Sentiment Analysis Based on Support Vector Machine and Big Data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU120166" target="_blank" >RIV/00216305:26220/16:PU120166 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/document/7760939" target="_blank" >https://ieeexplore.ieee.org/document/7760939</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TSP.2016.7760939" target="_blank" >10.1109/TSP.2016.7760939</a>

Result language

angličtina

Original language name

Sentiment Analysis Based on Support Vector Machine and Big Data

Original language description

This paper deals with sentiment analysis in text documents, especially text valence detection. The proposed solution is based on Support Vector Machines classifier. This classifier was trained with huge amount of data and complex word combinations were analysed. For this purpose distributed learning on 112 processors was used. Datasets used for training and testing were automatically obtained from real user feedback on products from different web pages (and different product segments). The proposed solution has been evaluated with different languages – English, German, Czech and Spanish. This paper improves accuracy achieved with the Big Data approach about 11%. The best accuracy achieved in this work was 95.31% for recognition of positive and negative text valence. The described learning is fully automatic, can be applied to any language and no complicated preprocessing is needed.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2016

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 39th International Conference on Telecommunication and Signal Processing, TSP 2016

ISBN

978-1-5090-1287-9

ISSN

—

e-ISSN

—

Number of pages

3

Pages from-to

543-545

Publisher name

Neuveden

Place of publication

Vídeň

Event location

Vídeň

Event date

Jun 27, 2016

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000390164000118