When I first started writing about credit scores more than a decade ago, few
people knew what these three-digit numbers were or how they worked.
Today most people have at least a vague understanding that credit scores
are important. But they often don’t realize how important—until they get
turned down for a loan or an apartment, or wind up paying more interest or
higher insurance premiums than they expected.
We show that question-based sentence fusion is a better deﬁned task than generic sentence fusion (Q-based fusions are shorter, display less variety in length, yield more identical results and have higher normalized Rouge scores). Moreover, we show that in a QA setting, participants strongly prefer Q-based fusions over generic ones, and have a preference for union over intersection fusions.
During the second half of the 1990s, mortgage underwriting increasingly incorporated
credit scores and other automated evaluations of credit histories. As of 1999,
approximately 60 to 70 percent of all mortgages were underwritten using an automated
evaluation of credit, and the share was rising2
The automated quantification of the information in credit reports has not simply been
used to decide whether or not to extend credit, but has also been used to set prices and
terms for mortgages and other consumer credit.
OpenStack is an open source software for building public and private clouds, born from
Rackspace and NASA. It is now a global success and is developed and supported by scores
of people around the globe and backed by some of the leading players in the cloud space
today. This book is specifically designed to quickly help you get up to speed with OpenStack
and give you the confidence and understanding to roll it out into your own datacenters.
Differences in Audit Quality Among Audit Firms: An Examination Using Bid-Ask Spreads Then, in Section 1.6, I examine the distribution of average test
scores across markets, looking for evidence that interdistrict competition leads to increases
in the average effectiveness of local administrators.
Have you ever needed to find a public golf course,
immediately? Ever wished you could hold those critical out-oftown
business meetings on the links, if only you knew where
they were? Or have you even just wanted to get away and find
a game between meetings, while on the road?
The Golf Course Locator is the book youve been waiting for.
Featuring greens from coast to coast, sorted by City &
State, proximity to both airports and the nation’s
leading companies and law firms, this book will help you zonein
on the perfect course to meet your needs.
Your TOEFL (Test of English as a Foreign Language) scores are important in de¬termining whether you are ready to study in a U.S. or Canadian college or univer¬sity. Thorough preparation leads to better scores, so you need to make the most of your available study time.
In this paper, we propose a linguistically annotated reordering model for BTG-based statistical machine translation. The model incorporates linguistic knowledge to predict orders for both syntactic and non-syntactic phrases. The linguistic knowledge is automatically learned from source-side parse trees through an annotation algorithm. We empirically demonstrate that the proposed model leads to a signiﬁcant improvement of 1.55% in the BLEU score over the baseline reordering model on the NIST MT-05 Chinese-to-English translation task. ...
Ensuring that children are healthy and able to learn is an essential part of an effective
education system. As many studies show, education and health are inseparable. A child’s
nutritional status affects cognitive performance and test scores; illness from parasitic
infection results in absence from school, leading to school failure and dropping out (Vince
Whitman et al., 2001). Structures and conditions of the learning environment are as
important to address as individual factors. Water and sanitation conditions at school can
affect girls’ attendance.
This paper studies transliteration alignment, its evaluation metrics and applications. We propose a new evaluation metric, alignment entropy, grounded on the information theory, to evaluate the alignment quality without the need for the gold standard reference and compare the metric with F -score. We study the use of phonological features and afﬁnity statistics for transliteration alignment at phoneme and grapheme levels. The experiments show that better alignment consistently leads to more accurate transliteration.
To put the odds ratios of these genetic markers in context, let’s consider the effect size of the above
mentioned environmental risk factors that physicians currently use to assess patients’ likelihood of
myocardial infarction. The effect size of the genetic markers 9p21 and MTHFD1L equals or surpasses the
effect size of most of the currently recognized medical risk factors -- an insight which many physicians
may find illuminating.
This paper presents a novel approach to automatic captioning of geo-tagged images by summarizing multiple webdocuments that contain information related to an image’s location. The summarizer is biased by dependency pattern models towards sentences which contain features typically provided for different scene types such as those of churches, bridges, etc. Our results show that summaries biased by dependency pattern models lead to signiﬁcantly higher ROUGE scores than both n-gram language models reported in previous work and also Wikipedia baseline summaries. ...
A key question facing the parsing community is how to compare parsers which use different grammar formalisms and produce different output. Evaluating a parser on the same resource used to create it can lead to non-comparable accuracy scores and an over-optimistic view of parser performance. In this paper we evaluate a CCG parser on DepBank, and demonstrate the difﬁculties in converting the parser output into DepBank grammatical relations.
We present a Minimum Bayes Risk (MBR) decoder for statistical machine translation. The approach aims to minimize the expected loss of translation errors with regard to the BLEU score. We show that MBR decoding on N -best lists leads to an improvement of translation quality. We report the performance of the MBR decoder on four different tasks: the TCSTAR EPPS Spanish-English task 2006, the NIST Chinese-English task 2005 and the GALE Arabic-English and Chinese-English task 2006. The absolute improvement of the BLEU score is between 0.2% for the TCSTAR task and 1.