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Um estudo sobre o papel de medidas de similaridade em visualização de coleções de documentos; A study on the role of similarity measures in visual text analytics

Salazar, Frizzi Alejandra San Roman
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 27/09/2012 PT
Relevância na Pesquisa
46.09%
Técnicas de visualização de informação, tais como as que utilizam posicionamento de pontos baseado na similaridade do conteúdo, são utilizadas para criar representações visuais de dados que evidenciem certos padrões. Essas técnicas são sensíveis à qualidade dos dados, a qual, por sua vez, depende de uma etapa de pré-processamento muito influente. Esta etapa envolve a limpeza do texto e, em alguns casos, a detecção de termos e seus pesos, bem como a definição de uma função de (dis)similaridade. Poucos são os estudos realizados sobre como esses cálculos de (dis)similaridade afetam a qualidade das representações visuais geradas para dados textuais. Este trabalho apresenta um estudo sobre o papel das diferentes medidas de (dis)similaridade entre pares de textos na geração de mapas visuais. Nos concentramos principalmente em dois tipos de funções de distância, aquelas computadas a partir da representação vetorial do texto (Vector Space Model (VSM)) e em medidas de comparação direta de strings textuais. Comparamos o efeito na geração de mapas visuais com técnicas de posicionamento de pontos, utilizando as duas abordagens. Para isso, foram utilizadas medidas objetivas para comparar a qualidade visual dos mapas...

Three-phase tri-state integrated boost inverter with special space vector and dq0 control

De Brito, Moacyr A.G.; Junior, Luigi G.; Canesin, Carlos A.
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Conferência ou Objeto de Conferência Formato: 644-648
ENG
Relevância na Pesquisa
46.07%
This paper presents a three-phase integrated inverter suitable for stand-alone and grid-connected applications. Furthermore, the utilization of the special features of the tri-state coupled with the new space vector modulation allows the converter to present an attractive degree of freedom for the designing of the controllers. Additionally, the control is derived through dq0 transformation, all the system is described and interesting simulation results are available to confirm the proposal. © 2012 IEEE.

The development and assessment of the semantic fields model of visual salience.

Stone, Benjamin
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2010
Relevância na Pesquisa
46%
The present thesis describes the development and assessment of the Semantic Fields Model of visual salience. The Semantic Fields model provides estimates of visual salience in relation to goal-oriented Web site search tasks. The development and assessment of this model is reported over seven studies that are presented in two journal articles and two peer-reviewed conference papers. In Paper 1 (N=50), pupil dilation is validated as a measure of cognitive load for use in later studies. While it has been found previously that a participant’s pupil dilation will be larger during more complex tasks, these experiments have not generally been conducted under the environmental condition of light radiated from a computer monitor. The findings of this experiment indicate that computer monitor radiance in our experimental setting did not interfere with the ability to discriminate successfully between task-related pupil dilation. Paper 2 (N=49) introduces the Semantic Fields model for estimating the visual salience of different areas displayed on a Web page. Latent Semantic Analysis and the Touchstone Applied Science Associates (TASA) corpus were used to calculate Semantic Field values for any (x, y) coordinate point on a Web page based on the structure of that Web page. These Semantic Field values were then used to estimate eye-tracking data that was collected from participants’ goal-oriented search tasks on a total of 1842 Web pages. Semantic Field values were found to predict the participants’ eye-tracking data. In Paper 3 (N=100)...

A context vector model for information retrieval

Billhardt, Holger; Borrajo, Daniel; Maojo, Víctor
Fonte: Wiley & Sons Publicador: Wiley & Sons
Tipo: Artigo de Revista Científica Formato: application/pdf
Publicado em //2002 ENG
Relevância na Pesquisa
56.07%
In the vector space model for information retrieval, term vectors are pair-wise orthogonal, that is, terms are assumed to be independent. It is well known that this assumption is too restrictive. In this article, we present our work on an indexing and retrieval method that, based on the vector space model, incorporates term dependencies and thus obtains semantically richer representations of documents. First, we generate term context vectors based on the co-occurrence of terms in the same documents. These vectors are used to calculate context vectors for documents. We present different techniques for estimating the dependencies among terms. We also define term weights that can be employed in the model. Experimental results on four text collections (MED, CRANFIELD, CISI, and CACM) show that the incorporation of term dependencies in the retrieval process performs statistically significantly better than the classical vector space model with IDF weights. We also show that the degree of semantic matching versus direct word matching that performs best varies on the four collections. We conclude that the model performs well for certain types of queries and, generally, for information tasks with high recall requirements. Therefore, we propose the use of the context vector model in combination with other...

Large vector spaces of block-symmetric strong linearizations of matrix polynomials

Bueno, M. I.; Martínez Dopico, Froilan C.; Furtado, S.; Rychnovsky, M.
Fonte: Elsevier Publicador: Elsevier
Tipo: info:eu-repo/semantics/acceptedVersion; info:eu-repo/semantics/article
Publicado em 15/07/2015 ENG
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55.95%
Given a matrix polynomial P(lambda) = Sigma(k)(i=0) lambda(i) A(i) of degree k, where A(i) are n x n matrices with entries in a field F, the development of linearizations of P(lambda) that preserve whatever structure P(lambda) might posses has been a very active area of research in the last decade. Most of the structure-preserving linearizations of P(lambda) discovered so far are based on certain modifications of block-symmetric linearizations. The block-symmetric linearizations of P(lambda) available in the literature fall essentially into two classes: linearizations based on the so-called Fiedler pencils with repetition, which form a finite family, and a vector space of dimension k of block-symmetric pencils, called DL(P), such that most of its pencils are linearizations. One drawback of the pencils in DL(P) is that none of them is a linearization when P(lambda) is singular. In this paper we introduce new vector spaces of block,symmetric pencils, most of which are strong linearizations of P(lambda). The dimensions of these spaces are O(n(2)), which, for n >= root k, are much larger than the dimension of DL(P). When k is odd, many of these vector spaces contain linearizations also when P(lambda) is singular. The coefficients of the block-symmetric pencils in these new spaces can be easily constructed as k x k block-matrices whose n x n blocks are of the form 0...

Making clustering in delay-vector space meaningful

Chen, Jason Robert
Fonte: Springer Publicador: Springer
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
55.87%
Sequential time series clustering is a technique used to extract important features from time series data. The method can be shown to be the process of clustering in the delay-vector space formalism used in the Dynamical Systems literature. Recently, the

Some necessary conditions for vector space partitions

Heden, Olof; Lehmann, Juliane
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46%
Some new necessary conditions for the existence of vector space partitions are derived. They are applied to the problem of finding the maximum number of spaces of dimension t in a vector space partition of V(2t,q) that contains m_d spaces of dimension d, where t/2

Partial derivatives of a generic subspace of a vector space of forms: quotients of level algebras of arbitrary type

Zanello, Fabrizio
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46%
Given a vector space $V$ of homogeneous polynomials of the same degree over an infinite field, consider a generic subspace $W$ of $V$. The main result of this paper is a lower-bound (in general sharp) for the dimensions of the spaces spanned in each degree by the partial derivatives of the forms generating $W$, in terms of the dimensions of the spaces spanned by the partial derivatives of the forms generating the original space $V$. Rephrasing our result in the language of commutative algebra (where this result finds its most important applications), we have: let $A$ be a type $t$ artinian level algebra with $h$-vector $h=(1,h_1,h_2,...,h_e)$, and let, for $c=1,2,...,t-1$, $H^{c,gen}=(1,H_1^{c,gen},H_2^{c,gen},...,H_e^{c,gen})$ be the $h$-vector of the generic type $c$ level quotient of $A$ having the same socle degree $e$. Then we supply a lower-bound (in general sharp) for the $h$-vector $H^{c,gen}$. Explicitly, we will show that, for any $u\in \lbrace 1,...,e\rbrace $, $$H_u^{c,gen}\geq {1\over t^2-1}((t-c)h_{e-u}+(ct-1)h_u).$$ This result generalizes a recent theorem of Iarrobino (which treats the case $t=2$). Finally, we begin to obtain, as a consequence, some structure theorems for level $h$-vectors of type bigger than 2, which is...

Entanglement Sharing in Real-Vector-Space Quantum Theory

Wootters, William K.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46%
The limitation on the sharing of entanglement is a basic feature of quantum theory. For example, if two qubits are completely entangled with each other, neither of them can be at all entangled with any other object. In this paper we show, at least for a certain standard definition of entanglement, that this feature is lost when one replaces the usual complex vector space of quantum states with a real vector space. Moreover, the difference between the two theories is extreme: in the real-vector-space theory, there exist states of arbitrarily many binary objects, "rebits," in which every rebit in the system is maximally entangled with each of the other rebits.; Comment: 13 pages; minor corrections in v2

Vector cross product in n-dimensional vector space

Tian, Xiu-Lao; Yang, Chao; Hu, Yang; Tian, Chao
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 18/10/2013
Relevância na Pesquisa
46.08%
The definition of vector cross product (VCP) introduced by Eckmann only exists in thethree- and the seven- dimensional vector space. In this paper, according to the orthogonal completeness, magnitude of basis vector cross product and all kinds of combinations of basis vector $\hat{e}_i$, the generalized definition of VCP in the odd n-dimensional vector space is given by introducing a cross term $X_{AB}$. In addition, the definition is validated by reducing the generalization definition to the fundamental three- and seven-dimensional vector space.; Comment: 9 pages, 1 figure, comments are welcome

A survey of the different types of vector space partitions

Heden, Olof
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 05/03/2011
Relevância na Pesquisa
46.16%
A {\it vector space partition} is here a collection $\mathcal P$ of subspaces of a finite vector space $V(n,q)$, of dimension $n$ over a finite field with $q$ elements, with the property that every non zero vector is contained in a unique member of $\mathcal P$. Vector space partitions relates to finite projective planes, design theory and error correcting codes. In the first part of the talk I will discuss some relations between vector space partitions and other branches of mathematics. The other part of the talk contains a survey of known results on the type of a vector space partition, more precisely: the theorem of Beutelspacher and Heden on $\mathrm{T}$-partitions, rather recent results of El-Zanati et al. on the different types that appear in the spaces V(n,2), for $n\leq8$, a result of Heden and Lehmann on vector space partitions and maximal partial spreads including their new necessary condition for the existence of a vector space partition, and furthermore, I will give a theorem of Heden on the length of the tail of a vector space partition. Finally, I will also give a few historical remarks.; Comment: This talk was presented at Matematiska kollokviet at Department of Mathematics at Link\"oping University on May 19, 2010

Sp(2,$\mathbb{Z}$) invariant Wigner function on even dimensional vector space

Horibe, Minoru; Hashimoto, Takaaki; Hayashi, Akihisa
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 31/01/2013
Relevância na Pesquisa
46.05%
We construct the quasi probability distribution $W(p,q)$ on even dimensional vector space with marginality and invariance under the transformation induced by projective representation of the group ${\rm Sp}(2,\mathbb{Z})$ whose elements correspond to linear canonical transformation. On even dimensional vector space, non-existence of such a quasi probability distribution whose arguments take physical values was shown in our previous paper(Phys.Rev.A{\bf 65} 032105(2002)). For this reason we study a quasi probability distribution $W(p,q)$ whose arguments $q$ and $p$ take not only $N$ physical values but also $N$ unphysical values, where $N$ is dimension of vector space. It is shown that there are two quasi probability distributions on even dimensional vector space. The one is equivalent to the Wigner function proposed by Leonhardt, and the other is a new one.; Comment: 5 pages

Vector-Space Markov Random Fields via Exponential Families

Tansey, Wesley; Padilla, Oscar Hernan Madrid; Suggala, Arun Sai; Ravikumar, Pradeep
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 19/05/2015
Relevância na Pesquisa
46%
We present Vector-Space Markov Random Fields (VS-MRFs), a novel class of undirected graphical models where each variable can belong to an arbitrary vector space. VS-MRFs generalize a recent line of work on scalar-valued, uni-parameter exponential family and mixed graphical models, thereby greatly broadening the class of exponential families available (e.g., allowing multinomial and Dirichlet distributions). Specifically, VS-MRFs are the joint graphical model distributions where the node-conditional distributions belong to generic exponential families with general vector space domains. We also present a sparsistent $M$-estimator for learning our class of MRFs that recovers the correct set of edges with high probability. We validate our approach via a set of synthetic data experiments as well as a real-world case study of over four million foods from the popular diet tracking app MyFitnessPal. Our results demonstrate that our algorithm performs well empirically and that VS-MRFs are capable of capturing and highlighting interesting structure in complex, real-world data. All code for our algorithm is open source and publicly available.; Comment: See https://github.com/tansey/vsmrfs for code

The Bloch-vector space for N-level systems -- the spherical-coordinate point of view

Kimura, Gen; Kossakowski, Andrzej
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46.05%
Bloch-vector spaces for $N$-level systems are investigated from the spherical-coordinate point of view in order to understand their geometrical aspects. We show that the maximum radius in each direction, which is due to the construction of the Bloch-vector space, is determined by the minimum eigenvalue of the corresponding observable (orthogonal generator of SU(N)). From this fact, we reveal the dual property of the structure of the Bloch-vector space; if in some direction the space reachs the large sphere (pure state), then in the opposite direction the space can only get to the small sphere, and vice versa. Another application is a parameterization with simple ranges of density operators. We also provide three classes of quantum-state representation based on actual measurements beyond the Bloch vector and discuss their state-spaces.; Comment: REVTeX4, 25 pages, 3 EPS figures, Rewritten with improved explanation; references add

The Clustering of Author's Texts of English Fiction in the Vector Space of Semantic Fields

Pavlyshenko, Bohdan
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 06/12/2012
Relevância na Pesquisa
46%
The clustering of text documents in the vector space of semantic fields and in the semantic space with orthogonal basis has been analysed. It is shown that using the vector space model with the basis of semantic fields is effective in the cluster analysis algorithms of author's texts in English fiction. The analysis of the author's texts distribution in cluster structure showed the presence of the areas of semantic space that represent the author's ideolects of individual authors. SVD factorization of the semantic fields matrix makes it possible to reduce significantly the dimension of the semantic space in the cluster analysis of author's texts.; Comment: 7 pages, 5 figures

Group-theoretical vector space model

Kim, Dohan
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 20/09/2015
Relevância na Pesquisa
46.03%
This paper presents a group-theoretical vector space model (VSM) that extends the VSM with a group action on a vector space of the VSM. We use group and its representation theory to represent a dynamic transformation of information objects, in which each information object is represented by a vector in a vector space of the VSM. Several groups and their matrix representations are employed for representing different kinds of dynamic transformations of information objects used in the VSM. We provide concrete examples of how a dynamic transformation of information objects is performed and discuss algebraic properties involving certain dynamic transformations of information objects used in the VSM.; Comment: This is an Accepted Manuscript of an article published by Taylor & Francis Group in International Journal of Computer Mathematics on 16/09/2014, available online: http://dx.doi.org/10.1080/00207160.2014.958079

Metrizability of Topological Vector Space Valued Cone Metric Spaces

Cakalli, Huseyin; Sonmez, Ayse; Genc, Cigdem
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46.03%
Scalarization method is an important tool in the study of vector optimization as corresponding solutions of vector optimization problems can be found by solving scalar optimization problems. This is applied by Du (2010) [A note on cone metric fixed point theory and its equivalence, Nonlinear Analysis 72 2259-2261] to investigate the equivalence of vectorial versions of fixed point theorems of contractive mappings in generalized cone metric spaces and scalar versions of fixed point theorems in general metric spaces in usual sense. In this paper we find out that the topology induced by topological vector space valued cone metric coincides with the topology induced by the metric obtained via a nonlinear scalarization function, i.e any topological vector space valued cone metric space is metrizable.; Comment: This paper has been withdrawn by the authors. We withdraw our paper due to the acceptance in the journal "Applied Mathematics Letters" with a different title. r has been withdrawn by the authors due to a

Vector space framework for unification of one- and multidimensional filter bank theory

Chen, Tsuhan; Vaidyanathan, P. P.
Fonte: Instituto de Tecnologia da Califórnia Publicador: Instituto de Tecnologia da Califórnia
Tipo: Article; PeerReviewed Formato: application/pdf
Publicado em /08/1994
Relevância na Pesquisa
46.09%
A number of results in filter bank theory can be viewed using vector space notations. This simplifies the proofs of many important results. In this paper, we first introduce the framework of vector space, and then use this framework to derive some known and some new filter bank results as well. For example, the relation among the Hermitian image property, orthonormality, and the perfect reconstruction (PR) property is well-known for the case of one-dimensional (1-D) analysis/synthesis filter banks. We can prove the same result in a more general vector space setting. This vector space framework has the advantage that even the most general filter banks, namely, multidimensional nonuniform filter banks with rational decimation matrices, become a special case. Many results in 1-D filter bank theory are hence extended to the multidimensional case, with some algebraic manipulations of integer matrices. Some examples are: the equivalence of biorthonormality and the PR property, the interchangeability of analysis and synthesis filters, the connection between analysis/synthesis filter banks and synthesis/analysis transmultiplexers, etc. Furthermore, we obtain the subband convolution scheme by starting from the generalized Parseval's relation in vector space. Several theoretical results of wavelet transform can also be derived using this framework. In particular...

Soft Similarity and Soft Cosine Measure: Similarity of Features in Vector Space Model

Sidorov,Grigori; Gelbukh,Alexander; Gómez-Adorno,Helena; Pinto,David
Fonte: Centro de Investigación en computación, IPN Publicador: Centro de Investigación en computación, IPN
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/09/2014 EN
Relevância na Pesquisa
65.96%
We show how to consider similarity between features for calculation of similarity of objects in the Vector Space Model (VSM) for machine learning algorithms and other classes of methods that involve similarity between objects. Unlike LSA, we assume that similarity between features is known (say, from a synonym dictionary) and does not need to be learned from the data. We call the proposed similarity measure soft similarity. Similarity between features is common, for example, in natural language processing: words, n-grams, or syntactic n-grams can be somewhat different (which makes them different features) but still have much in common: for example, words "play" and "game" are different but related. When there is no similarity between features then our soft similarity measure is equal to the standard similarity. For this, we generalize the well-known cosine similarity measure in VSM by introducing what we call "soft cosine measure". We propose various formulas for exact or approximate calculation of the soft cosine measure. For example, in one of them we consider for VSM a new feature space consisting of pairs of the original features weighted by their similarity. Again, for features that bear no similarity to each other, our formulas reduce to the standard cosine measure. Our experiments show that our soft cosine measure provides better performance in our case study: entrance exams question answering task at CLEF. In these experiments...

Vector Space Basis Change in Information Retrieval

Mbarek,Rabeb; Tmar,Mohamed; Hattab,Hawete
Fonte: Centro de Investigación en computación, IPN Publicador: Centro de Investigación en computación, IPN
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/09/2014 EN
Relevância na Pesquisa
66.07%
The Vector Space Basis Change (VSBC) is an algebraic operator responsible for change of basis and it is parameterized by a transition matrix. If we change the vector space basis, then each vector component changes depending on this matrix. The strategy of VSBC has been shown to be effective in separating relevant documents and irrelevant ones. Recently, using this strategy, some feedback algorithms have been developed. To build a transition matrix some optimization methods have been used. In this paper, we propose to use a simple, convenient and direct method to build a transition matrix. Based on this method we develop a relevance feedback algorithm. Experimental results on a TREC collection show that our proposed method is effective and generally superior to known VSBC-based models. We also show that our proposed method gives a statistically significant improvement over these models.