A framework for parsing heritable information

Information Pursuit: A Bayesian Framework for Sequential Scene Parsing

Despite enormous progress in object detection and classification, the problem of incorporating expected contextual relationships among object instances into modern recognition systems remains a key challenge. In this work we propose information pursuit, a Bayesian framework for scene parsing that combines prior models for the geometry of the scene and the spatial arrangement of objects instance...

A Framework For Incorporating Alignment Information In Parsing

The standard PCFG approach to parsing is quite successful on certain domains, but is relatively inflexible in the type of feature information we can include in its probabilistic model. In this work, we discuss preliminary work in developing a new probabilistic parsing model that allows us to easily incorporate many different types of features, including crosslingual information. We show how thi...

a framework for identifying and prioritizing factors affecting customers’ online shopping behavior in iran

the purpose of this study is identifying effective factors which make customers shop online in iran and investigating the importance of discovered factors in online customers’ decision. in the identifying phase, to discover the factors affecting online shopping behavior of customers in iran, the derived reference model summarizing antecedents of online shopping proposed by change et al. was us...

A generalized parsing framework for Abstract Grammars

This technical report presents a general framework for parsing a variety of grammar formalisms. We develop a grammar formalism, called an Abstract Grammar, which is general enough to represent grammars at many levels of the hierarchy, including Context Free Grammars (CFGs), Minimalist Grammars (MG), and other weakly MG-equivalent languages like Linear Context-Free Rewriting Systems. We then dev...

A Framework for SGLR Parsing in Java