This work revisits the information given by the graph-of-words and its typical utilization through graph-based ranking approaches in the context of keyword extraction. Recent, well-known graph-based approaches typically employ the knowledge from word
vector representations during the ranking process via popular centrality measures (e.g., PageRank) without giving the primary role to vectors' distribution. We consider the adjacency matrix that corresponds to the graph-of-words of a target text document as the vector representation of its vocabulary. We propose the distribution-based modeling of this adjacency matrix using unsupervised (learning) algorithms. The efficacy of the distribution-based modeling approaches compared to state-of-the-art graph-based methods is confirmed by an extensive experimental study according to the F1 score. Our code is available on GitHub.
This paper presents a new type of encryption, using a matrix
asymmetric and symmetric matrix inverse matrix clear text, which
is an internal encryption.
As well as asymmetric encryption, where the ciphertext is inversely
symmetric matrix.
Decryp
tion matrix related to any asymmetric encryption keys
depends on public and private, and is applied to the coded messages
used in the current system ASCII our computers.
There are many known methods for finding each of:
Determinate for square matrix, Inverse for irregular
square matrix, and Rank for any matrix. but these
methods become difficult to high- order matrices . and
even software gives results are rounde
d due to
recycling numbers several times. The main idea in this
work is finding Determinate, Rank, and Inverse matrix
by reduction the order of matrix.
In this paper, we introduce a modification to fuzzy mountain
data clustering algorithm. We were able to make this algorithm
working automatically, through finding a way to divide the
space, to determine the values of the input parameters, and
the stop condition automatically, instead of getting them by the
user.
We performed in this research forecast in the direction of the index
numbers for consumer prices for ( food- clothes and shoes –
education -health- transportation communications - housing water,
electricity, gas and other fuel oils), by using Mark
ov chains in
estimating with dependence on monthly data were taken from the
central bureau of statistics in Syria during the period (1/1/2010 ,
31/12/2011) , So results were analyzed by calculating the vector of
states probabilities in the moment 0 t and using it with matrix of
transition probabilities states transition probability for forecasting in the
vector of states probabilities on the long and short range for knowing
the direction at which the index numbers may behave in the future.
The most important results of the study were instability of the beam of
the transition probabilities (high low stability) during the prediction
period, as well as for the matrix of transition probabilities.
In this paper, we introduce a modification to fuzzy mountain
data clustering algorithm. We were able to make this algorithm
working automatically, through finding a way to divide the
space, to determine the values of the input parameters, and
the stop condition automatically, instead of getting them by the
user.
Theory Resultant are considered as one of the new mathematical
tools that motivate the researchers in all mathematical
domains.They use in solving many of mathematical problems.
The volume of data being generated nowadays is increasing at
phenomenal rate. Extracting useful knowledge from such data
collections is an important and challenging issue. A promising
technique is the rough set approach, a new mathematical method
to data analysis based on classification of objects into similarity
classes, which are indiscernible with respect to some features. This
paper focuses on discovering maximal generalized decision rules
in databases based on a simple or multiple regression, generalized
theory, and decision matrix.
This paper addresses the subject of design changes management in the context of a
multidisciplinary collaborative Building Information Models (BIM) environment. Within
Building projects organization field, This research aims to use change managemen
t as tool
for design and decision making.
The proposed method for the management of design changes depends on both
modeling the elements of structure based on BIM and using parameter-based design
structure matrix as tool for Change Management in a way that will support the effective
flow of information between disciplines, and thus reduces design changes, and will be able
to trace a series of successive changes within the BIM environment.
This paper offers different necessary models to build the DSM; then they are fed by
the information of a commercial building project collected from design engineers.
The proposed method represents the various dependencies between the parameters of
building and evaluates their impact on the levels of elements, the whole system and
subsystems in a way that allows to identify the critical parameters and predict some of the
iterative cycles of change to avoid unnecessary rework.
In this paper, we present two new methods for finding
the numerical solutions of systems of the nonlinear equations.
The basic idea depend on
founding relationship between minimum of a function and the
solution of systems of the nonlinear equatio
ns. The first method
seeks the numerical solution with a sequence of search
directions, which is depended on gradient and Hessian matrix of
function, while the second method is based on a sequence of
conjugate search directions. The study shows that our two
methods are convergent, and they can find exact solutions for
quadratic functions, so they can find high accurate solutions for
over quadratic functions. The purposed two algorithms are
programmed by Mathematica Version9. The approximate
solutions of some test problems are given. Comparisons of our
results with other methods illustrate the efficiency and highly
accurate of our suggested methods.
