Social Sciences Via Network Analysis and Computation

ISBN-13: 9783631665220 / Angielski / Miękka / 2015 / 127 str.

Tadej Kanduc; Tadej Kanduc

Opis

Information and communication technologies have gained significant importance in the social sciences. This study presents some of the results, practices and approaches in network analysis, machine learning, data mining, data clustering and classifications in the contents of social sciences.

Spis treści

Contents: Joze Bucar/Janez Povh/Andrej Dobrovoljc: Web Clipping and Sentiment Analysis of Slovenian news articles - Renato Barisic/Joze Bucar: Machine Learning in Classification of News Portal Articles - Hana Rizvic/Sanda Martincic-Ipsic/Ana Mestrovic: Network Motifs Analysis of Croatian Literature - Sabina Sisovic/Sanda Martincic-Ipsic/Ana Mestrovic: Toward Network-based Keyword Extraction from Multitopic Web Documents - Darko Zelenika/Andrej Dobrovoljc/Robert Pezdirc/Helena Novosel/Simon Kegljevic/Janez Povh/Bernard Zenko: Automatic invoice capture in small and medium-sized Slovenian enterprises - project report - Bostjan Delak: Information System Mirror - Approach How to Analyze Information System Strengths and Weaknesses within Organization - Stefana Janicijevic/Dragan Urosevic/Nenad Mladenovic: Comparison of SAS/STAT Procedures and Variable Neighborhood Search Based Clustering Applied on Telekom Serbia Data - Rok Piltaver/Mitja Lustrek/Matjaz Gams/Sanda Martincic-Ipsic: Measuring Classification-Tree Comprehensibility - Borut Luzar/Mirko Petrusevski/Riste Skrekovski: On vertex-parity and weak vertex-parity edge-colorings - Vesna Andova/Frantisek Kardos/Riste Skrekovski: Diameter on some classes of fullerene graphs.

O autorze

Tadej Kanduc is a researcher at the Faculty of Information Studies in Novo mesto, Slovenia. His work focuses on discrete and agent based modelling and simulation, optimisation algorithms and parallel programming.