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      • Department of Computer Engineering
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      Large-scale cluster-based retrieval experiments on Turkish texts

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      Author
      Altıngövde, İsmail Şengör
      Özcan, Rıfat
      Öcalan Hüseyin C.
      Can, Fazlı
      Ulusoy, Özgür
      Date
      2007
      Source Title
      SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
      Publisher
      ACM
      Pages
      891 - 892
      Language
      English
      Type
      Conference Paper
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      Abstract
      We 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.
      Keywords
      Cluster-based retrieval
      Cluster-skipping
      Inverted index
      Turkish
      Classification (of information)
      Cluster analysis
      Data processing
      Query languages
      Search engines
      Cluster based retrieval
      Full-text search (FS)
      Inverted index
      Information retrieval
      Permalink
      http://hdl.handle.net/11693/27076
      Published Version (Please cite this version)
      http://dx.doi.org/10.1145/1277741.1277961
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      • Department of Computer Engineering 1368
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