scholarly journals Knowledge Compilation meets Uniform Sampling

10.29007/h4p9 ◽  
2018 ◽  
Author(s):  
Shubham Sharma ◽  
Rahul Gupta ◽  
Subhajit Roy ◽  
Kuldeep S. Meel
Keyword(s):  
Programming Languages ◽  
State Of The Art ◽  
The State ◽  
Knowledge Compilation ◽  
New Approach ◽  
Uniform Sampling ◽  
Incremental Sampling ◽  
Uniform Generation ◽  
Constrained Random Verification ◽  
Primary Contribution

Uniform sampling has drawn diverse applications in programming languages and software engineering, like in constrained-random verification (CRV), constrained-fuzzing and bug synthesis. The effectiveness of these applications depend on the uniformity of test stimuli generated from a given set of constraints. Despite significant progress over the past few years, the performance of the state of the art techniques still falls short of those of heuristic methods employed in the industry which sacrifice either uniformity or scalability when generating stimuli.In this paper, we propose a new approach to the uniform generation that builds on recent progress in knowledge compilation. The primary contribution of this paper is marrying knowledge compilation with uniform sampling: our algorithm, KUS, employs the state-of-the-art knowledge compilers to first compile constraints into d-DNNF form, and then, generates samples by making two passes over the compiled representation.We show that KUS is able to significantly outperform existing state-of-the-art algorithms, SPUR and UniGen2, by up to 3 orders of magnitude in terms of runtime while achieving a geometric speedup of 1.7× and 8.3× over SPUR and UniGen2 respectively. Also, KUS achieves a lower PAR-21 score, around 0.82× that of SPUR and 0.38× that of UniGen2. Furthermore, KUS achieves speedups of up to 3 orders of magnitude for incremental sampling. The distribution generated by KUS is statistically indistinguishable from that generated by an ideal uniform sampler. Moreover, KUS is almost oblivious to the number of samples requested.

scholarly journals Graph Algorithms for Word Sense Disambiguation in Biomedicine

2015 ◽  
Author(s):  
Rodrigo Goulart ◽  
Juliano De Carvalho ◽  
Vera De Lima
Keyword(s):  
Text Mining ◽  
Graph Algorithms ◽  
State Of The Art ◽  
Word Sense Disambiguation ◽  
The State ◽  
Word Sense ◽  
New Approach ◽  
Similar Performance ◽  
Sense Disambiguation ◽  
Different Levels

Word Sense Disambiguation (WSD) is an important task for Biomedicine text-mining. Supervised WSD methods have the best results but they are complex and their cost for testing is too high. This work presents an experiment on WSD using graph-based approaches (unsupervised methods). Three algorithms were tested and compared to the state of the art. Results indicate that similar performance could be reached with different levels of complexity, what may point to a new approach to this problem.

Language-Independent Type Inference of the Instances from Multilingual Wikipedia

2019 ◽  
Vol 15 (2) ◽  
pp. 22-46 ◽  
Author(s):  
Tianxing Wu ◽  
Guilin Qi ◽  
Bin Luo ◽  
Lei Zhang ◽  
Haofen Wang
Keyword(s):  
Knowledge Base ◽  
State Of The Art ◽  
The State ◽  
Type Inference ◽  
Experimental Results ◽  
High Quality ◽  
New Approach ◽  
Semantic Associations ◽  
Quality Type ◽  
Type Information

Extracting knowledge from Wikipedia has attracted much attention in recent ten years. One of the most valuable kinds of knowledge is type information, which refers to the axioms stating that an instance is of a certain type. Current approaches for inferring the types of instances from Wikipedia mainly rely on some language-specific rules. Since these rules cannot catch the semantic associations between instances and classes (i.e. candidate types), it may lead to mistakes and omissions in the process of type inference. The authors propose a new approach leveraging attributes to perform language-independent type inference of the instances from Wikipedia. The proposed approach is applied to the whole English and Chinese Wikipedia, which results in the first version of MulType (Multilingual Type Information), a knowledge base describing the types of instances from multilingual Wikipedia. Experimental results show that not only the proposed approach outperforms the state-of-the-art comparison methods, but also MulType contains lots of new and high-quality type information.

Mapping the surface (hydr)oxo-groups of titanium oxide and its interface with an aqueous solution: The state of the art and a new approach

2008 ◽  
Vol 142 (1-2) ◽  
pp. 20-42 ◽  
Author(s):  
George D. Panagiotou ◽  
Theano Petsi ◽  
Kyriakos Bourikas ◽  
Christos S. Garoufalis ◽  
Athanassios Tsevis ◽  
...  
Keyword(s):  
Aqueous Solution ◽  
Titanium Oxide ◽  
State Of The Art ◽  
The State ◽  
New Approach

scholarly journals Using two-stream theory to capture fluctuations of satellite-perceived TOA SW radiances reflected from clouds over ocean

2020 ◽  
Vol 13 (7) ◽  
pp. 3909-3922
Author(s):  
Florian Tornow ◽  
Carlos Domenech ◽  
Howard W. Barker ◽  
René Preusker ◽  
Jürgen Fischer
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
State Of The Art ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Cloud Water ◽  
Effective Radius ◽  
The State ◽  
Distribution Models ◽  
New Approach

Abstract. Shortwave (SW) fluxes estimated from broadband radiometry rely on empirically gathered and hemispherically resolved fields of outgoing top-of-atmosphere (TOA) radiances. This study aims to provide more accurate and precise fields of TOA SW radiances reflected from clouds over ocean by introducing a novel semiphysical model predicting radiances per narrow sun-observer geometry. This model was statistically trained using CERES-measured radiances paired with MODIS-retrieved cloud parameters as well as reanalysis-based geophysical parameters. By using radiative transfer approximations as a framework to ingest the above parameters, the new approach incorporates cloud-top effective radius and above-cloud water vapor in addition to traditionally used cloud optical depth, cloud fraction, cloud phase, and surface wind speed. A two-stream cloud albedo – serving to statistically incorporate cloud optical thickness and cloud-top effective radius – and Cox–Munk ocean reflectance were used to describe an albedo over each CERES footprint. Effective-radius-dependent asymmetry parameters were obtained empirically and separately for each viewing-illumination geometry. A simple equation of radiative transfer, with this albedo and attenuating above-cloud water vapor as inputs, was used in its log-linear form to allow for statistical optimization. We identified the two-stream functional form that minimized radiance residuals calculated against CERES observations and outperformed the state-of-the-art approach for most observer geometries outside the sun-glint and solar zenith angles between 20 and 70∘, reducing the median SD of radiance residuals per solar geometry by up to 13.2 % for liquid clouds, 1.9 % for ice clouds, and 35.8 % for footprints containing both cloud phases. Geometries affected by sun glint (constituting between 10 % and 1 % of the discretized upward hemisphere for solar zenith angles of 20 and 70∘, respectively), however, often showed weaker performance when handled with the new approach and had increased residuals by as much as 60 % compared to the state-of-the-art approach. Overall, uncertainties were reduced for liquid-phase and mixed-phase footprints by 5.76 % and 10.81 %, respectively, while uncertainties for ice-phase footprints increased by 0.34 %. Tested for a variety of scenes, we further demonstrated the plausibility of scene-wise predicted radiance fields. This new approach may prove useful when employed in angular distribution models and may result in improved flux estimates, in particular dealing with clouds characterized by small or large droplet/crystal sizes.

Language-Independent Type Inference of the Instances from Multilingual Wikipedia

2022 ◽  
pp. 580-606
Author(s):  
Tianxing Wu ◽  
Guilin Qi ◽  
Bin Luo ◽  
Lei Zhang ◽  
Haofen Wang
Keyword(s):  
Knowledge Base ◽  
State Of The Art ◽  
The State ◽  
Type Inference ◽  
Experimental Results ◽  
High Quality ◽  
New Approach ◽  
Semantic Associations ◽  
Quality Type ◽  
Type Information

Extracting knowledge from Wikipedia has attracted much attention in recent ten years. One of the most valuable kinds of knowledge is type information, which refers to the axioms stating that an instance is of a certain type. Current approaches for inferring the types of instances from Wikipedia mainly rely on some language-specific rules. Since these rules cannot catch the semantic associations between instances and classes (i.e. candidate types), it may lead to mistakes and omissions in the process of type inference. The authors propose a new approach leveraging attributes to perform language-independent type inference of the instances from Wikipedia. The proposed approach is applied to the whole English and Chinese Wikipedia, which results in the first version of MulType (Multilingual Type Information), a knowledge base describing the types of instances from multilingual Wikipedia. Experimental results show that not only the proposed approach outperforms the state-of-the-art comparison methods, but also MulType contains lots of new and high-quality type information.

scholarly journals Efficient Structured Inference for Transition-Based Parsing with Neural Networks and Error States

2016 ◽  
Vol 4 ◽  
pp. 183-196 ◽  
Author(s):  
Ashish Vaswani ◽  
Kenji Sagae
Keyword(s):  
Neural Networks ◽  
State Of The Art ◽  
The State ◽  
Local Models ◽  
Dependency Parsing ◽  
New Approach ◽  
Local Classification

Transition-based approaches based on local classification are attractive for dependency parsing due to their simplicity and speed, despite producing results slightly below the state-of-the-art. In this paper, we propose a new approach for approximate structured inference for transition-based parsing that produces scores suitable for global scoring using local models. This is accomplished with the introduction of error states in local training, which add information about incorrect derivation paths typically left out completely in locally-trained models. Using neural networks for our local classifiers, our approach achieves 93.61% accuracy for transition-based dependency parsing in English.

A New Approach to Evaporation

1968 ◽  
Author(s):  
Derek F. Dinnage
Keyword(s):  
State Of The Art ◽  
The State ◽  
New Techniques ◽  
New Approach

The ever growing need for the removal of water from solutions has brought forward the development of many new techniques. As the state-of-the-art has become more sophisticated, specialist designs have been evolved to cater for particular requirements. Paper published with permission.

gXML, a New Approach to Cultivating XML Trees in Java

2010 ◽  
Author(s):  
Amelia A. Lewis ◽  
Eric E. Johnson
Keyword(s):  
Data Model ◽  
Design Pattern ◽  
State Of The Art ◽  
The State ◽  
Model Specification ◽  
Tree Model ◽  
New Approach ◽  
Model Following ◽  
Tree Models

A number of issues facing the use of XML tree models in Java are enumerated: multiplicity, interoperability, variability, and weight. The gXML API, following the Handle/Body design pattern and conforming to the XQuery Data Model specification XDM, is proposed as a solution to these problems, and as a platform for advancing the state of the art for XML in Java. gXML is not a new tree model, but a unified API and model following a rigorous, external specification, which can be used with any tree model for which a "bridge" has been developed. Applications and processors targeting the gXML API may then use any supported tree model, as appropriate for the task.

scholarly journals Ontology Mapping using Fuzzy Decision Tree and Formal Concept Analysis

2013 ◽  
Vol 8 (1) ◽  
pp. 743-750
Author(s):  
Manjula Shenoy ◽  
Dr. K.C. Shet ◽  
Dr. U. Dinesh Acharya
Keyword(s):  
Decision Tree ◽  
Formal Concept Analysis ◽  
State Of The Art ◽  
Concept Analysis ◽  
The State ◽  
Ontology Mapping ◽  
Formal Concept ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree ◽  
New Approach

An ontology describes and defines the terms used to describe and represent an area of knowledge. Different people or organizations come up with their own ontology; having their own view of the domain. So, for systems to interoperate, it becomes necessary to map these heterogeneous ontologies.This paper discusses the state of the art methods and outlines a new approach with improved precision and recall. Also the system finds other than 1:1 relationships. 

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