Adapting pivoted document-length normalization for query size: Experiments in Chinese and English

Tze Leung Chung, Wing Pong Robert Luk, Kam Fai Wong, Kui Lam Kwok, Dik Lun Lee

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)


The vector space model (VSM) is one of the most widely used information retrieval (IR) models in both academia and industry. It was less effective at the Chinese ad hoc retrieval tasks than other retrieval models in the NTCIR-3 evaluation workshop, but comparable to those in the NTCIR-4 and NTCIR-5 workshops. We do not know whether the lower level performance was due to the VSM's inherent deficiencies or to a less effective normalization of document length. Hence we evaluated the VSM with various pivoted normalizations of document length using the NTCIR-3 collection for confirmation. We found that VSM's retrieval effectiveness with pivoted normalization was comparable to other competitive retrieval models (for example, 2-Poisson), and that VSM's retrieval speed with pivoted normalization was similar to competitive retrieval models (2-Poisson). We proposed a novel adaptive scheme that automatically estimates the (near) best parameters for pivoted document-length normalization based on query size; the new normalization is called adaptive pivoted document-length normalization. This scheme achieved good retrieval effectiveness, sometimes for short (title) queries and sometimes for long queries, without manually adjusting parameter values. We found that unique, adaptive pivoted normalization can enhance fixed pivoted normalizations for different test collections (TREC-5 and TREC-6). We also evaluated the VSM with the adaptive pivoted normalization using the pseudo-relevance feedback (PRF) and found that this type of VSM performs similarly to the competitive retrieval models (2-Poisson) with PRF. Hence, we conclude that the VSM with unique (adaptive) pivoted document-length normalization is effective for Chinese IR and that its retrieval effectiveness is comparable to that of other competitive retrieval models with or without PRF for the reference test collections used in this evaluation.
Original languageEnglish
Pages (from-to)245-263
Number of pages19
JournalACM Transactions on Asian Language Information Processing
Issue number3
Publication statusPublished - 1 Sept 2006


  • Chinese information retrieval
  • Indexing strategies
  • Pivoted normalization

ASJC Scopus subject areas

  • General Computer Science


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