More recently, StreamCube approach [2] introduces a method to perform multi-dimensional, multi-level, on-line analysis of data streams. This proposition is.
Multidimensional Data Stream Summarization Using Extended Tilted-Time Windows. Abstract: Nowadays, servers register more and more log entries. Monitoring ...
Multidimensional Data Stream Summarization Using Extended. Tilted-Time Windows ... patterns in data streams at multiple time granularities, 2002. [2] J. Han ...
These functions define for each granularity level of each dimension the minimal interval of a Tilted Time Windows to avoid storing unqueried or computable data.
Multidimensional Data Stream Summarization Using Extended Tilted-Time Windows · Stream Cube: An Architecture for Multi-Dimensional Analysis of Data Streams.
In this paper, we propose a summarization method for multidimensional data streams based on a graph structure and taking advantage of the data hierarchies. The ...
In this paper, we present a multi-dimensional and multi-granular data warehousing schema (MMDW). MMDW is based on Relational OLAP (ROLAP) and uses a RDBMS to ...
Multidimensional Data Stream Summarization Using Extended Tilted-Time Windows ... Summarizing multidimensional data streams: A hierarchy-graph-based approach.
In this paper, we propose a summarization method for multidi- mensional data streams based on a graph structure and taking advantage of the data hierarchies.
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Three models for tilted time windows. 3.1. Tilted time frame. 203. In stream data analysis, people are usually interested in recent changes ...
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