Papers by Markus Dietsche

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Challenge:	Existing semantic text encoding models are limited in coverage and few attempts to empirically compare them on IR tasks have been made.
Approach:	They propose to implement word embedding aggregators and pretrained semantic encoders and to allow for their comparative evaluation on arbitrary IR collections.
Outcome:	The proposed model can be exploited via an easy-to-use web interface and its modular backend (micro-service architecture) can easily be extended with additional semantic search models.