| Autor: |
Manjusha Pandey, Siddharth Swarup Rautray, Chandrima Roy |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Smart Computing Techniques and Applications ISBN: 9789811615016 |
| DOI: |
10.1007/978-981-16-1502-3_45 |
| Popis: |
Recommender Systems are quite popular and very useful for predictions of various products to consumers by providing recommendations. It deals with the definite type of items and produces the recommendations that are personalized to deliver effective and valuable suggestions to the consumer. The cold-start problem is one of the challenges in recommender systems. The cold-start situation arrives when products added to the collection have either no experiences, or very little. This causes a challenge for collaborative filtering algorithms mainly because they rely on the interactions of the item to make recommendations. In general, it is much harder to ask new user about their personal information (users don’t want to answer too many questions). But it is easier to ask a lot of information about a new item (people who add it are interested in filling in this information to make their products recommended to the customers). The proposed system delivers the recommendation of new items to existing users with high consistency and precision. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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