical models for quantifying and predicting patent quality.
Incorporating SAT solvers into hierarchical clustering algorithms: an efficient and flexible approach.
INCONCO: interpretable clustering of numerical and categorical objects.
Improving predictions using aggregate information.
I want to answer; who has a question?: Yahoo! answers recommender system.
Human mobility, social ties, and link prediction.
GBASE: a scalable and general graph management system.
Friendship and mobility: user movement in location-based social networks.
Fast locality-sensitive hashing.
Fast coordinate descent methods with variable selection for non-negative matrix factorization.
Fast approximate similarity search based on degree-reduced neighborhood graphs.
Exploiting place features in link prediction on location-based social networks.
Entity disambiguation with hierarchical topic models.
Diversified ranking on large graphs: an optimization viewpoint.
Display advertising impact: search lift and social influence.
Discovering spatio-temporal causal interactions in traffic data streams.
Discovering shakers from evolving entities via cascading graph inference.
Discovering highly reliable subgraphs in uncertain graphs.
Cost-aware travel tour recommendation.
Content-driven trust propagation framework.
Compression of weighted graphs.
Common component analysis for multiple covariance matrices.
Clustering with relative constraints.
Classification of functional magnetic resonance imaging data using informative pattern features.
Brain effective connectivity modeling for alzheimer's disease by sparse gaussian bayesian network.
Axiomatic ranking of network role similarity.
Automatically tagging email by leveraging other users' folders.
Ask me better questions: active learning queries based on rule induction.
Approximate kernel k-means: solution to large scale kernel clustering.
Anomaly localization for network data streams with graph joint sparse PCA.
An iterated graph laplacian approach for ranking on manifolds.
An effective evaluation measure for clustering on evolving data streams.
Algorithms for speeding up distance-based outlier detection.
Active learning using on-line algorithms.
Active learning for node classification in assortative and disassortative networks.
A time-dependent topic model for multiple text streams.
A simple statistical model and association rule filtering for classification.
A multi-task learning formulation for predicting disease progression.
A GPU-tailored approach for training kernelized SVMs.
A game theoretic framework for heterogenous information network clustering.
2D-interval predictions for time series.
Thriving as a data miner in the real world.
The practitioner's viewpoint to data mining: key lessons learned in the trenches and case studies.
The power of analysis and data.
Real-time risk control system for CNP (card not present).
Operational security analytics: doing more with less.
Knowledge discovery and data mining in pharmaceutical cancer research.
Broad scale predictive modeling and marketing optimization in retail sales.
Applications of data mining and machine learning in online customer care.
Accelerating large-scale data mining using in-database analytics.
"Which half Is wasted?": controlled experiments to measure online-advertising effectiveness.
Video analytics solution for tracking customer locations in retail shopping malls.
Topic-level social network search.
Social flocks: a crowd simulation framework for social network generation, community detection, and collective behavior modeling.
SIGKDD demo: sensors and software to allow computational entomology, an emerging application of data mining.
MIME: a framework for interactive visual pattern mining.
LikeMiner: a system for mining the power of 'like' in social media networks.
Frontex real-time news event extraction framework.
Data intensive analysis on the gordon high performance data and compute system.
Article clipper: a system for web article extraction.
Apolo: interactive large graph sensemaking by combining machine learning and visualization.
A taxi business intelligence system.
Two-locus association mapping in subquadratic time.
Multi-source domain adaptation and its application to early detection of fatigue.
Bounded coordinate-descent for biological sequence classification in high dimensional predictor space.
Selective block minimization for faster convergence of limited memory large-scale linear models.
Clustering very large multi-dimensional datasets with MapReduce.
Fast clustering using MapReduce.
Triangle listing in massive networks and its applications.
It's who you know: graph mining using recursive structural features.
Dual active feature and sample selection for graph classification.
Online heterogeneous mixture modeling with marginal and copula selection.
Unsupervised clustering of multidimensional distributions using earth mover distance.
Density estimation trees.
Latent aspect rating analysis without aspect keyword supervision.
Localized factor models for multi-context recommendation.
Latent topic feedback for information retrieval.
Mining frequent closed graphs on evolving data streams.
Direct local pattern sampling by efficient two-step random procedures.
Tell me what i need to know: succinctly summarizing data with itemsets.
An information theoretic framework for data mining.
Leakage in data mining: formulation, detection, and avoidance.
Stackelberg games for adversarial prediction problems.
Leveraging collaborative tagging for web item design.
Sparsification of influence networks.
On the semantic annotation of places in location-based social networks.
Exploiting vulnerability to secure user privacy on a social networking site.
k-NN as an implementation of situation testing for discrimination discovery and prevention.
Differentially private data release for data mining.
Tracking trends: incorporating term volume into temporal topic models.
Conditional topical coding: an efficient topic model conditioned on rich features.
Refining causality: who copied from whom?
Partially labeled topic models for interpretable text mining.
Collaborative topic modeling for recommending scientific articles.
Beyond keyword search: discovering relevant scientific literature.
Democrats, republicans and starbucks afficionados: user classification in twitter.
Smoothing techniques for adaptive online language models: topic tracking in tweet streams.
Predictive client-side profiles for personalized advertising.
Matching unstructured product offers to structured product specifications.
Toward personalized care management of patients at risk: the diabetes case study.
Detecting bots via incremental LS-SVM learning with dynamic feature adaptation.
A case study in a recommender system based on purchase data.
Understanding atrophy trajectories in alzheimer's disease using association rules on MRI images.
Experiences with mining temporal event sequences from electronic medical records: initial successes and some challenges.
Ameliorating buyer's remorse.
Classification of proxy labeled examples for marketing segment generation.
NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce.
Interactive learning for efficiently detecting errors in insurance claims.
Driving with knowledge from the physical world.
A pattern discovery approach to retail fraud detection.
From market baskets to mole rats: using data mining techniques to analyze RFID data describing laboratory animal behavior.
Enhancing investment decisions in P2P lending: an investor composition perspective.
Applying data mining techniques to address disaster information management challenges on mobile devices.
Detecting adversarial advertisements in the wild.
Bid landscape forecasting in online ad exchange marketplace.
Data-driven multi-touch attribution models.
Estimating the number of users behind ip addresses for combating abusive traffic.
Activity analysis based on low sample rate smart meters.
High-precision phrase-based document classification on a modern scale.
Combining file content and file relations for cloud based malware detection.
Linear scale semantic mining algorithms in microsoft SQL server's semantic platform.
Learning to trade off between exploration and exploitation in multiclass bandit prediction.
Unbiased online active learning in data streams.
Online active inference and learning.
Enabling fast prediction for ensemble models on data streams.
Selecting a comprehensive set of reviews.
User reputation in a comment rating environment.
From bias to opinion: a transfer-learning approach to real-time sentiment analysis.
Response prediction using collaborative filtering with hierarchies and side-information.
Click shaping to optimize multiple objectives.
Multiple domain user personalization.
Scalable distributed inference of dynamic user interests for behavioral targeting.
Benefits of bias: towards better characterization of network sampling.
Semi-supervised ranking on very large graphs with rich metadata.
Collective graph identification.
Diversity in ranking via resistive graph centers.
Large-scale matrix factorization with distributed stochastic gradient descent.
Rank aggregation via nuclear norm minimization.
Model order selection for boolean matrix factorization.
Integrating low-rank and group-sparse structures for robust multi-task learning.
An improved GLMNET for l1-regularized logistic regression.
Trading representability for scalability: adaptive multi-hyperplane machine for nonlinear classification.
Supervised learning for provenance-similarity of binaries.
CHIRP: a new classifier based on composite hypercubes on iterated random projections.
The mathematics of causal inference.
Cancer genomics.
Internet scale data analysis.
Convex optimization: from embedded real-time to large-scale distributed.
