Entity extraction for people profile matching
Abstract: With the rise in social media platform usage, the average number of people profileshas increased as well. The fact that people have social media profiles on multipleplatforms reveals the interesting problem of matching them in order to aggregate allthe profiles in one. As a significant part of these profiles are made of unstructuredtext, extracting labeled data using an entity extraction system can lead to an increasein precision and recall.This thesis documents the effects a bootstrapped pattern learning approach canhave on a profile matching system. The entity extraction system is trained in adistributed manner on a big amount of data, in order to generate as many qualitypatterns as possible.
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