The recent advances in hardware and software have enabled the capture of different measurements of data in a wide range of fields. These measurements are generated continuously and in a very high fluctuating data rates. Examples include sensor networks, web logs, and computer network traffic. The storage, querying and mining of such data sets are highly computationally challenging tasks. Mining data streams is concerned with extracting knowledge structures represented in models and patterns in non stopping streams of information. The research in data stream mining has gained a high attraction due to the importance of its applications and the increasing generation of streaming information. Applications of data stream analysis can vary from c...
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low di...
Abstract-Applications such as satellite networks, telecommunication systems etc., are generating mas...
Abstract. In this paper we propose a new method to perform incremen-tal discretization. The basic id...
Conventional data mining deals with static data stored on disk, for example, using the current state...
Data stream processing has gained increasing popularity in the last few years as an effective paradi...
Data mining aims at discovering valid, novel and potentially useful patterns from data. Over last tw...
Streaming data is becoming more prevalent in our society every day. With the increasing use of techn...
AbstractData Stream Mining is one of the area gaining lot of practical significance and is progressi...
The data stream model for data mining places harsh restrictions on a learning algorithm. First, a mo...
A growing number of applications that generate massive streams of data need intelligent dataprocessi...
With the development of computing systems in every sector of activity, more and more data is now ava...
A data stream is a continuous and high-speed flow of data items. High speed refers to the phenomenon...
Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the l...
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with exam...
Abstract — Traditional databases store sets of relatively static records without the concept of time...
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low di...
Abstract-Applications such as satellite networks, telecommunication systems etc., are generating mas...
Abstract. In this paper we propose a new method to perform incremen-tal discretization. The basic id...
Conventional data mining deals with static data stored on disk, for example, using the current state...
Data stream processing has gained increasing popularity in the last few years as an effective paradi...
Data mining aims at discovering valid, novel and potentially useful patterns from data. Over last tw...
Streaming data is becoming more prevalent in our society every day. With the increasing use of techn...
AbstractData Stream Mining is one of the area gaining lot of practical significance and is progressi...
The data stream model for data mining places harsh restrictions on a learning algorithm. First, a mo...
A growing number of applications that generate massive streams of data need intelligent dataprocessi...
With the development of computing systems in every sector of activity, more and more data is now ava...
A data stream is a continuous and high-speed flow of data items. High speed refers to the phenomenon...
Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the l...
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with exam...
Abstract — Traditional databases store sets of relatively static records without the concept of time...
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low di...
Abstract-Applications such as satellite networks, telecommunication systems etc., are generating mas...
Abstract. In this paper we propose a new method to perform incremen-tal discretization. The basic id...