SOAR uses friendships and review sentiment for place recommendations
Original title: SOAR: Social and Opinion-Aware Recommendations
The model judges whether a location fits a user and reports higher precision when reviews are included.
Researchers propose SOAR, a recommendation model for points of interest that uses a user's friendship network and the sentiment of textual reviews. It is intended to decide whether a location suits a specific person. Experiments on real-world datasets are reported to improve recommendation precision when reviews are included.
- SOAR combines friendship links with shared-review sentiment.
- The task is personalized point-of-interest suitability.
- Real-world dataset tests are said to raise precision.
From the original article
1 min read at arxiv.orgOne of the enduring challenges in online platforms is recommendation. Both communities and advertisers face difficulties in analyzing complex user behavior, identifying habits and evolving preferences, and providing timely recommendations that are relevant to user interests.
By Giannis Christoforidis · arxiv.org
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