Abstract
Due to the openness of crowdsourced testing, mobile app crowdsourced testing has been subject to duplicate reports. The previous research methods extract the textual features of the crowdsourced test reports, combine with shallow image analysis, and perform unsupervised clustering on the crowdsourced test reports to clarify the duplication of crowdsourced test reports and solve the problem. However, these methods ignore the semantic connection between textual descriptions and screenshots, making the clustering results unsatisfactory and the deduplication effect less accurate.
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