The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Summary of WWW characterizations
World Wide Web
Discovery of climate indices using clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Eigenspace-based anomaly detection in computer systems
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
On the Bursty Evolution of Blogspace
World Wide Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Object-level ranking: bringing order to Web objects
WWW '05 Proceedings of the 14th international conference on World Wide Web
BRAID: stream mining through group lag correlations
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
The predictive power of online chatter
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Google's PageRank and Beyond: The Science of Search Engine Rankings
Google's PageRank and Beyond: The Science of Search Engine Rankings
Local Correlation Tracking in Time Series
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
StatStream: statistical monitoring of thousands of data streams in real time
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Continuous subspace clustering in streaming time series
Information Systems
Computing Correlation Anomaly Scores Using Stochastic Nearest Neighbors
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Establishing relationships among patterns in stock market data
Data & Knowledge Engineering
Detecting leaders from correlated time series
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Mining tribe-leaders based on the frequent pattern of propagation
APWeb'12 Proceedings of the 14th international conference on Web Technologies and Applications
Exploiting space-time status for service recommendation
APWeb'12 Proceedings of the 14th international conference on Web Technologies and Applications
A time decoupling approach for studying forum dynamics
World Wide Web
Mining most frequently changing component in evolving graphs
World Wide Web
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Nowadays, World Wide Web is full of rich information, including text data, XML data, multimedia data, time series data, etc. The web is usually represented as a large graph and PageRank is computed to rank the importance of web pages. In this paper, we study the problem of ranking evolving time series and discovering leaders from them by analyzing lead-lag relations. A time series is considered to be one of the leaders if its rise or fall impacts the behavior of many other time series. At each time point, we compute the lagged correlation between each pair of time series and model them in a graph. Then, the leadership rank is computed from the graph, which brings order to time series. Based on the leadership ranking, the leaders of time series are extracted. However, the problem poses great challenges since the dynamic nature of time series results in a highly evolving graph, in which the relationships between time series are modeled. We propose an efficient algorithm which is able to track the lagged correlation and compute the leaders incrementally, while still achieving good accuracy. Our experiments on real weather science data and stock data show that our algorithm is able to compute time series leaders efficiently in a real-time manner and the detected leaders demonstrate high predictive power on the event of general time series entities, which can enlighten both weather monitoring and financial risk control.