An Application of Knowledge Discovery in Textual Databases to Identify Sentiments in Product Reviews
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- Type
- article
- Published
- 2014-11-24
- Cited by
- 0
- References
- 31
- OpenAlex
- https://openalex.org/W309031467
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:60410611
Keywords
Computer science, Knowledge extraction, Product (mathematics), Data science, Database
References
- Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
- Business Intelligence Success Factors: Tools for Aligning Your Business in the Global Economy
- Mining Opinion Features in Customer Reviews
- Clustering product features for opinion mining
- A Comparison of Collocation-Based Similarity Measures in Query Expansion
- Extended Naive Bayes classifier for mixed data
- Support-Vector Networks
- Measures of Distributional Similarity
- Sentiment Analysis and Subjectivity
- Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques
- Aspect Extraction through Semi-Supervised Modeling
- Orange: data mining toolbox in python
- The WEKA data mining software: an update
- Sentiment Learning on Product Reviews via Sentiment Ontology Tree
- Opinion observer: analyzing and comparing opinions on the Web
- NLTK: The Natural Language Toolkit
- Modeling Review Comments
- Thumbs up? Sentiment Classification using Machine Learning Techniques
- An introduction to support vector machines for data mining
- Sentiment Analysis and Opinion Mining
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