We show that combining both bottom-up rule chunking and top-down rule segmentation search strategies in purely unsupervised learning of phrasal inversion transduction grammars yields significantly better translation accuracy than either strategy alone. Previous approaches have relied on incrementally building larger rules by chunking smaller rules bottomup; we introduce a complementary top-down...

This paper describes a human-like natural language parser called Plink. It works by parsing left-to-right through a sentence and keeping a complete representation of the partially read sentence. It does this by combining a sophisticated unification-based grammar and grammar rule selection heuristics. Plink also functions in real world applications. To do this, it must process texts that are not...

Research from over 200 studies demonstrates that combining forecasts produces consistent but modest gains in accuracy. However, this research does not define well the conditions under which combining is most effective nor how methods should be combined in each situation. Rule-based forecasting can be used to define these conditions and to specify more effective combinations. Introduction “Combi...

BACKGROUND/AIMS The aim of this study was to assess whether combining the Rowland Universal Dementia Assessment Scale (RUDAS) and Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) could improve diagnostic accuracy when screening for dementia in an Arabic-speaking population with low levels of literacy. METHODS Based on data from 225 elderly participant and informant dyads, ...

This paper studies the problem of diversity combining for frequency-hopped multiple access (FHMA) systems that operate in a mobile satellite environment characterized by frequency-nonselective Rician multipath fading. The modulation scheme considered is the incoherent 3f-ary frequency-shift keying (MFSK). The optimal diversity combining rule is derived under the assumptions that the number of a...

Henry’s law constants of the solutes methane, nitrogen, oxygen and carbon dioxide in the solvent ethanol are predicted by molecular simulation. The molecular models for the solutes are taken from previous work. For the solvent ethanol, a new rigid anisotropic united atom molecular model based on Lennard-Jones and Coulombic interactions is developed. It is adjusted to experimental pure component...

It is well known that there cannot be a single “best” heuristic for optimal planning in general. One way of overcoming this is by combining admissible heuristics (e.g. by using their maximum), which requires computing numerous heuristic estimates at each state. However, there is a tradeoff between the time spent on computing these heuristic estimates for each state, and the time saved by reduci...

The aim of this paper is to present some findings from a study into how a large scale semantic resource, FrameNet, can be applied for event extraction in the (Swedish) biomedical domain. Combining lexical resources with domain specific knowledge provide a powerful modeling mechanism that can be utilized for event extraction and other advanced text miningrelated activities. The results, from dev...

Written contracts are a fundamental framework for commercial and cooperative transactions and relationships. Limited research has been published on the application of machine learning and natural language processing (NLP) to contracts. In this paper we report the classification of components of contract texts using machine learning and hand-coded methods. Authors studying a range of domains hav...

To improve weak classifiers bagging and boosting could be used. These techniques are based on combining classifiers. Usually, a simple majority vote or a weighted majority vote are used as combining rules in bagging and boosting. However, other combining rules such as mean, product and average are possible. In this paper, we study bagging and boosting in Linear Discriminant Analysis (LDA) and t...