Next Article in Journal
Learning Algorithm of Boltzmann Machine Based on Spatial Monte Carlo Integration Method
Previous Article in Journal
Connectivity and Hamiltonicity of Canonical Colouring Graphs of Bipartite and Complete Multipartite Graphs
Open AccessArticle

A Distributed Indexing Method for Timeline Similarity Query

by 1,* and 2
School of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China
Department of Computer Science, University of Idaho, 875 Perimeter Drive MS 1010, Moscow, ID 83844-1010, USA
Author to whom correspondence should be addressed.
Algorithms 2018, 11(4), 41;
Received: 10 February 2018 / Revised: 27 March 2018 / Accepted: 29 March 2018 / Published: 30 March 2018
Timelines have been used for centuries and have become more and more widely used with the development of social media in recent years. Every day, various smart phones and other instruments on the internet of things generate massive data related to time. Most of these data can be managed in the way of timelines. However, it is still a challenge to effectively and efficiently store, query, and process big timeline data, especially the instant recommendation based on timeline similarities. Most existing studies have focused on indexing spatial and interval datasets rather than the timeline dataset. In addition, many of them are designed for a centralized system. A timeline index structure adapting to parallel and distributed computation framework is in urgent need. In this research, we have defined the timeline similarity query and developed a novel timeline index in the distributed system, called the Distributed Triangle Increment Tree (DTI-Tree), to support the similarity query. The DTI-Tree consists of one T-Tree and one or more TI-Trees based on a triangle increment partition strategy with the Apache Spark. Furthermore, we have provided an open source timeline benchmark data generator, named TimelineGenerator, to generate various timeline test datasets for different conditions. The experiments for DTI-Tree’s construction, insertion, deletion, and similarity queries have been executed on a cluster with two benchmark datasets that are generated by TimelineGenerator. The experimental results show that the DTI-tree provides an effective and efficient distributed index solution to big timeline data. View Full-Text
Keywords: timelines; interval data; DTI-tree; distributed index; timeline generator timelines; interval data; DTI-tree; distributed index; timeline generator
Show Figures

Figure 1

MDPI and ACS Style

He, Z.; Ma, X. A Distributed Indexing Method for Timeline Similarity Query. Algorithms 2018, 11, 41.

AMA Style

He Z, Ma X. A Distributed Indexing Method for Timeline Similarity Query. Algorithms. 2018; 11(4):41.

Chicago/Turabian Style

He, Zhenwen; Ma, Xiaogang. 2018. "A Distributed Indexing Method for Timeline Similarity Query" Algorithms 11, no. 4: 41.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop