Principles and Methods For Recommendation Framework
| Autor: | Kavitha S, Ranjana R. Badre |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Risk analysis (engineering)
Scope (project management) Computer science 020204 information systems 0202 electrical engineering electronic engineering information engineering Key (cryptography) 020201 artificial intelligence & image processing Unstructured data 02 engineering and technology Recommender system Data modeling |
| Zdroj: | 2018 4th International Conference on Computing Communication and Automation (ICCCA). |
| DOI: | 10.1109/ccaa.2018.8777575 |
| Popis: | Structured, semi-structured and unstructured data is growing exponentially. The exponential increase in the data resulted in providing a plethora of alternatives for items, services and products. In e-commerce, recommender systems have become the most powerful tool to avoid choice overload. People who lack effective proficiency to evaluate the various alternatives can use Recommender systems. Poor decision making is due to the exponential growth of information and the convention of new e-business services like comparison of products, auction, purchase of products etc. This paper outline the key concepts used in recommendation systems and elucidate different recommendation approaches using content based, collaborative and hybrid methods. The paper reviews the drawbacks of various recommendation methods and the possible future scope to enhance the performance of recommendation systems. Several approaches are addressed in this paper to deal with the common cold start and data sparsity problems. The paper also proposes a hybrid recommendation system, which provides a recommendation based on the score for each scenario. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|