maximum entropy approach
Maximum Entropy Approach based Named Entity Recognition in Punjabi Language
... Named Entity Recognition is the task of identifying and classifying named entities into some predefine categories like person, location, organization etc. NER is used in many applications like text summarization, text ...
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A Maximum Entropy Approach to Combining Word Alignments
... This paper presents a new approach to combining outputs of existing word align- ment systems. Each alignment link is rep- resented with a set of feature functions extracted from linguistic features and in- put ...
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Refined Lexicon Models for Statistical Machine Translation using a Maximum Entropy Approach
... the maximum en- tropy approach. This approach has been applied in natural language processing to a variety of ...this approach to the so-called IBM Candide system to build con- text dependent ...
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A maximum entropy approach to detect close-in giant planets around active stars
... present maximum entropy method constitutes a very simple way to extract orbital parameters from heavily distorted line profiles of active stars, paving the way towards a system- atic search for close-in ...
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Named Entity Recognition: A Maximum Entropy Approach Using Global Information
... The maximum entropy framework estimates prob- abilities based on the principle of making as few assumptions as possible, other than the constraints ...highest entropy. It is unique, agrees with the ...
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Economic-environmental efficiency of European agriculture – a generalized maximum entropy approach
... Abstract: The study aims to estimate the agricultural economic-environmental efficiency (eco-efficiency) for European countries. Eco-efficiency is obtained by the data envelopment analysis (DEA) and stochastic frontier ...
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A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation
... has maximum entropy (see Cover and Thomas, 1991, Problem 5, Chapter ...the maximum entropy distribution has the form in (3). The maximum entropy characterization ensures that ...
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Multi-directional maximum-entropy approach to the evolutionary design optimization of water distribution systems
... Example 1 is a hypothetical network from the literature (Fig. 1a). Awumah et al. (1990) introduced this network that has been used previously in many studies concerned with entropy including Awumah et al. (1991), ...
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A Maximum Entropy Approach to Natural Language Processing
... The feature selection algorithm de- scribed in Section 4 calculated that if this constraint were imposed on the model, the log-likelihood w o u l d rise by approximately 0.019059 bits; s[r] ...
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A Maximum Entropy Approach for Semantic Language Modeling
... In this study, we evaluate the proposed ME language model by measuring the model perplexity and the character-error rate in continuous speech recognition. The conventional n-gram language model is used as the baseline, ...
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A Maximum Entropy Approach to Chinese Spelling Check
... Spelling check identifies incorrect writ- ing words in documents. For the reason of input methods, Chinese spelling check is much different from English and it is still a challenging work. For the past dec- ade years, ...
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Semantic Role Labeling of NomBank: A Maximum Entropy Approach
... Opennlp maxent 1 , an implementation of Maxi- mum Entropy (ME) modeling, is used as the clas- sification tool. Since its introduction to the Natural Language Processing (NLP) community (Berger et al., 1996), ...
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A Maximum-Entropy approach for accurate document annotation in the biomedical domain
... a Maximum Entropy-based approach for our task is the fact that similar approaches have been applied to text related tasks in the biomedical ...a Maximum Entropy- based approach ...
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Maximum Entropy Models for FrameNet Classification
... The development of FrameNet, a large database of semantically annotated sen- tences, has primed research into statistical methods for semantic tagging. We ad- vance previous work by adopting a Maximum ...
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Maximum Entropy Discrimination Markov Networks
... the maximum margin principle and convex optimization formulation un- derlying the support vector machines, and concentrate directly on the input-output mapping (Taskar et ...this approach can lead to a ...
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Feature Lattices for Maximum Entropy Modelling
... Our approach uses the feature collocation lattice and builds complex candidate features without resorting to iterative scaling.. Maximum entropy modelling has been recently introduced to[r] ...
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Subjectivity in Application of the Principle of Maximum Entropy
... Bayesian estimation is formulated for PME prior. The combination of the maximum likelihood function and the prior distribution makes Bayes approach superior to traditional approaches limited to the former. ...
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Using the maximum entropy production approach to integrate energy budget modelling in a hydrological model
... mum entropy production (MEP) model of land surface fluxes offers an alternative approach for simulating terrestrial evap- oration in a simple way while fulfilling the physical con- straint of energy budget ...
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Information Entropy Production of Maximum Entropy Markov Chains from Spike Trains
... Consider a finite and fix number of neurons N and a potential of range 1. This case includes the Ising model [5], Triplets [9], K-pairwise [7] and all other memoryless potentials that has been used in the context of ...
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Entire Relaxation Path for Maximum Entropy Problems
... the maximum entropy principle to language processing is the work of Berger, Della Pietra × 2, and Lafferty (Berger et ...highest entropy subject to equality ...relaxed maximum-entropy ...
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