@inproceedings{rao2005,
abstract = { The vector space model (VSM) of information
retrieval suf- fers in two areas, it does not
utilise term positions and it treats every term as
being independent. We examine two information
retrieval meth- ods based on the simple vector space
model. The first uses the query term position flow
within the documents to calculate the document
score, the second includes related terms in the
query by making use of term corre- lations. Both of
these methods show significant improvements over the
VSM precision while keeping the query time to speeds
similar to those of the VSM. },
author = {Kotagiri Ramamohanarao and Laurence A.~F.~Park},
booktitle = {The Proceedings of the Seventh Asia Pacific Web Conference},
date-modified = {2008-06-30 15:34:53 +1000},
doi = {10.1007/b106936},
keywords = {latent semantic analysis; laurence},
month = {March},
pages = {15-26},
title = {Broadening Vector Space Schemes for Improving the Quality of Information Retrieval},
url = {http://www.csse.unimelb.edu.au/~lapark/extensionsToVectorSpace.pdf},
year = {2005},
bdsk-url-1 = {http://dx.doi.org/10.1007/b106936},
bdsk-url-2 = {http://www.csse.unimelb.edu.au/~lapark/extensionsToVectorSpace.pdf}
}
@article{park2003,
abstract = {Current information retrieval methods either
ignore the term positions or deal with exact term
positions; the former can be seen as coarse document
resolution, the latter as fine document reso-
lution. We propose a new spectral-based information
retrieval method that is able to utilize many
different levels of document resolution by examining
the term patterns that occur in the documents. To
do this, we take advantage of the multiresolution
analysis properties of the wavelet transform. We
show that we are able to achieve higher precision
when compared to vector space and proximity
retrieval methods, while producing fast query times
and using a compact index. },
author = {Laurence A.~F.~Park and Marimuthu Palaniswami and Kotagiri Ramamohanarao},
date-modified = {2007-10-19 12:19:33 +1000},
doi = {10.1109/TPAMI.2005.2},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
keywords = {information retrieval; laurence},
month = {January},
number = {1},
pages = {130-135},
title = {A novel document ranking method using the Discrete Cosine Transform},
url = {http://www.csse.unimelb.edu.au/~lapark/cds2002_compact.pdf},
volume = {27},
year = {2005},
contribution = {60\%},
era2010rank = {A*},
sniprank = {15.12},
citations = {11},
bdsk-url-1 = {http://dx.doi.org/10.1109/TPAMI.2005.2},
bdsk-url-2 = {http://www.csse.unimelb.edu.au/~lapark/cds2002_compact.pdf}
}
@article{park2003.2,
abstract = {Current information retrieval methods either
ignore the term positions or deal with exact term
positions; the former can be seen as coarse document
resolution, the latter as fine document reso-
lution. We propose a new spectral-based information
retrieval method that is able to utilize many
different levels of document resolution by examining
the term patterns that occur in the documents. To
do this, we take advantage of the multiresolution
analysis properties of the wavelet transform. We
show that we are able to achieve higher precision
when compared to vector space and proximity
retrieval methods, while producing fast query times
and using a compact index. },
address = {New York, NY, USA},
author = {Laurence A. F. Park and Kotagiri Ramamohanarao and Marimuthu Palaniswami},
date-modified = {2007-10-19 12:19:33 +1000},
doi = {10.1145/1080343.1080345},
issn = {1046-8188},
journal = {ACM Transactions on Information Systems},
keywords = {wavelet transform; laurence},
number = {3},
pages = {267--298},
publisher = {ACM Press},
title = {A novel document retrieval method using the discrete wavelet transform},
url = {http://www.cs.mu.oz.au/~lapark/TOIS2005_park.pdf},
volume = {23},
year = {2005},
contribution = {75\%},
era2010rank = {A},
sniprank = {5.53},
citations = {26},
bdsk-url-1 = {http://www.cs.mu.oz.au/~lapark/TOIS2005_park.pdf},
bdsk-url-2 = {http://dx.doi.org/10.1145/1080343.1080345}
}
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