{"id":36,"date":"2017-12-04T13:05:33","date_gmt":"2017-12-04T11:05:33","guid":{"rendered":"https:\/\/coursepages.uta.fi\/tiets44\/?page_id=36"},"modified":"2019-02-14T14:06:37","modified_gmt":"2019-02-14T12:06:37","slug":"project-work","status":"publish","type":"page","link":"https:\/\/coursepages2.tuni.fi\/tiets44\/project-work\/","title":{"rendered":"Project Work"},"content":{"rendered":"

The project work will include the implementation of algorithms that realize steps of the entity resolution process.<\/p>\n

Please work on groups of two (2).<\/p>\n

[Part 1]<\/strong> Implement the following blocking methods: Token Blocking<\/em> and Attribute Clustering Blocking<\/em>. Please explain any assumptions you made (e.g., if you apply any stemming method on your data, which is the similarity measure that you use for computing similarities between sets of tokens (one similarity function, like Jaccard, is enough for the needs of our project), etc.). For details on the blocking methods please see at the paper:\u00a0A Blocking Framework for Entity Resolution in Highly Heterogeneous Information Spaces<\/a>.<\/p>\n

[Part 2]<\/strong> Implement the meta-blocking method using as edge weighting the Jaccard scheme<\/em> and the common blocks scheme<\/em>, and as pruning scheme the weight edge pruning<\/em> and the cardinality node pruning<\/em> methods. For details on the meta-blocking methods please see at the paper:\u00a0Meta-Blocking: Taking Entity Resolution to the Next Level<\/a>.<\/p>\n

Additional information:<\/p>\n