Recommender System Based on Expert and Item Category
| Autor: | Thanaphon Phukseng, Sunantha Sodsee |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
020203 distributed computing
Information retrieval lcsh:TA1-2040 Computer science 0202 electrical engineering electronic engineering information engineering General Engineering 020201 artificial intelligence & image processing 02 engineering and technology Recommender system lcsh:Engineering (General). Civil engineering (General) |
| Zdroj: | Engineering Journal, Vol 22, Iss 2 (2018) |
| ISSN: | 0125-8281 |
| DOI: | 10.4186/ej.2018.22.2.157 |
| Popis: | The objective of this study was to introduce the recommender system based on expert and item category to match the right items to users. In this study, the expert identification was divided into 3 techniques which were 1) the experts from social network technique, 2) the experts from the frequency of rating technique, and 3) the experts from other user’s preferences. To filter the expert users by using the frequency of rating technique and the experts from other user’s preferences technique, data about item category is used. For evaluation in this study, the researcher used Epinion for the performance testing to find out errors and accuracies in the prediction process. The results of this study showed that all the presented techniques had mean absolute error score at 0.15 and 85 percentages of accuracy, especially the expert identification combining with item category, it can reduce 60 percentages of the duration of recommendation creating. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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