Fast Clustering of Short Text Streams Using Efficient Cluster Indexing and Dynamic Similarity Thresholds

01/21/2021
by   Md Rashadul Hasan Rakib, et al.
0

Short text stream clustering is an important but challenging task since massive amount of text is generated from different sources such as micro-blogging, question-answering, and social news aggregation websites. One of the major challenges of clustering such massive amount of text is to cluster them within a reasonable amount of time. The existing state-of-the-art short text stream clustering methods can not cluster such massive amount of text within a reasonable amount of time as they compute similarities between a text and all the existing clusters to assign that text to a cluster. To overcome this challenge, we propose a fast short text stream clustering method (called FastStream) that efficiently index the clusters using inverted index and compute similarity between a text and a selected number of clusters while assigning a text to a cluster. In this way, we not only reduce the running time of our proposed method but also reduce the running time of several state-of-the-art short text stream clustering methods. FastStream assigns a text to a cluster (new or existing) using the dynamically computed similarity thresholds based on statistical measure. Thus our method efficiently deals with the concept drift problem. Experimental results demonstrate that FastStream outperforms the state-of-the-art short text stream clustering methods by a significant margin on several short text datasets. In addition, the running time of FastStream is several orders of magnitude faster than that of the state-of-the-art methods.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

01/31/2020

Enhancement of Short Text Clustering by Iterative Classification

Short text clustering is a challenging task due to the lack of signal co...
05/27/2019

Scaling Fine-grained Modularity Clustering for Massive Graphs

Modularity clustering is an essential tool to understand complicated gra...
06/10/2015

Fast Online Clustering with Randomized Skeleton Sets

We present a new fast online clustering algorithm that reliably recovers...
02/14/2020

Clustering based on Point-Set Kernel

Measuring similarity between two objects is the core operation in existi...
01/13/2022

Improved Multi-objective Data Stream Clustering with Time and Memory Optimization

The analysis of data streams has received considerable attention over th...
01/26/2021

Event-Driven News Stream Clustering using Entity-Aware Contextual Embeddings

We propose a method for online news stream clustering that is a variant ...
10/11/2020

GuCNet: A Guided Clustering-based Network for Improved Classification

We deal with the problem of semantic classification of challenging and h...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.