Using text mining algorithms in identifying emerging trends for recommender systems
Bibliographic Data
| ID | 21377429 |
|---|---|
| Authors | Iman Raeesi Vanani (0000-0001-8324-9896, Allameh Tabataba'i University), Laya Mahmoudi (0009-0000-1863-2872, Allameh Tabataba'i University), Seyed Mohammad Jafar Jalali (0000-0002-2169-4350, Deakin University), Kim-Hung Pho (0000-0001-9743-1306, Ton Duc Thang University, corresponding author) |
| Year | 2022 |
| Volume | 56 |
| Issue | 3 |
| Pages | 1293-1326 |
| Publication date | 2022-06-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Quality & Quantity (JOURNAL) |
| Journal identifiers | ISSN: 0033-5177 • E-ISSN: 1573-7845 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11135-021-01177-9 |
| OpenAlex | W3166194924 |
| Language | EN |
| Citations received | 1 |
| References cited | 63 |
Cold start (automotive) · Data science · Domain (mathematical analysis) · Field (mathematics) · Identification (biology) · Information retrieval · Process (computing) · Reading (process) · Recommender system · World Wide Web · Advanced Text Analysis Techniques · Computer Science · Recommender Systems and Techniques · Sentiment Analysis and Opinion Mining
| Citations per year | 1 |
|---|---|
| Citation span | 2025 - 2025 (1) |
| Highly cited | No |