Learning and Knowledge-Based Sentiment Analysis in Movie Review Key Excerpts

Schuller, Björn; Knaup, Tobias

doi:10.1007/978-3-642-18184-9_39

Cited by 19 publications

(7 citation statements)

References 20 publications

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“…Consequently, other researchers investigated the use of completely knowledge-based sentiment analysis [7], or models that combine knowledge-based and machine learning-based sentiment analysis [8,9]. For example, [9] presents a Two-Stage Hybrid Model (TSHM), which contains a knowledge repository as well as a machine-learning component.…”

Section: Introductionmentioning

confidence: 99%

SOBA: Semi-automated Ontology Builder for Aspect-based sentiment analysis

Zhuang

Schouten

Frăsincar

2020

Journal of Web Semantics

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Section: Introductionmentioning

confidence: 99%

SOBA: Semi-automated Ontology Builder for Aspect-based sentiment analysis

Zhuang

Schouten

Frăsincar

2020

Journal of Web Semantics

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“…Schuller and Knaup [120] designed a method for Opinion Mining applied to reviews that relies on the combined knowledge of three online resources: The General Inquirer [121], WordNet [59] and ConceptNet [122]. The General Inquirer returns the sentiment valence of a given verb or adjective with 1 corresponding to a positive valence and -1 to a negative valence.…”

Section: Fusion Of Resourcesmentioning

confidence: 99%

Opinion Mining and Information Fusion: A survey

2016

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“…While lexical databases such as WN is developed for lexical categorization and word-similarity determination and FN is optimized to describe a particular type of situation and event, CN is used for making practical context-based inferences (Schuller & Knaup, 2011). The main goal of developing CN is to capture common-sense knowledge that describe the real world (Hsu et al, 2006;Wu & Tsai, 2014).…”

Section: Conceptnetmentioning

confidence: 99%

Towards knowledge modeling and manipulation technologies: A survey

Bimba

Al-Hunaiyyan

Mahmud

et al. 2016

International Journal of Information Management

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A system which represents knowledge is normally referred to as a knowledge based system (KBS). This article focuses on surveying publications related to knowledge base modelling and manipulation technologies, between the years 2000-2015. A total of 185 articles excluding the subject descriptive articles which are mentioned in the introductory parts, were evaluated in this survey. The main aim of this study is to identify different knowledge base modelling and manipulation techniques based on 4 categories; 1) linguistic knowledge base; 2) expert knowledge base; 3) ontology and 4) cognitive knowledge base. This led to the proposition of 8 research questions, which focused on the different categories of knowledge base modelling technologies, their underlying theories, knowledge representation technique, knowledge acquisition technique, challenges, applications, development tools and development languages. A part of the findings from this survey is the high dependence of linguistic knowledge base, expert knowledge base and ontology on volatile expert knowledge. A promising technique for knowledge-based business management and other knowledge related applications is also discussed.

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Learning and Knowledge-Based Sentiment Analysis in Movie Review Key Excerpts

Cited by 19 publications

References 20 publications

SOBA: Semi-automated Ontology Builder for Aspect-based sentiment analysis

SOBA: Semi-automated Ontology Builder for Aspect-based sentiment analysis

Opinion Mining and Information Fusion: A survey

Towards knowledge modeling and manipulation technologies: A survey

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