Altıngövde, İsmail ŞengörÖzcan, RıfatÖcalan Hüseyin C.Can, FazlıUlusoy, Özgür2016-02-082016-02-082007http://hdl.handle.net/11693/27076Date of Conference: July 23 - 27, 2007We present cluster-based retrieval (CBR) experiments on the largest available Turkish document collection. Our experiments evaluate retrieval effectiveness and efficiency on both an automatically generated clustering structure and a manual classification of documents. In particular, we compare CBR effectiveness with full-text search (FS) and evaluate several implementation alternatives for CBR. Our findings reveal that CBR yields comparable effectiveness figures with FS. Furthermore, by using a specifically tailored cluster-skipping inverted index we significantly improve in-memory query processing efficiency of CBR in comparison to other traditional CBR techniques and even FS.EnglishCluster-based retrievalCluster-skippingInverted indexTurkishClassification (of information)Cluster analysisData processingQuery languagesSearch enginesCluster based retrievalFull-text search (FS)Inverted indexInformation retrievalConference Paper10.1145/1277741.1277961