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89
An I-vector Based Approach to Compact Multi-Granularity Topic Spaces Representation of Textual Documents
"... Various studies highlighted that topic-based approaches give a powerful spo-ken content representation of documents. Nonetheless, these documents may con-tain more than one main theme, and their automatic transcription inevitably contains errors. In this study, we propose an orig-inal and promising ..."
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framework based on a compact representation of a textual docu-ment, to solve issues related to topic space granularity. Firstly, various topic spaces are estimated with different numbers of classes from a Latent Dirichlet Allocation. Then, this multiple topic space representa-tion is compacted
Document Clustering based on Topic Maps
"... Importance of document clustering is now widely acknowledged by researchers for better management, smart navigation, efficient filtering, and concise summarization of large collection of documents like World Wide Web (WWW). The next challenge lies in semantically performing clustering based on the s ..."
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for document clustering based on the Topic Map representation of the documents. The document is being transformed into a compact form. A similarity measure is proposed based upon the inferred information through topic maps data and structures. The suggested method is implemented using agglomerative hierarchal
An aspect based document representation for event clustering
- In Proceedings of CLIN 19
"... We have studied several techniques for creating and comparing content representations of textual documents in the field of event detection. We define a document as a collection of aspects, i.e. disjoint components that reveal (latent) topics and/or extracted information such as named entities. As un ..."
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We have studied several techniques for creating and comparing content representations of textual documents in the field of event detection. We define a document as a collection of aspects, i.e. disjoint components that reveal (latent) topics and/or extracted information such as named entities
Document Clustering via Matrix Representation
"... Abstract—The Vector Space Model (VSM) is widely used to represent documents and web pages. It is simple and easy to deal computationally, but it also oversimplifies a document into a vector, susceptible to noise, and cannot explicitly represent underlying topics of a document. A matrix representatio ..."
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. The latent topic extraction based on the matrix representation of documents is formulated as a constraint optimization problem in which each matrix (i.e., a document) Ai is factorized into a common base determined by non-negative matrices L and R ⊤ , and a non-negative weight matrix Mi such that the sum
Representation Models for Text Classification: a comparative analysis over three Web document types
"... Text classification constitutes a popular task in Web research with various applications that range from spam filtering to sentiment analysis. To address it, patterns of cooccurring words or characters are typically extracted from the textual content of Web documents. However, not all documents are ..."
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Cited by 2 (0 self)
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on inherent document characteristics. We claim and support that each category calls for different classification settings with respect to the representation model. We verify this claim experimentally, by showing that topic classification on these different document types offers very different results per type
DOI: 10.1140/epjst/e2012-01529-y THE EUROPEAN PHYSICAL JOURNAL SPECIAL TOPICS Review Active Brownian Particles From Individual to Collective Stochastic Dynamics
, 2012
"... Abstract. We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of sta ..."
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of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically pow-ered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles
M. Massih-Reza AMINI Directeur de thèse
"... Document clustering is one of the fundamental techniques of unsupervised learning from unstructured textual data which constitutes a real saving in terms of efficiency for various information retrieval (IR) tasks. The clustering results are not only used as basic information for the structure of a c ..."
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or as clustering techniques. Especially, topic models have been rapidly developed and became popular tools among these models. In this thesis, we are interested in to develop effective clustering techniques which allow to find meaningful reduced spaces on which document clustering may be performed more efficiently
APractical Lattice-based Digital Signature Schemes
"... Digital signatures are an important primitive for building secure systems and are used in most real world security protocols. However, almost all popular signature schemes are either based on the factoring as-sumption (RSA) or the hardness of the discrete logarithm problem (DSA/ECDSA). In the case o ..."
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of classical cryptanalytic advances or progress on the development of quantum computers the hardness of these closely related problems might be seriously weakened. A potential alternative approach is the construction of sig-nature schemes based on the hardness of certain lattices problems which are assumed
unknown title
"... ACKNOWLEDGMENTS I would like to give many thanks to Dr. Shengli Fu and Dr. Yan Huang as my advi- ..."
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ACKNOWLEDGMENTS I would like to give many thanks to Dr. Shengli Fu and Dr. Yan Huang as my advi-
Results 1 - 10
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