Large-scale cluster-based retrieval experiments on Turkish texts

Simple item page
dc.citation.epage892en_US
dc.citation.spage891en_US
dc.contributor.authorAltıngövde, İsmail Şengören_US
dc.contributor.authorÖzcan, Rıfaten_US
dc.contributor.authorÖcalan Hüseyin C.en_US
dc.contributor.authorCan, Fazlıen_US
dc.contributor.authorUlusoy, Özgüren_US
dc.coverage.spatialAmsterdam, The Netherlandsen_US
dc.date.accessioned2016-02-08T11:43:40Z
dc.date.available2016-02-08T11:43:40Z
dc.date.issued2007en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: July 23 - 27, 2007en_US
dc.description.abstractWe 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.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T11:43:40Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2007en
dc.identifier.doi10.1145/1277741.1277961en_US
dc.identifier.urihttp://hdl.handle.net/11693/27076
dc.language.isoEnglishen_US
dc.publisherACMen_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/1277741.1277961en_US
dc.source.titleSIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrievalen_US
dc.subjectCluster-based retrievalen_US
dc.subjectCluster-skippingen_US
dc.subjectInverted indexen_US
dc.subjectTurkishen_US
dc.subjectClassification (of information)en_US
dc.subjectCluster analysisen_US
dc.subjectData processingen_US
dc.subjectQuery languagesen_US
dc.subjectSearch enginesen_US
dc.subjectCluster based retrievalen_US
dc.subjectFull-text search (FS)en_US
dc.subjectInverted indexen_US
dc.subjectInformation retrievalen_US
dc.titleLarge-scale cluster-based retrieval experiments on Turkish textsen_US
dc.typeConference Paperen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Large-scale cluster-based retrieval experiments on Turkish texts.pdf
Size:
206.13 KB
Format:
Adobe Portable Document Format
Description:
Full printable version
Download

Collections

Department of Computer Engineering