The 1st International Workshop on Context-Aware Recommendation Systems with Big Data Analytics (CARS-BDA)
Paper
Paper/Presentation Title | The 1st International Workshop on Context-Aware Recommendation Systems with Big Data Analytics (CARS-BDA) |
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Presentation Type | Paper |
Authors | Zhou, Xiangmin (Author), Zhang, Ji (Author) and Zhang, Yanchun (Author) |
Journal or Proceedings Title | Proceedings of the 12th ACM International Conference on Web Search and Data Mining (WSDM 2019) |
ERA Conference ID | 42297 |
Number of Pages | 2 |
Year | 2019 |
Place of Publication | New York, United States |
ISBN | 9781450359405 |
Digital Object Identifier (DOI) | https://doi.org/10.1145/3289600.3291372 |
Conference/Event | 12th ACM International Conference on Web Search and Data Mining (WSDM 2019) |
ACM International Conference on Web Search and Data Mining | |
Event Details | ACM International Conference on Web Search and Data Mining WSDM Rank B B B B B B |
Event Details | 12th ACM International Conference on Web Search and Data Mining (WSDM 2019) Event Date 11 to end of 15 Feb 2019 Event Location Melbourne, Australia |
Abstract | Motivation and Goals. With the explosive growth of online service platforms, increasing number of people and enterprises are doing everything online. In order for organizations, governments, and individuals to understand their users, and promote their products or services, it is necessary for them to analyse big data and recommend the media or online services in real time. Effective recommendation of items of interest to consumers has become critical for enterprises in domains such as retail, e-commerce, and online media. Driven by the business successes, academic research in this field has also been active for many years. Though many scientific breakthroughs have been achieved, there are still tremendous challenges in developing effective and scalable recommendation systems for real-world industrial applications. Existing solutions focus on recommending items based on pre-set contexts, such as time, location, weather etc. The big data sizes and complex contextual information add further challenges to the deployment of advanced recommender systems. This workshop aims to bring together researchers with wide-ranging backgrounds to identify important research questions, to exchange ideas from different research disciplines, and, more generally, to facilitate discussion and innovation in the area of context-aware recommender systems and big data analytics. In a broad sense, the objective of such a workshop is to present results of the research undertaken in the area of data driven context-aware recommender systems, as a fishow and tellfi occasion. To some extent, the workshop is an exercise in showcasing research activities and findings, rather than in and not of fiworkshoppingfi or holding group discussions on research. This orientation, and the large number of presentations which are being made, means that tight timelines have to be followed. An intensive series of presentations is made, the downside of which is that the time available for group discussion is limited. |
Keywords | data mining |
ANZSRC Field of Research 2020 | 460510. Recommender systems |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | Royal Melbourne Institute of Technology (RMIT) |
School of Agricultural, Computational and Environmental Sciences | |
Victoria University | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q52wy/the-1st-international-workshop-on-context-aware-recommendation-systems-with-big-data-analytics-cars-bda
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