The LWDA 2016 conference was hosted by Hasso-Plattner-Institute (HPI) at the University of Potsdam, September 12-14, 2016. The acronym LWDA expands to “Lernen, Wissen, Daten, Analysen” (“Learning, Knowledge, Data, Analytics”). Recent research in the field was presented and discussed from the viewpoint of machine learning, data mining, knowledge extraction, knowledge management, information retrieval, personalization, database management, information systems, big data management and big data analytics to name a few.
RGCL PhD student Mireille presented ‘Using key phrases as new queries in building relevance judgments automatically’. An abstract can be found below:
Abstract: We describe a new technique for building a relevance judgment list (qrels) for TREC test collections with no human intervention. For each TREC topic, a set of new queries is automatically generated from key phrases extracted from the top k documents retrieved from 12 different Terrier weighting models when the initial TREC topic is submitted. We assign a score to each key phrase based on its similarity to the original TREC topic. The key phrases with the highest scores become the new queries for a second search, this time using the Terrier BM25 weighting model. The union of the documents retrieved forms the automatically-build set of qrels.