OntoSenticNet: A Commonsense Ontology for Sentiment Analysis

被引：101

作者：

Dragoni, Mauro ^{[1
]}

Poria, Soujanya ^{[2
]}

Cambria, Erik ^{[3
]}

机构：

[1] Fdn Bruno Kessler, Povo, Italy

[2] Nanyang Technol Univ, Temasek Labs, Singapore, Singapore

[3] Nanyang Technol Univ, Singapore, Singapore

来源：

IEEE INTELLIGENT SYSTEMS | 2018年 / 33卷 / 03期

关键词：

CHALLENGES;

D O I：

10.1109/MIS.2018.033001419

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work, we present OntoSenticNet, a commonsense ontology for sentiment analysis based on SenticNet, a semantic network of 100,000 concepts based on conceptual primitives. The key characteristics of OntoSenticNet are: (i) the definition of precise conceptual hierarchy and properties associating concepts and sentiment values; (ii) the support for connecting external information (e.g., word embedding, domain information, and different polarity representations) to each individual defined within the ontology; and (iii) the capability of associating each concept with annotations contained in external resources (e.g., documents and multimodal resources).

引用

页码：77 / 85

页数：9

共 20 条

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[Anonymous], 2016, arXiv preprint arXiv:1610.08815

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[3]

[Anonymous], 2015, SENTIC COMPUTING COM

[4]

[Anonymous], 2016, COLING 2016 26 INT C