Welcome to 501 Synonym and Antonym
Questions! This book is designed to help you prepare
for the verbal sections of many assessment and entrance
exams. By completing the exercises in this book you will also increase
your vocabulary and refine your knowledge of words.
Most standardized tests—including high school entrance exams,
the SAT, civil service exams, and the GRE—use synonym and
antonym questions to test verbal skills. These questions ask test takers
to identify the word that is most similar or dissimilar to another
word, effectively testing their knowledge of two words....
It is well known that parsing accuracy suffers when a model is applied to out-of-domain data. It is also known that the most beneﬁcial data to parse a given domain is data that matches the domain (Sekine, 1997; Gildea, 2001). Hence, an important task is to select appropriate domains. However, most previous work on domain adaptation relied on the implicit assumption that domains are somehow given.
Distributional word similarity is most commonly perceived as a symmetric relation. Yet, one of its major applications is lexical expansion, which is generally asymmetric. This paper investigates the nature of directional (asymmetric) similarity measures, which aim to quantify distributional feature inclusion. We identify desired properties of such measures, specify a particular one based on averaged precision, and demonstrate the empirical beneﬁt of directional measures for expansion.
This paper deals with the task of ﬁnding generally applicable substitutions for a given input term. We show that the output of a distributional similarity system baseline can be ﬁltered to obtain terms that are not simply similar but frequently substitutable. Our ﬁlter relies on the fact that when two terms are in a common entailment relation, it should be possible to substitute one for the other in their most frequent surface contexts.
This paper analyses the relation between the use of similarity in Memory-Based Learning and the notion of backed-off smoothing in statistical language modeling. We show that the two approaches are closely related, and we argue that feature weighting methods in the Memory-Based paradigm can offer the advantage of automatically specifying a suitable domainspecific hierarchy between most specific and most general conditioning information without the need for a large number of parameters. We report two applications of this approach: PP-attachment and POStagging. ...
We propose an automatic machine translation (MT) evaluation metric that calculates a similarity score (based on precision and recall) of a pair of sentences. Unlike most metrics, we compute a similarity score between items across the two sentences. We then ﬁnd a maximum weight matching between the items such that each item in one sentence is mapped to at most one item in the other sentence.
Detection of discourse structure is crucial in many text-based applications. This paper presents an original framework for describing textual parallelism which allows us to generalize various discourse phenomena and to propose a unique method to recognize them. With this prospect, we discuss several methods in order to identify the most appropriate one for the problem, and evaluate them based on a manually annotated corpus.
Beautiful beaches attract people, no doubt about it. Just look at this city’s beautiful beaches, which are among the most overcrowded beaches in the state. Which of the following exhibits a pattern of reasoning most similar to the one exhibited in the argument above? (A) Moose and bear usually appear at the same drinking hole at the same time of day. Therefore, moose and bear must grow thirsty at about the same time. (B) Children who are scolded severely tend to misbehave more often than other children. Hence, if a child is not scolded severely that child is less...
This paper proposes a new method for approximate string search, speciﬁcally candidate generation in spelling error correction, which is a task as follows. Given a misspelled word, the system ﬁnds words in a dictionary, which are most “similar” to the misspelled word. The paper proposes a probabilistic approach to the task, which is both accurate and efﬁcient. The approach includes the use of a log linear model, a method for training the model, and an algorithm for ﬁnding the top k candidates. ...
· Costa Rica undertook a forest depletion exercise similar to that of Indonesia; the work
was carried out by the Costa Rican Centro Cientifico Tropical and the Washington-based
World Resources Institute. Since then the Central Bank has taken a cautious attitude
towards institutionalizing the work, agreeing to include data in the accounts if another
institution took responsibility for developing them and doing the subjective valuation
Apart from the multiple alignment construction
problem, a fully automatic approach also has to
provide a clustering, and to work for multidomain
proteins, deﬁne domain boundaries. For instance,
the Domainer algorithm,
10 which performs the clus-
tering of domain families based on all versus all
Blastp matching, is a fully automatic approach that
was used for building the ProDom database. We are
most familiar with the Domainer method but believe
that other automated sequence clustering approaches
share similar drawbacks.
We consider a very simple, yet effective, approach to cross language adaptation of dependency parsers. We ﬁrst remove lexical items from the treebanks and map part-of-speech tags into a common tagset. We then train a language model on tag sequences in otherwise unlabeled target data and rank labeled source data by perplexity per word of tag sequences from less similar to most similar to the target. We then train our target language parser on the most similar data points in the source labeled data. ...
In order to obtain the sample, the universe of municipalities was those with little more than 100.000
individuals. The municipalities were classified in 25 strata according to geographical region, population
size living in the urban part of the municipality, the value of synthetic index for quality of life (QLI) as
well as education and health infrastructure.
Two treatment municipalities were randomly selected
within each stratum among the municipalities participating in Familias en Accion.
In insects, the functional molecules responsible for the taste system are still
obscure. The gene for a 28.5 kDa protein purified from taste sensilla of the
blowflyPhormia reginabelongs to a gene family that includestakeout of
Drosophila melanogaster. Molecular phylogenetic analysis revealed that the
PhormiaTakeout-like protein is most similar to the protein encoded by a
member of theDrosophila takeoutgene family, CG14661, whose expression
and function have not been identified yet.
TheSTAT5(signal transducer andactivator of transcription
5) genewas isolated and characterized froma round-spotted
pufferfish genomic library. This gene is composed of 19
exons spanning 11 kb. The full-length cDNA ofTetraodon
fluviatilis STAT5(TfSTAT5) contains 2461 bp and encodes
a protein of 785 amino acid residues. From the amino acid
sequence comparison,TfSTAT5 is most similar to mouse
STAT5a and STAT5bwith an overall identity of 76% and
78%, respectively, and has
Genomic and cDNA sequences coding for a fatty acid-binding protein
(FABP) in zebrafish were retrieved from DNA sequence databases. The
cDNA codes for a protein of 14.7 kDa (pI= 5.94), and the gene consists
of four exons, properties characteristic of most vertebrate FABP genes.
Phylogenetic analyses using vertebrate FABPs indicated that this protein is
most similar to zebrafish Fabp10.
During vitellogenesis, one of the most tightly regulated processes in ovipar-ous reproduction, vitellogenins are incorporated into the oocyte through
vitellogenin receptor (VgR)-mediated endocytosis. In this paper, we report
the cloning of the VgR cDNA from Blattella germanica, as well as the
first functional analysis of VgR following an RNA interference (RNAi)
This paper proposes a novel method to extract named entities including unfamiliar words which do not occur or occur few times in a training corpus using a large unannotated corpus. The proposed method consists of two steps. The ﬁrst step is to assign the most similar and familiar word to each unfamiliar word based on their context vectors calculated from a large unannotated corpus. After that, traditional machine learning approaches are employed as the second step.
The N-terminal fusion peptide of Sendai virus F1envelope
glycoprotein is a stretchof 14aminoacids,most ofwhichare
hydrophobic. Following this region, we detected a segment
of 11 residues that are strikingly similar to the N-terminal
fusion peptide. We found that, when anchored to the mem-brane by palmitoylation of its N-terminus, this segment
(WT-palm-19–33) induces membrane fusion of large unila-mellar liposomes toalmost the same extent as a segment that
includes the N-terminal fusion peptide....
The three MT systems are characterized by different translation units. D3 , HPAT, and SAT use sentences, phrases, and words, respectively. D3 (Sentence-based EBMT): It retrieves the most similar example by DP-matching of the input and example sentences and adjusts the gap between the input and the retrieved example by using dictionaries. (Sumita 2001) HPAT (Phrase-based EBMT): Based on phrasealigned bilingual trees, transfer patterns are generated.