This paper introduces a method for learning to find translation of a given source term on the Web. In the approach, the source term is used as a query and part of patterns to retrieve and extract translations in Web pages. The method involves using a bilingual term list to learn sourcetarget surface patterns. At runtime, the given term is submitted to a search engine then the candidate translations are extracted from the returned summaries and subsequently ranked based on the surface patterns, occurrence counts, and transliteration knowledge.
Skills tested by STAT
STAT F, STAT T and STAT Multiple Choice each
consist of 70 items, which are placed into Units .
Units comprise either Verbal or Quantitative
questions. Quantitative and Verbal units are
interspersed throughout the test paper .
STAT questions are based on stimulus material
drawn from a variety of common sources . All
the information required to answer questions
is contained in the Unit . So, for example, if the
stimulus material is an historical document, the
candidate’s knowledge of history is NOT being
Secondly, seeking out paid work should always be the choice of women themselves.
Policies adopted by conservative government administrations such as workfare, which
force social assistance recipients into the workforce, ìÖcreate a source of low-wage and
free labour by providing subsidies to the private sector and forcing recipients to volunteer
in exchange for assistanceî.
These polices are based on a distrust of those living in
poverty, and do not empower, but malign people into working for pay.
These different sources of propaganda and/or violence vary in
their intellectual underpinnings, sectarian and political aims,
and in their internationalist or nationalist orientations. But
what they have in common is an assault on the values of the
West – on its democratic processes and its freedom of religion
– and an exultation over the murder of Jews, Americans,
Hindus, ‘unbelievers’, ‘infidels’, ‘apostates’ and various ‘infe-
The modern drug discovery process, in general, involves the identiﬁcation of a biochemical target (usually protein target), screening of synthetic compounds or compound libraries from combinatorial chemistry/natural sources for a lead compound, and optimization of the lead compound (activity, selectivity, pharmacokinetics, etc.) for recommending a potential clinical candidate.
Atrial fibrillation is a rapidly evolving epidemic associated with increased cardiovascular
morbidity and mortality, and its prevalence has increased during the past few decades. In
the past few years, the recent understanding of the diverse mechanisms of this arrhythmia
has led to the improvement of our therapeutic strategies. However, many clinicians have
still felt the frustration in management of this commonly encountered arrhythmia.
If you have obtained competitive bids, the proposals are the grounds for your decision and
ultimately for the contract. In the case of a sole-source contract, the proposal is the basis for
agreement between client and conservator on the scope of work, fee, schedule, and other
To evaluate proposals in either case, form a small advisory committee of knowledgeable
people who can assess the technical merits of each conservator’s experience, methods and
materials, schedule, and fee.
Can they read and understand materi¬als in textbooks? Understand and take notes on lectures? Hold conversations with teachers, administrators, and other students? Write papers involving a number of sources? The new test indicates whether candidates have these skills.
In this paper we focus on how to improve pronoun resolution using the statisticsbased semantic compatibility information. We investigate two unexplored issues that inﬂuence the effectiveness of such information: statistics source and learning framework. Speciﬁcally, we for the ﬁrst time propose to utilize the web and the twin-candidate model, in addition to the previous combination of the corpus and the single-candidate model, to compute and apply the semantic information. t
Discriminative reranking is one method for constructing high-performance statistical parsers (Collins, 2000). A discriminative reranker requires a source of candidate parses for each sentence. This paper describes a simple yet novel method for constructing sets of 50-best parses based on a coarse-to-ﬁne generative parser (Charniak, 2000). This method generates 50-best lists that are of substantially higher quality than previously obtainable. We used these parses as the input to a MaxEnt reranker (Johnson et al., 1999; Riezler et al.
SMT has been used in paraphrase generation by translating a source sentence into another (pivot) language and then back into the source. The resulting sentences can be used as candidate paraphrases of the source sentence.
In Cross-Language Information Retrieval (CLIR), Out-of-Vocabulary (OOV) detection and translation pair relevance evaluation still remain as key problems. In this paper, an English-Chinese Bi-Directional OOV translation model is presented, which utilizes Web mining as the corpus source to collect translation pairs and combines supervised learning to evaluate their association degree.
This paper extends previous work on extracting parallel sentence pairs from comparable data (Munteanu and Marcu, 2005). For a given source sentence S, a maximum entropy (ME) classiﬁer is applied to a large set of candidate target translations . A beam-search algorithm is used to abandon target sentences as non-parallel early on during classiﬁcation if they fall outside the beam. This way, our novel algorithm avoids any document-level preﬁltering step.
level knowledge sources can then be used to select a decision from the candidate set for each word image. In this paper, we propose that visual inter-word constraints can be used to facilitate candidate selection. Visual inter-word constraints provide a way to link word images inside the text page, and to interpret t h e m systematically. Introduction The objective of visual text recognition is to transform an arbitrary image of text into its symbolic equivalent correctly.