Combining Formal Logic and Machine Learning for Sentiment Analysis

Niklas Christoffer Petersen, Jørgen Villadsen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper presents a formal logical method for deep structural analysis of the syntactical properties of texts using machine learning techniques for efficient syntactical tagging. To evaluate the method it is used for entity level sentiment analysis as an alternative to pure machine learning methods for sentiment analysis, which often work on sentence or word level, and are argued to have difficulties in capturing long distance dependencies.
Original languageEnglish
Title of host publication Foundations of Intelligent Systems
EditorsT. Andreasen, H. Christiansen, J.-C. Cubero, Z.W. Ras
PublisherSpringer
Publication date2014
Pages375-384
ISBN (Print)978-3-319-08325-4
Publication statusPublished - 2014
Event21st International Symposium on Methodologies for Intelligent Systems (ISMIS 2014) - Roskilde, Denmark
Duration: 25 Jun 201427 Jun 2014
Conference number: 21
http://isl.ruc.dk/ismis2014/

Conference

Conference21st International Symposium on Methodologies for Intelligent Systems (ISMIS 2014)
Number21
CountryDenmark
CityRoskilde
Period25/06/201427/06/2014
Internet address
SeriesLecture Notes in Computer Science
Volume8502
ISSN0302-9743

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