The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
SenticNet 3: A Common and Common-Sense Knowledge Base for Cognition-Driven Sentiment Analysis
Open accessAbstract
SenticNet is a publicly available semantic and affective resource for concept-level sentiment analysis. Rather than using graph-mining and dimensionality-reduction techniques, SenticNet 3 makes use of "energy flows" to connect various parts of extended common and common-sense knowledge representations to one another. SenticNet 3 models nuanced semantics and sentics (that is, the conceptual and affective information associated with multi-word natural language expressions), representing information with a symbolic opacity of an intermediate nature between that of neural networks and typical symbolic systems.
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Cites
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Freebase: a collaboratively created graph database for structuring human knowledge
Bollacker, K., Evans, C., Paritosh, P., Sturge, T., & Taylor, J. (2008) · Proceedings of the 2008 ACM SIGMOD international conference on Management of data · doi:10.1145/1376616.1376746 · Cited by 4,852
Maximum Likelihood from Incomplete Data via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1976) · Cited by 4,517
A Survey of Clustering Data Mining Techniques
Berkhin, P. (2006) · Grouping Multidimensional Data · doi:10.1007/3-540-28349-8_2 · Cited by 2,804
Yago: a core of semantic knowledge
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DBpedia - A crystallization point for the Web of Data
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Cited by
A survey on opinion mining and sentiment analysis: Tasks, approaches and applications
Ravi, K., & Ravi, V. (2015) · Knowledge-Based Systems · doi:10.1016/j.knosys.2015.06.015 · Cited by 1,306
Affective Computing and Sentiment Analysis
Cambria, E. (2016) · IEEE Intelligent Systems · doi:10.1109/mis.2016.31 · Cited by 1,204
Self-citationA review: Knowledge reasoning over knowledge graph
Chen, X., Jia, S., & Xiang, Y. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2019.112948 · Cited by 1,035
Fusing audio, visual and textual clues for sentiment analysis from multimodal content
Poria, S., Cambria, E., Howard, N., Huang, G.-B., & Hussain, A. (2016) · Neurocomputing · doi:10.1016/j.neucom.2015.01.095 · Cited by 534
Self-citationSentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods
Ribeiro, F. N., Araújo, M., Gonçalves, P., André Gonçalves, M., & Benevenuto, F. (2016) · EPJ Data Science · doi:10.1140/epjds/s13688-016-0085-1 · Cited by 468
Metadata
- Authors
- Cambria, E., Olsher, D., & Rajagopal, D.
- Venue
- Proceedings of the AAAI Conference on Artificial Intelligence
- Published
- 2014-06-21
- Volume
- 28
- Issue
- 1
- ISSN
- 2159-5399 (ISSN-L)
- 2374-3468
- OpenAlex
- W2296734373
- Cited by
- 438
- References
- 34
- FWCI
- 37.16
- Type
- conference paper
- Language
- en
- Open access
- diamond
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- Cambria, E., Olsher, D., & Rajagopal, D. (2014). SenticNet 3: A Common and Common-Sense Knowledge Base for Cognition-Driven Sentiment Analysis. Proceedings of the AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v28i1.8928
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