شماره ركورد كنفرانس :
1730
عنوان مقاله :
Extending Fuzzy C-means to Clustering Data Streams
عنوان به زبان ديگر :
Extending Fuzzy C-means to Clustering Data Streams
پديدآورندگان :
Mostafavi Sara نويسنده , Amiri Ali نويسنده
كليدواژه :
Fuzzy clustering , Fuzzy C-Means , Fuzzy C-Means , DATA MINING , KDD-CUP99 data set , data stream clustering , data stream
عنوان كنفرانس :
بيستمين كنفرانس مهندسي برق ايران
چكيده لاتين :
A data stream is an ordered and continuous sequence of examples that can be examined only once. Data stream mining introduces new challenges compared to traditionalmining algorithms. Fuzzy c-means (FCM) is a method of clustering in which a data point can assign to more than onecluster at the same time. In this paper we extend FCM algorithm to clustering data streams. Our performance experiments over KDD-CUP’99 data set show the efficiency ofthe algorithm
شماره مدرك كنفرانس :
4460809
