Dass, Rajanish

English

Research Papers in Economics

A fast majority vote algorithm,

A Regression-Based Temporal Pattern Mining Scheme for Data Streams.

A Simple Algorithm For Finding Frequent Elements In Streams And Bags.&quot;

A Sliding Window Method for Finding Recently Frequent Itemsets over Online Data Streams.&quot;

Adaptive Mining Techniques for Data Streams using Algorithm Output Granularity. It was a workshop named- The Australasian Data Mining Workshop (AusDM

Adaptive Mining Techniques for Data Streams Using Algorithm Output Granularity. The Australasian Data Mining Workshop (AusDM

Algorithms and frameworks for stream mining and knowledge discovery on Grids,

An algorithm for in-core frequent itemset mining on streaming data.&quot; ICDM

An effcient algorithm for closed itemset mining. 2nd SIAM Int'l Conf. on Data Mining.

An Implementation of the FPgrowth Algorithm. Workshop Open Source Data Mining Software.

An Intuitive Framework for Understanding Changes in Evolving Data Streams.

Approximate frequency counts over data streams.

Approximate Mining of Frequent Patterns on Streams.

Catch the Moment: Maintaining Closed Frequent Itemsets over a Data Stream Sliding Window,

Catching Up with the Data: Research Issues in Mining Data Streams.

Computing iceberg queries efficiently.

Cost-Efficient Mining Techniques for Data Streams. the second workshop on Australasian information security,

Data Streams: Algorithms and Applications. Fourteenth annual ACM-SIAM symposium on discrete algorithms.

Discovering Frequent Tree Patterns over Data Streams.

Fast, small-space algorithms for approximate histogram maintenance.

Finding a majority among n votes: Solution to problem.&quot;

Finding Frequent items in data streams.

Finding hierarchical heavy hitters in data streams.

Finding recent frequent itemsets adaptively over online data streams.

Finding repeated elements.&quot;

Issues in Data Stream Management.&quot;

Load Shedding for Aggregation Queries over Data Streams.

Maintaining Stream Statistics Over Sliding Windows (Extended Abstract).

Mining data streams - a review.&quot;

Mining Data Streams for Frequent Sequences Extraction,

Mining Data Streams under Block Evolution.&quot;

Mining Frequent Patterns in Data Streams at Multiple Time Granularities.

Mining Frequent Patterns in Data Streams at Multiple Time Granularities. Next Generation Data Mining AAAI/MIT.

Mining Frequent Patterns without Candidate Generation.

Mining Sequential Patterns Across Data Streams,

Mining Sequential Patterns from Multidimensional Squence.&quot;

Mining Sequential Patterns:

Mining Sequential Patterns. Data Eng.

Models and issues in data stream systems.

New sampling-based summary statistics for improving approximate query answers.

On mining webclick streams for path traversal patterns.

Online Mining of Changes from Data Streams:Research Problems and Preliminary Results.&quot;

Querying and mining data streams: you only get one look a tutorial. The

Research Issues in Data Stream Association Rule Mining.&quot;

Sampling from a moving window over Streaming data.&quot;

Sampling large database for association rules.

StatStream: Statistical monitoring of thousands of data streams in real time.

Tilted-Time Window Implementation,

What's hot and what's not: tracking most frequent items dynamically.&quot;

When to Update the sequential patterns of stream data.

Mining Frequent Item sets in Data Streams

http://www.iimahd.ernet.in/assets/snippets/workingpaperpdf/2008-01-06Dass.pdf

Mining Frequent Item sets in Data Streams

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Research Papers in Economics