Schematic Design of Hotel Recommendation Systems by user Precedence on Twitter
Recommender systems utilization has proven sales enhancement in most e-commerce platforms. This system objected to provide more options, comfort and flexibility to user which could make him interested, as well as providing better chance for companies to increase sells in their products and services....
| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
| Published: |
Allameh Tabataba'i University Press
2018-12-01
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| Series: | مطالعات مدیریت کسب و کار هوشمند |
| Subjects: | |
| Online Access: | https://ims.atu.ac.ir/article_9742_df4c1edea85e1ee6b94bd6fb4481b5c1.pdf |
| Summary: | Recommender systems utilization has proven sales enhancement in most e-commerce platforms. This system objected to provide more options, comfort and flexibility to user which could make him interested, as well as providing better chance for companies to increase sells in their products and services. Flourishing popularity of web site has originated intrigue for recommendation systems. By penetrating in infinite fields, recommendation systems give deceptive suggestion on services compatible with user precedence. Integrating recommender systems by data management techniques to can targeted such issues and quality of suggestions will be improved considerably. Recent research reveals an idea of utilizing social network data to refine weakness points of traditional recommender system and improve prediction accuracy and efficiency. In this paper we represent views of recommender systems based on Twitter social network data by usage of variety interfaces, content analysis Methods, computational linguistics techniques and MALLET topic modeling algorithm. By deep exploration of objects, methodologies and available data sources, this paper will helps interested people to develop travel recommendation systems and facilitates future research by achieved direction. |
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| ISSN: | 2821-0964 2821-0816 |