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» Essential Dimensions of Latent Semantic Indexing (LSI)
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SIGIR
2006
ACM
14 years 1 months ago
Tensor space model for document analysis
Vector Space Model (VSM) has been at the core of information retrieval for the past decades. VSM considers the documents as vectors in high dimensional space. In such a vector spa...
Deng Cai, Xiaofei He, Jiawei Han
ICDE
2007
IEEE
211views Database» more  ICDE 2007»
14 years 1 months ago
Document Representation and Dimension Reduction for Text Clustering
Increasingly large text datasets and the high dimensionality associated with natural language create a great challenge in text mining. In this research, a systematic study is cond...
M. Mahdi Shafiei, Singer Wang, Roger Zhang, Evange...
TREC
2001
13 years 8 months ago
Challenges of Multi-Mode IR Software
Web track results are presented. A software project, IRTools, is described. IRTools is intended to enable information retrieval (IR) experimentation by incorporating methods for m...
Gregory B. Newby
SIGIR
2005
ACM
14 years 1 months ago
Orthogonal locality preserving indexing
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
Deng Cai, Xiaofei He
CIKM
2009
Springer
14 years 2 months ago
Supervised semantic indexing
We present a class of models that are discriminatively trained to directly map from the word content in a query-document or documentdocument pair to a ranking score. Like Latent Se...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...