Robust Dynamic Topic Derivation Implementation

Nugroho, Robertus Setiawan Aji Robust Dynamic Topic Derivation Implementation. Technical Report. Unika Soegijapranata. (Unpublished)

	Text (Laporan Penelitian) Dynamic Topic Derivation Infrastructure.pdf Restricted to Registered users only Download (5MB) | Request a copy
	Text (Surat Tugas) ST Pak Aji Penelitian Robust Dynamic.pdf Download (4MB)
	Text (Pengesahan dan Review) pengesahanHadoop.pdf Download (29kB)

Abstract

There are quite a few algorithms and methods available to derive topics from social media in near real time fashion. Recently, the approach to incorporate both social interactions and content has shown a significant improvement on the quality of identified topics. However, the performance of the implementation has not yet been visited. Most of the existing works have focused on a static dataset and might not be effective for an online situation. This research is the second part of the previous work on proposing a new approach for performing a dynamic topic derivation process in social media. The approach considers the sensitivity of keywords and time period to improve the accuracy of the topic derivation process. In this research, we will test different configurations to find the most effective and efficient infrastucture setup.

Item Type:	Monograph (Technical Report)
Subjects:	000 Computer Science, Information and General Works 000 Computer Science, Information and General Works > 004 Data processing & computer science 000 Computer Science, Information and General Works > 005 Computer programming, programs & data > Internet
Divisions:	Faculty of Computer Science > Department of Informatics Engineering
Depositing User:	Mr R. Setiawan Aji Nugroho
Date Deposited:	14 Sep 2020 03:19
Last Modified:	14 Sep 2020 03:19
URI:	http://repository.unika.ac.id/id/eprint/22017

Actions (login required)

View Item