Personalized Recommendation with Confidence
| Autor: | Xiaoqin Shelley Zhang, Sadhana Kuthuru, Brahmi Mamillapalli, Rama Mara |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Information retrieval
Computer science 02 engineering and technology Recommender system Data science Preference Set (abstract data type) Knowledge-based systems Consistency (negotiation) Ranking Order (business) 020204 information systems 0202 electrical engineering electronic engineering information engineering Feature (machine learning) 020201 artificial intelligence & image processing Product (category theory) |
| Zdroj: | WI |
| DOI: | 10.1109/wi.2016.0099 |
| Popis: | This paper presents a personalized recommendation system mining online product reviews, fusing opinions together and providing a ranked order of a set similar products. We define three attributes of opinion summary: opinion coverage, opinion consistency and opinion consensus. Confidence factor is computed based on these attributes. A user specifies the relative importance of each product feature. The quantitive summary reflects the user's preference, the opinion synopsis and the confidence measurement. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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