Latent semantic indexing is an optimal special case of multidimensional scaling
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Automating the assignment of submitted manuscripts to reviewers
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Personalized information delivery: an analysis of information filtering methods
Communications of the ACM - Special issue on information filtering
Latent semantic indexing: a probabilistic analysis
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
A semidiscrete matrix decomposition for latent semantic indexing information retrieval
ACM Transactions on Information Systems (TOIS)
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A similarity-based probability model for latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Restructuring sparse high dimensional data for effective retrieval
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Latent semantic space: iterative scaling improves precision of inter-document similarity measurement
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Random projection in dimensionality reduction: applications to image and text data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Document clustering based on non-negative matrix factorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Pattern Classification (2nd Edition)
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Learning an image manifold for retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Locality preserving clustering for image database
Proceedings of the 12th annual ACM international conference on Multimedia
Orthogonal locality preserving indexing
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Multi-label informed latent semantic indexing
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Document Clustering Using Locality Preserving Indexing
IEEE Transactions on Knowledge and Data Engineering
Statistical and computational analysis of locality preserving projection
ICML '05 Proceedings of the 22nd international conference on Machine learning
Dimensionality reduction in patch-signature based protein structure matching
ADC '06 Proceedings of the 17th Australasian Database Conference - Volume 49
An adaptive graph model for automatic image annotation
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Exploiting parallelism to support scalable hierarchical clustering
Journal of the American Society for Information Science and Technology
Locality discriminating indexing for document classification
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Dimensionality reduction for dimension-specific search
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Regularized locality preserving indexing via spectral regression
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
An empirical study of required dimensionality for large-scale latent semantic indexing applications
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Modeling hidden topics on document manifold
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MM '08 Proceedings of the 16th ACM international conference on Multimedia
Graph-based generalized latent semantic analysis for document representation
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
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2D-LPI: Two-Dimensional Locality Preserving Indexing
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Symbolic representation of text documents
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FLPI: an optimal algorithm for document indexing
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Self-taught hashing for fast similarity search
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LPP solution schemes for use with face recognition
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GEMS '10 Proceedings of the 2010 Workshop on GEometrical Models of Natural Language Semantics
Learning a user-thread alignment manifold for thread recommendation in online forum
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Shape pattern matching: A tool to cluster unstructured text documents
Journal of Computational Methods in Sciences and Engineering - Special Supplement Issue in Section A and B: Selected Papers from the ISCA International Conference on Software Engineering and Data Engineering, 2009
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Journal of Artificial Intelligence Research
A symbolic approach for text classification based on dissimilarity measure
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Transfer latent variable model based on divergence analysis
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A new proposal for locality preserving projection
PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence
The optimum clustering framework: implementing the cluster hypothesis
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Text classification using symbolic similarity measure
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Document representation and indexing is a key problem for document analysis and processing, such as clustering, classification and retrieval. Conventionally, Latent Semantic Indexing (LSI) is considered effective in deriving such an indexing. LSI essentially detects the most representative features for document representation rather than the most discriminative features. Therefore, LSI might not be optimal in discriminating documents with different semantics. In this paper, a novel algorithm called Locality Preserving Indexing (LPI) is proposed for document indexing. Each document is represented by a vector with low dimensionality. In contrast to LSI which discovers the global structure of the document space, LPI discovers the local structure and obtains a compact document representation subspace that best detects the essential semantic structure. We compare the proposed LPI approach with LSI on two standard databases. Experimental results show that LPI provides better representation in the sense of semantic structure.