... Attribute/Domain
Row Tuple
Values in a column Domain
Table Definition Schema of a Relation
Populated Table Extension
The RelationalDataModel and
Relational Database Constraints
... We noted during our visits a general shift in the financial services industry – including in
small firms – from holding customer datain paper files to the electronic scanning and
filing of correspondence. ... repeat
training or testing. In addition, training for front-line staff, such as those who work in
call centres, tended to focus mainly on legislative and regulatory requirements. This
Data Security in ... transparent international market for stolen customer data,
including data belonging to UK citizens, according to PricewaterhouseCoopers, a
consulting firm. Sets of data are bought and sold freely in social...
... XMark. Instead of storing the
entire data as a single, large XML instance, it is more
natural in a relational database to store the datain tables
representing the different entities in the data ... publishing relationaldata
in XML. ACM TODS, vol. 27, no. 4, December, 2002.
[6] D. Florescu and D. Kossmann. Storing and Querying XML
Data Using an RDBMS. IEEE Data Engineering Bulletin,
22(3):27-34, ...
a JOIN in case of wildcard and //-axis queries.
6. Conclusions
This paper introduces techniques for indexing XML
instances stored in a relational database in an
undecomposed form. It introduces...
... Probab
2004;41A:177–187.
Tankov P. Pricing and hedging in exponential L
´
evy models: review of recent results. To
appear inthe Paris-PrincetonLecture Notes in MathematicalFinance, Springer-Verlag,
Berlin, Heidelberg, ... during the after-event window. To determine the optimal window size
and optimal α level, we use the following trading strategy.
DEFINITION 2.2
A position is opened at a point determined according ... and
analytical work on data sampled with high frequency in the financial industry.
In today’s world, many fields are confronted with increasingly large amounts
of data. Financial data sampled with high...
... two types of vi-
sual input, peripheral input giving word boundary
information and foveal input giving information
about letter identity.
4.2.1 Peripheral visual input
In our model, any eccentricity ... been
explained by computational models as re-
sulting from the rational use of probabilis-
tic linguistic information. Many times,
these hypotheses have been tested in read-
ing by linking predictions ... among models of eye
movement control in reading (except Mr. Chips)
in having a fully explicit model of how visual in-
put is used to discriminate word identity. This ap-
proach stands in sharp...
... novel-specific models,
splitting each novel into 50% training data and
50% testing data. We required novels to contain
more than 200 labeled sentences. This ruled out
most short stories, leaving us with ... pro-
noun use in four European languages: Intralingual
and interlingual dimensions. In Proceedings of the
Annual Meeting of the Australian Linguistic Society,
Brisbane, Australia.
Ralf Steinberger, ... for Computational Linguistics
Towards a model of formal and informal address in English
Manaal Faruqui
Computer Science and Engineering
Indian Institute of Technology
Kharagpur, India
manaalfar@gmail.com
Sebastian...
... acyclic
join queries. We also show how to incorporate our algo-
rithm into NPRR to speed up acyclic join processing for
certain class of instances, while retaining its worst-case
guarantee. We show in ... adaptive intersection
set. Specifically, as in DLM, the element is eliminated in low-to-high ordering fashion. At any point of time, the
set of smallest uneliminated elements in all sets is maintained. ... replace the three intervals
by [
1
, r
2
], which is now considered live.
ã All original intervals in the ConstraintTree T are live.
ã One can convert any live interval into a cashed -in interval. (We...
... Stephanie Seneff. 2000. Integrating recognition
confidence scoring with language understanding and
dialogue modeling. In Proc. ICSLP.
Robert Kass and Tim Finin. 1988. Modeling the user in
natural language ... ob-
tained in every utterance. Moreover, in order
to smooth unbalanced distribution of the train-
ing data, a cost corresponding to the reciprocal
ratio of the number of samples in each class is
introduced. ... experienced.
We introduce user models not for defining users’ be-
haviors beforehand, but for detecting users’ patterns
in real-time interaction.
We define three dimensions in the user models:
‘skill...
... for undergoing the training (to
offset loss in daily wages). Each training program
included pre- and post-test questionnaires to evaluate the
change in level of knowledge after the training. Only ... HIV/AIDS. Lancet
Infect Dis 2004, 4:714.
6. Singh YN, Malaviya AN: Long distance truck drivers in India:
HIV infection and their possible role in disseminating HIV
into rural areas. Int J STD AIDS ... education models in many other rural areas that are
in urgent need of similar activities to avert an increase in
HIV prevalence.
Competing interests
The authors declare that they have no competing interests.
Authors'...
... ignoring the reminder-
response at baseline (scenario one) indicated data were
MAR, but including the reminder-response data (scenario
two) suggested MCAR. Data were MAR at three months in
both ... baseline and then annually [8].
Each dataset contained a proportion of patients with com-
plete data or a monotone, intermittent or mixed missing
data pattern.
Mechanisms of missing data
The missing ... surrounding miss-
ing datain QoL are the same irrespective of the QoL meas-
ure being used. If the data are missing because reduced
QoL leads to informative censoring, then this should be
taken into...
... them in actually better segmenting,
targeting, acquiring, retaining and maintaining a profitable customer base. Business
Intelligence and data mining techniques can also help them in identifying ...
recovery
Model
Correlations
Model
instrument
Pricing
Interest
Rate
Scenario
Customer, Instrument, portfolio risk to market and credit risk
Models through data mining
9
Data mining techniques ... own database and data mining techniques, fitting
models to the business needs and the business current credit portfolio.
4
The broad categories of application of Data Mining and Business...
... regression model
including three-linear lines in 6π interval is explained in
detail . The proposed LS criterion using the multiple lin-
ear regression model is given as
ˆτ
E,d
= arg min
τ
1
m=−1
l
|(ω
l
τ ... the
past data set. In addition, a process is included such
that all of the RLS vectors are initialized when long
silence interval is included in the observation data.
Experimental results described in ... focusing
on j [31]. It is increasingly flattened for higher level
noise because the f irst term in Equation 6 becomes a
principle factor, i.e. reducing the del ay information con-
tained in the...
... linear models for longitudinal data with only
-mixing and r-mixing. In fact, our results with other mixing-dependent structures,
such as a-mixing, *-mixing and r*-mixing, can also be obtained ... Heckman, N: Spline smoothing in a partly linear models. J R Stat Soc B. 48, 244–248 (1986)
5. Speckman, P: Kernel smoothing in partial linear models. J R Stat Soc B. 50, 413–436 (1988)
6. Robinson, PM: ... generalized linear models with longitudinal data. J Multivar
Anal. 140, 3445–3456 (2010)
25. Hu, Z, Wang, N, Carroll, RJ: Profile-kernel versus backfitting in the partially linear models for longitudinal/clustered...