Significant term extraction by Higher Order SVD

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dc.contributor.authorManna, Sukanya
dc.contributor.authorPetres, Zoltan
dc.contributor.authorGedeon, Tamas (Tom)
dc.coverage.spatialHerlany Slovakia
dc.date.accessioned2015-12-10T22:21:34Z
dc.date.createdJanuary 30-31 2009
dc.date.issued2009
dc.date.updated2016-02-24T10:17:27Z
dc.description.abstractIn this paper, we present a novel method for term importance, called Tensor Term Indexing (TTI). This extracts significant terms from a document as well as a coherent collection of document set. The basic idea of this approach is to represent the whole document collection in a Term-Sentence-Document tensor and employs higher-order singular value decomposition (HOSVD) for important term extraction. TTI uses the lower rank approximation technique to reduce noise by eliminating anecdotal terms, to mitigate synonymy by merging the dimensions associated with terms that have similar meanings, and to mitigates polysemy, since components of polysemous words that point in the "right" direction are added to the components of words that share a similar meaning. Our evaluation shows that that TTI model can extract significant terms relevant to a topic from a small number of documents which Term Frequency and Inverse Document Frequency (tfidf) cannot.
dc.identifier.isbn9781424438013
dc.identifier.urihttp://hdl.handle.net/1885/52271
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesInternational Symposium on Applied Machine Intelligence and Informatics (SAMI 2009)
dc.sourceProceedings of the 7th International Symposium on Applied Machine Intelligence and Informatics Proceedings
dc.subjectKeywords: Approximation techniques; Basic idea; Collection of documents; Document collection; Higher order singular value decomposition; Higher order SVD; Inverse Document Frequency; Novel methods; Polysemous word; Term extraction; Term Frequency; Term importance;
dc.titleSignificant term extraction by Higher Order SVD
dc.typeConference paper
local.bibliographicCitation.lastpage68
local.bibliographicCitation.startpage63
local.contributor.affiliationManna, Sukanya, College of Engineering and Computer Science, ANU
local.contributor.affiliationPetres, Zoltan, College of Engineering and Computer Science, ANU
local.contributor.affiliationGedeon, Tamas (Tom), College of Engineering and Computer Science, ANU
local.contributor.authoremailu4088783@anu.edu.au
local.contributor.authoruidManna, Sukanya, u4321410
local.contributor.authoruidPetres, Zoltan, a276450
local.contributor.authoruidGedeon, Tamas (Tom), u4088783
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080704 - Information Retrieval and Web Search
local.identifier.ariespublicationu3594520xPUB243
local.identifier.doi10.1109/SAMI.2009.4956610
local.identifier.scopusID2-s2.0-69849094114
local.identifier.uidSubmittedByu3594520
local.type.statusPublished Version

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