پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 158 |
| تعداد شماره‌ها | 6,230 |
| تعداد مقالات | 67,757 |
| تعداد مشاهده مقاله | 115,111,368 |
| تعداد دریافت فایل اصل مقاله | 89,872,356 |
Opinion Fraud Detection in Streaming Comments Utilising Node Similarity in the Review Network | ||
| Journal of Algorithms and Computation | ||
| دوره 54، شماره 2، اسفند 2022، صفحه 21-35 اصل مقاله (460.81 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jac.2022.90383 | ||
| نویسندگان | ||
| Shahab Ghodsi1؛ Ali Moieni* 2 | ||
| 1School of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran | ||
| 2University of Tehran, College of Engineering, School of Engineering Science, Tehran, Iran. | ||
| چکیده | ||
| One important criterion in decision-making when we want to purchase a product or a service is users’ reviews. When something is valuable, it’s fake and will be created as well. It is the same for users’ reviews. The purpose of these fake reviews is to deceive users, leading them to make a wrong choice. One challenging problem is when we can trust a review. Although many researchers attempted to address this problem, none of them pictured the problem in a streaming domain. With the help of the review network’s properties, we propose a model to find reliable reviews when reviews are coming in a stream. Our model is fast and online, that is, it is capable of identifying reliable reviews as they are been submitted, and scalable because it is a complementary model to offline models in detecting fake reviews. | ||
| کلیدواژه‌ها | ||
| big data؛ opinion fraud؛ network science؛ review spam؛ Spark؛ fake reviews؛ streaming data | ||
|
آمار تعداد مشاهده مقاله: 240 تعداد دریافت فایل اصل مقاله: 162 |
||