Crowdsourced Data Stream Mining for Tourism Recommendation

نویسندگان

چکیده

Crowdsourced data streams are continuous flows of generated at high rate by users, also known as the crowd. These popular and extremely valuable in several domains. This is case tourism, where crowdsourcing platforms rely on tourist business inputs to provide tailored recommendations future tourists real time. The continuous, open non-curated nature crowd-originated requires robust stream mining techniques for on-line profiling, recommendation evaluation. sought need, not only, continuously improve profiles learn models, but be transparent, overcome biases, prioritise preferences, master huge volumes; all article surveys state-of-art this field, identifies research opportunities.

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ژورنال

عنوان ژورنال: Advances in intelligent systems and computing

سال: 2021

ISSN: ['2194-5357', '2194-5365']

DOI: https://doi.org/10.1007/978-3-030-72657-7_25