natural language programming research papers


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Inductive logic programming for natural language processing
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This paper reviews our recent work on applying inductive logic programming to the
construction of natural language processing systems. We have developed a system, Chill,
that learns a parser from a training corpus of parsed sentences by inducing heuristics that 

NLP (natural language processing) for NLP (natural language programming)
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Abstract. Natural Language Processing holds great promise for making computer interfaces
that are easier to use for people, since people will (hopefully) be able to talk to the computer
in their own language, rather than learn a specialized language of computer commands. 

 Using inductive logic programming to automate the construction of natural language parsers
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Computer understanding of natural (human) languages is one of the oldest and most
enduring challenges in the eld of arti cial intelligence. Fundamental to the problem of
computer understanding is the ability to translate or parse natural language inputs into an 

Feasibility studies for programming in natural language
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H Lieberman, H Liu ,End User Development, 2006 ,Springer
We think it is time to take another look at an old dream—that one could program a computer
by speaking to it in natural language. Programming in natural language might seem
impossible, because it would appear to require complete natural language understanding 

 Theoretical foundations of natural language programming and publishing for intelligent agents and robots
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SM Veres ,Proc. 11th Conference Towards , 2010 ,cognitive-agent-toolbox.com
Abstract—This paper is an application of ontology theory, conceptual graph and
programming languages theories to develop the foundations of natural language
programming (NLP) that can be used to produce natural language documents for 

Using answer set programming and lambda calculus to characterize natural languagesentences with normatives and exceptions
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TC Son ,2008 ,aaai.org
Abstract One way to solve the knowledge acquisition bottleneck is to have ways to translate
natural language sentences and discourses to a formal knowledge representation
language, especially ones that are appropriate to express domain knowledge in sciences, 

Multiobjective genetic programming for natural language parsing and tagging
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L Araujo ,Parallel Problem Solving from Nature-PPSN IX, 2006 ,Springer
Abstract. Parsing and Tagging are very important tasks in Natural Language Processing.
Parsing amounts to searching the correct combination of grammatical rules among those
compatible with a given sentence. Tagging amounts to labeling each word in a sentence 

 Constraint programming for natural language processing
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D Duchier ,Lecture Notes, ESSLLI, 2000 ,news.mozart-oz.org
Abstract This course demonstrates how constraint programming can be used effectively in
practice, for linguistic applications. It shows how many forms of ambiguity arising in
computational linguistic can be represented compactly and elegantly, and processed 

 A Flexible Representation for Genetic Programming: Lessons from Natural LanguageProcessing
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Abstract This thesis principally addresses some problems in genetic programming (GP) and
grammar-guided genetic programming (GGGP) arising from the lack of operators able to
make small and bounded changes on both genotype and phenotype space. It proposes a 

Parallel distributed genetic programming applied to the evolution of natural languagerecognisers
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This paper describes an application of Parallel Distributed Genetic Programming (PDGP) to
the problem of inducing recognisers for natural language from positive and negative
examples. PDGP is a new form of Genetic Programming (GP) which is suitable for the 

 Integrating top-down and bottom-up approaches in inductive logic programming: applications in natural language processing and relational data mining
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B Porter, R Miikkulainen ,2003 ,lib.utexas.edu
Machine learning concerns with the question of how to construct computer programs that
automatically improve with experience (aka learning algorithms)(Mitchell, 1997). Many a
successful

Machine learning application to the Korean freshwater ecosystems
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This paper considers the advantage of Machine Learning (ML) implemented to freshwater ecosystem research. Currently, many studies have been carried out to find the patterns of environmental impact on dynamics of communities in aquatic ecosystems. Ecological

Designing a machine learning Based framework for enhancing performance of livestock mobile application system
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a real intelligent one. Figure 10. Typical learning. 4.3.3. Steps in Developing Machine Learning Application Below are steps that will be used in developing machine learning application . 1) Collect data. Data will be collected

On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning
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Page 1. On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning

Machine Learning Application for Stock Market Prices Prediction.
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The development of a vibrant application for analyzing and predicting stock market prices is a basic tool aimed at increasing the rate of investors interest in stock markets. This paper explains the development and implementation of a stock price prediction application using

Extremal Entropy: Information Geometry, Numerical Entropy Mapping, and Machine Learning Application of Associated Conditional Independences
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Entropy and conditional mutual information are the key quantities information theory provides to measure uncertainty of and independence relations between random variables. While these measures are key to diverse areas such as physics, communication, signal

Machine Learning Application to Improve COCOMO Model using Neural Networks
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Millions of companies expend billions of dollars on trillions of software for the development and maintenance. Still many projects result in failure causing heavy financial loss. Major reason is the inefficient effort estimation techniques which are not so suitable for the current

Machine Learning Methods Application to Search for Regularities in Chemical Data
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The success of approach that was put forward in IMET has given an impetus to many investigations which were connected with machine learning application to inorganic chemistry and materials science and carried-out in various countries

MACHINE LEARNING APPLICATION IN THE FINANCIAL MARKETS INDUSTRY
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Machine Learning is increasingly prevalent in Stock Market trading. The goal of this paper is to investigate whether the machine learning technique is able to retrieve information from past prices and predict price movement and future trends. We explore using trend trading

Machine learning application in optimization of flexible circuit configuration
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One solution is to place semi-rigid transistors on a flexible polymer substrate. Next, we can optimize the transistor placement on the substrate using particle swarm optimization to minimize some objective (area, factor of safety, etc.). This has been successfully performed

MACHINE LEARNING APPLICATION IN LOAN DEFAULT PREDICTION
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In Todays world, most of world population has access to banking services. Consumers has increased many fold in last few years. For the banks, risks related to bank loans has increased especially after The Great Recession (2007 2012) and job threats due to

Machine Learning Application On Detecting Nudity In Images
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We built a mobile app that help people get opinions and recommendations from their social network. The app enables people to create picture poll and have friends to vote on it. Since it contains user-generated content, it is essential to censor the content to ensure that there is

MOBILE MIND: A FULLY MOBILE PLATFORM BASED MACHINE LEARNING APPLICATION
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In recent years, mobile devices have developed significantly in terms of technical capabilities, computing power, storage capacity and ability of sensing different activities via intelligent built-in sensors. In this perspective, capabilities of ultimate mobile phone

A Machine Learning Application for Latency Prediction in Operational 4G Networks
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Measuring performance on Internet is always challenging. When it comes to the mobile networks, the variety of technology characteristics coupled with the opaque network configuration make the performance evaluation even a more difficult task. Latency is one of

Selection of indicators by machine learning : Application to estimate permanent grassland plant richness
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Indicator based on key species or other data from field observation are very useful to manage permanent grasslands or to control result-oriented agri-environment schemes. These indicators must generally fulfil the following features: purpose relevance (ie optimize

ILP for Cosmetic Product Selection-Use of Smart Phone for Real-World Machine Learning Application
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In this study, we design a real-world machine learning system using a smart phone. This system can acquire images taken with the camera of a smart phone using learners (ILP and SVM) and automatically diagnose the new image. To develop this system, we implement an

Analysis of Machine Learning Research and Application
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similarity category. This algorithm is simple and computational speed, particularly the faster speed of classification, when compared with other algorithms. C. Machine Learning application in Data Mining Machine learning methods

Building real time object detection iOS application using machine learning
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(NPL) with a limited number of APIs and is only available for iOS 11 and above . Figure 6. General machine learning application structure. Copied from Apple documentation forward usage. In order to start integrating machine learning application , one just needs

Data visualisation and machine learning web application with potential use in sports data analytics
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data 3. Can a machine learning application , such as the one implemented in this project, be used in sports science to make predictions about athletic performance using biomarker data 2 Page 11. 1.3.2 Research Objectives

Increasing Portable Machine Learning Performance by Application of Rewrite Rules on Google Tensorflow Data Flow Graphs
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3 1.1 Contributions The goal of this project is to be able to execute as much of an existing Google Ten- sorflow machine learning application within the data parallel programming language Lift. This approach allows the Lift programming language to find a method in order to
has been developed in the past three, perhaps 

 Concurrent constraint programming in Oz for natural language processing
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D Duchier, C Gardent, J Niehren – Programming Systems Lab, , 1998 ,ns.ps.uni-sb.de
This software and its documentation are copyrighted by the German Research Center for
Artificial Intelligence (DFKI), the Swedish Institute of Computer Science (SICS), and other
parties. The following terms apply to all files associated with the software unless explicitly 

 A system for wizard of oz studies in natural language programming
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D Dahlstrom ,Bachelor’s Thesis, School of Computing, University , 2001 ,cseweb.ucsd.edu
1 Abstract In a Wizard of Oz study, subjects are intended to believe they are using software
when in fact there is a person—called the wizard—behind the scene playing the role of the
program. This paper describes a system designed for such a study where the program in 

Towards compatible and interderivable semantic specifications for the Scheme programming language, Part I: Denotational semantics, natural semantics, and abstract
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We derive two big-step abstract machines, a natural semantics, and the valuation function of
a denotational semantics based on the small-step abstract machine for Core Scheme
presented by Clinger at PLDI’98. Starting from a functional implementation of this small- 

 Querying biomedical ontologies in natural language using answer set programming
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H Erdogan, U Oztok, Y Erdem ,Proc. of SWAT4LS, 2010 ,webfiles.sabanciuniv.edu
Recent advances in health and life sciences have led to generation of a large amount of
data. To facilitate access to its desired parts, such a big mass of data has been represented
in structured forms, like biomedical ontologies. On the other hand, representing ontologies 

 Natural language as programming paradigm in data exploration domain
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Abstract. In this paper we present the progress of the natural language usage as the
programming paradigm for information extraction in distributed database environments.
Personal assistants form an environment where distributed knowledge is explored with 

Beyond exploratory programming: a methodology and environment for conceptual natural language processing
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P Johnson, W Lehnert ,AAAI, 1986 ,aaai.org
Abstract This paper presents an attempt to synthesize a methodology and environment
which has features both of traditional software development methodologies and exploratory
programming environments. The environment aids the development of conceptual natural 

 Natural Language Plurals in Logic Programming Queries
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MA Covington, AI Center ,Relation, 1996 ,ai1.ai.uga.edu
Abstract This paper presents a representation for natural language plurals in knowledge
base queries, implementing collective, distributive, cumulative, and multiply distributive
senses of the plural by means of higher predicates.

 Programming With Unrestricted Natural Language
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Abstract We argue it is better to program in a natural language such as English, instead of a
programming language like Java. A natural language interface for programming should
result in greater readability, as well as making possible a more intuitive way of writing 

 Declarative syntactic processing of natural language using concurrent constraintprogramming and probabilistic dependency modeling
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I Langkilde-Geary ,Proc. UCNLG, 2007
Abstract This paper describes a declarative approach to parsing and realization of natural
language using a probabilistic dependency model of syntax within a constrained
optimization framework. Such an approach is particularly well-suited for applications like 

 On the nature of natural language programming: generating transformation rules
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S Guberman, L Kuznetsov, W Wojtkowski ,afscet.asso.fr
Abstract In this paper we address the basic difference between the text written in a natural
language and the text written in a programming language, the natural programming
language. We ponder the rules of transforming a human-directed text written in a natural 

A Genetic Programming Experiment in Natural Language Grammar Engineering
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M Junczys-Dowmunt ,Text, Speech and Dialogue, 2012 ,Springer
This paper describes an experiment in grammar engineering for a shallow syntactic parser
using Genetic Programming and a treebank. The goal of the experiment is to improve the
Parseval score of a previously manually created seed grammar. We illustrate the 

 Ara_Pegasus: A new framework for programming using the Arabic natural language
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Abstract—This research paper presents a new framework for programming using the Arabic
natural language called Ara_pegasus. It accepts instructions written in Arabic natural
language as an input, and it executes the respective program accordingly. As reported, it 

 Natural Language Programming Using Class Sequential Rules
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Abstract This paper presents a system for Natural Language Programming using Class
Sequential Rules (CSR). The system recognizes a number of procedural primitives and
operators. The domain of the system is presently limited to the world of numbers and 

 Declarative Programming and Natural Language
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SJ Løvborg ,2007 ,imm.dtu.dk
The paper looks at data entry in existing declarative languages and the un- derlying relational
model is analyzed, also covering the subject of semantic networks. Context-free grammars are
described in the context of natural language parsing, and modified Earley parsing 

 Answering Complex Questions in Natural Language using Probabilistic Logic Programmingand the Web
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J Oramas, L De Raedt ,bnaic.gforge.uni.lu
Abstract We present an algorithm to answer complex questions in Natural Language that are
a boolean combination of simple questions. The main feature of this algorithm is to use a
probabilistic Prolog (ProbLog) to handle the uncertainty of answers obtained by 

3.15 Constrained Conditional Models: Integer Linear Programming Formulations for Natural Language Understanding
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Intelligent Information Access and Extraction suggest significant challenges for Natural
Language analysis. Tasks of interest include semantic role labeling (determining who did
what to whom, when and where), information extraction (identifying events, entities and 

Programming Spatial Algorithms in Natural Language
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Abstract We attempt programming spatial algorithms in natural language. The input of the
proposed system is a natural language description of a spatial processing algorithm, and the
output is the object-oriented program code to be compiled and executed.

Answer Set Programming via Controlled Natural Language Processing
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Controlled natural languages are subsets of natural languages that can be used to describe
a problem in a very precise way, furthermore they can often be translated automatically into
a formal notation. We investigate in this paper how a controlled natural language can be 

 Automatic Programming through Natural Language Compiler
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K Somasundaram, H Swaminathan ,weblidi.info.unlp.edu.ar
Abstract-The inherent ambiguity involved in understanding the natural language description
by a compiler is the greatest bane to the developers of an automated programming tool. Any
average programmer would assimilate a very good logic to solve a problem description 

 Natural Language Semantics on Logic Programming
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P Saint-Dizier, E Viegas ,Procesamiento de Lenguaje Natural, 1991 ,sepln.org
Very different goals, motivations and methods are at the origin of the development of the
three main trends in natural language semantics:-the logico-philosophical trend, mainly
oriented towards defining formal models,-the psycological trend, which carries out models 

 Natural Language of Application Domains versus Domain Specific ProgrammingLanguages
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C Bui, DE Curtis, T Rus ,cs.uiowa.edu
Abstract Research destined to make programming easier [SC98, Har08, May] and to enrich
computer application domains (ADs) with computational thinking developed by information
technology (IT)[Win06, TW07] are hot topics of today’s research. With the project on the 

 AUTOMATIC PROGRAMMING SYSTEM WITH ACCESS IN THE NATURAL LANGUAGE
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J Kazimierczak ,studiainformatica.ii.uph.edu.pl
Abstract. In this paper, acquisition of knowledge from user’s programs written in Pascal to the
knowledge base of the computer is introduced. It is shown that system with such a kind of
knowledge can be used as the automatic programming system. First, representation of 

 Logic Programming for Natural Language Processing
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MY Lee ,2006 ,tjhsst.edu
Abstract We propose a bifurcated paradigm for the construction of a Prolog knowledge base
from a body of documents: first, an information extraction (IE) application that will annotate
the corpus and output the annotated documents, and second, a Prolog knowledge base ( 




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