D-MFCLMin: A New Algorithm for Extracting Frequent Conceptual Links from Social Networks

Abstract

Massive amounts of data in social networks have made researchers look for ways to display a summary of the information provided and extract knowledge from them. One of the new approaches to describe knowledge of the social network is through a concise structure called conceptual view. In order to build this view, it is first needed to extract conceptual links from the intended network. However, extracting these links for large scale networks is very time consuming. In this paper, a new algorithm for extracting frequent conceptual link from social networks is provided where by introducing the concept of dependency, it is tried to accelerate the process of extracting conceptual links. Although the proposed algorithm will be able to accelerate this process if there are dependencies between data, but the tests carried out on Pokec social network, which lacks dependency between its data, revealed that absence of dependency, increases execution time of extracting conceptual links only up to 15 percent.

Authors and Affiliations

Hamid Tabatabaee

Keywords

Related Articles

An Optimized Inset Feed Circular Cross Strip Antenna Design for C-Band Satellite Links

This proposed antenna model and progressing the investigation of an inset fed wideband circular slotted patch antenna is suitable for 5.2 GHz satellite C-band applications. A circularly shaped slot has been chosen to be...

Robust R Peak and QRS detection in Electrocardiogram using Wavelet Transform

In this paper a robust R Peak and QRS detection using Wavelet Transform has been developed. Wavelet Transform provides efficient localization in both time and frequency. Discrete Wavelet Transform (DWT) has been used to...

Modeling and Control of a Multi-Machine Traction System Connected in Series using Two Static Converter

Power may be segmented either at the converter, using a multilevel inverter, either at the machine, by performing a polyphase winding. Moreover, increasing numbers of phases enables improved power quality and reducing to...

HappyMeter: An Automated System for Real-Time Twitter Sentiment Analysis

The paper presents HappyMeter, an automated system for real-time Twitter sentiment analysis. More than 380 million tweets consisting of nearly 30,000 words, almost 6,000 hashtags and over 5,000 user mentioned have been s...

Using Social Signal of Hesitation in Multimedia Content Retrieval

This paper presents the graphical analysis of selection traces in matrix-factorization space of multimedia items. A trace consists of links (lines) between points that present a selected item during interaction between u...

Download PDF file
  • EP ID EP259119
  • DOI 10.14569/IJACSA.2017.081240
  • Views 88
  • Downloads 0

How To Cite

Hamid Tabatabaee (2017). D-MFCLMin: A New Algorithm for Extracting Frequent Conceptual Links from Social Networks. International Journal of Advanced Computer Science & Applications, 8(12), 315-321. https://europub.co.uk/articles/-A-259119