Abstract. In this paper we consider concurrent execution of multiple data mining queries. If such data mining queries operate on similar parts of the database, then their overall I/O cost can be reduced by integrating their data retrieval operations. The integration requires that many data mining queries are present in memory at the same time. If the memory size is not sufficient to hold all the data mining queries, then the queries must be scheduled into multiple phases of loading and processing. We discuss the problem of data mining query scheduling and propose a heuristic algorithm to efficiently schedule the data mining queries into phases
This work addresses the problem of sharing execution plans for queries that continuously cluster str...
Database systems frequently have to execute a batch of related queries. Multi-query optimization exp...
In addition to storing and managing the data and providing capabilities to query them, aDatabase Man...
Abstract. In this paper we consider concurrent execution of multiple data mining queries in the cont...
Frequent itemset mining is often regarded as advanced querying where a user specifies the source dat...
Abstract: Frequent itemset mining is often regarded as ad-vanced querying where a user species the s...
Abstract. In this paper we address the problem of processing of batches of frequent itemset queries ...
Multi-relational data mining algorithms search a large hypothesis space in order to find a suitable ...
In the current work, we derive a complete approach to optimization and automatic parallelization of ...
In this paper, we investigate two scheduling approaches for multicomputer-based parallel database sy...
Abstract:- In this paper, we propose a new solution for dynamic task scheduling in distributed envir...
Data stream systems process persistent queries, typically posed over sliding windows and re-evaluate...
Abstract. Frequent itemset mining is one of fundamental data mining problems that shares many simila...
Query scheduling plays an important role when systems are faced with limited resources and high wor...
Abstract:- Distributed data mining plays a crucial role in knowledge discovery in very large databas...
This work addresses the problem of sharing execution plans for queries that continuously cluster str...
Database systems frequently have to execute a batch of related queries. Multi-query optimization exp...
In addition to storing and managing the data and providing capabilities to query them, aDatabase Man...
Abstract. In this paper we consider concurrent execution of multiple data mining queries in the cont...
Frequent itemset mining is often regarded as advanced querying where a user specifies the source dat...
Abstract: Frequent itemset mining is often regarded as ad-vanced querying where a user species the s...
Abstract. In this paper we address the problem of processing of batches of frequent itemset queries ...
Multi-relational data mining algorithms search a large hypothesis space in order to find a suitable ...
In the current work, we derive a complete approach to optimization and automatic parallelization of ...
In this paper, we investigate two scheduling approaches for multicomputer-based parallel database sy...
Abstract:- In this paper, we propose a new solution for dynamic task scheduling in distributed envir...
Data stream systems process persistent queries, typically posed over sliding windows and re-evaluate...
Abstract. Frequent itemset mining is one of fundamental data mining problems that shares many simila...
Query scheduling plays an important role when systems are faced with limited resources and high wor...
Abstract:- Distributed data mining plays a crucial role in knowledge discovery in very large databas...
This work addresses the problem of sharing execution plans for queries that continuously cluster str...
Database systems frequently have to execute a batch of related queries. Multi-query optimization exp...
In addition to storing and managing the data and providing capabilities to query them, aDatabase Man...