@article {19160,
	title = {Dirichlet Mixtures, the Dirichlet Process, and the Structure of Protein Space},
	journal = {Journal of Computational Biology},
	volume = {20},
	number = {1},
	year = {2013},
	abstract = {The Dirichlet process is used to model probability distributions that are mixtures of an unknown number of components. Amino acid frequencies at homologous positions within related proteins have been fruitfully modeled by Dirichlet mixtures, and we use the Dirichlet process to derive such mixtures with an unbounded number of components. This application of the method requires several technical innovations to sample an unbounded number of Dirichlet-mixture components. The resulting Dirichlet mixtures model multiple-alignment data substantially better than do previously derived ones. They consist of over 500 components, in contrast to fewer than 40 previously, and provide a novel perspective on the structure of proteins. Individual protein positions should be seen not as falling into one of several categories, but rather as arrayed near probability ridges winding through amino acid multinomial space.},
	keywords = {ALIGNMENT, computational molecular biology, dynamic programming, multiple alignment, sequence analysis},
	doi = {10.1089/cmb.2012.0244},
	author = {Nguyen,Viet-An and Jordan Boyd-Graber and Altschul, Stephen F.}
}
@article {13790,
	title = {Improved Word-Level Alignment: Injecting Knowledge about MT Divergences},
	year = {2002},
	month = {2002/02/14/},
	institution = {Instititue for Advanced Computer Studies, Univ of Maryland, College Park},
	abstract = {Word-level alignments of bilingual text (bitexts) are not an integral part of statistical machine translation models, but also useful for lexical acquisition, treebank construction. and part-of-speech tagging. The frequent occurrence of divergences, structural differences between languages, presents a great challenge to the alignment task. We resolve some of the most prevalent divergence cases by using syntactic parse information to transform the sentence structure of one language to bear a closer resemblance to that of the other language. In this paper, we show that common divergence types can be found in multiple language pairs (in particular, we focus on English-Spanish and English-Arabic) and systematically identified. We describe our techniques for modifying English parse trees to form resulting sentences that share more similarity with the sentences in the other languages; finally, we present an empirical analysis comparing the complexities of performing word-level alignments with an without divergence handling. Our results suggest that divergence-handling can improve word-level alignment.},
	keywords = {*LEXICOGRAPHY, *MACHINE TRANSLATION, *STATISTICAL ANALYSIS, *WORDS(LANGUAGE), ACQUISITION, ALIGNMENT, EXPERIMENTAL DATA, LANGUAGE, linguistics, MATHEMATICAL MODELS, STATISTICS AND PROBABILITY, TREES},
	url = {http://stinet.dtic.mil/oai/oai?\&verb=getRecord\&metadataPrefix=html\&identifier=ADA458774},
	author = {Dorr, Bonnie J and Pearl,Lisa and Hwa,Rebecca and Habash,Nizar}
}
@article {16720,
	title = {Word-level Alignment for Multilingual Resource Acquisition},
	year = {2002},
	month = {2002/04//},
	institution = {Instititue for Advanced Computer Studies, Univ of Maryland, College Park},
	abstract = {We present a simple, one-pass word alignment algorithm for parallel text. Our algorithm utilizes synchronous parsing and takes advantage of existing syntactic annotations. In our experiments the performance of this model is comparable to more complicated iterative methods. We discuss the challenges and potential benefits of using the model to train syntactic parsers for new languages.},
	keywords = {*LEARNING MACHINES, *MULTILINGUAL RESOURCES, *WORDS(LANGUAGE), ACQUISITION, algorithms, ALIGNMENT, BENEFITS, ITERATIONS, LANGUAGE, linguistics},
	url = {http://stinet.dtic.mil/oai/oai?\&verb=getRecord\&metadataPrefix=html\&identifier=ADA458782},
	author = {Lopez,Adam and Nossal,Michael and Hwa,Rebecca and Resnik, Philip}
}
@article {11945,
	title = {Correspondence from Correspondence},
	journal = {Optical Society of America, Topical Meeting on Machine Vision},
	year = {1980},
	month = {1980///},
	pages = {46 - 51},
	abstract = {Image matching (or registration), is in general terms, aligning two identical or similar images or parts of images, and it is basic to a number of vision problems. These include optical nagivation (also known as motion analysis), stereo image interpretation, object analysis, change detection and others. The difficult part of all these problems, is the matching problem, i.e., the computation of the correspondence of elements in the different views. The computation of correspondence, in both the stereo and the motion problem is impossible without the use of some assumptions about the visual world and various researchers have proposed several theories for the computation of visual correspondence that worked well for the domains that fitted their assumptions. Studied here is the problem of the computation of visual correspondence, under the assumption that some values of the correspondence function are already known. The mathematical constraints that are needed for growing a solution for the correspondence function from points where its value is known are developed.},
	keywords = {ALIGNMENT, COMPUTATION, Error analysis, IMAGE PROCESSING, IMAGES, STEREOSCOPIC VISION, VECTORS (MATHEMATICS)},
	url = {http://adsabs.harvard.edu/abs/1980osa..meet...46A},
	author = {Aloimonos, J. and Kamgar-Parsi,Behrooz}
}
