Concepts and implementations of natural language query systems

Cover of: Concepts and implementations of natural language query systems |

Published by Computer Science Dept., University of Southwestern Louisiana, For sale by the National Technical Information Service in Lafayette, La, [Springfield, Va .

Written in English

Read online


  • Natural language processing (Computer science),
  • Information storage and retrieval systems.

Edition Notes

Book details

StatementI-Hsiung Liu.
SeriesNASA-CR -- 184514., USL/DBMS NASA/RECON working paper series report -- no. DBMS.NASA/RECON-6., NASA contractor report -- NASA CR-184514.
ContributionsUnited States. National Aeronautics and Space Administration.
The Physical Object
Pagination1 v.
ID Numbers
Open LibraryOL15282288M

Download Concepts and implementations of natural language query systems

Get this from a library. Concepts and implementations of natural language query systems. [I-Hsiung Liu; United States. National Aeronautics and Space Administration.]. These interfaces commonly ignore potentially the largest user group, i.e., casual users.

This project discusses the concepts and implementations of a natural query language system which satisfy the nature and information needs of casual users by allowing them to communicate with the system in the form of their native (natural) : Wayne D.

Dominick and I-Hsiung Liu. These interfaces commonly ignore potentially the largest user group, i.e., casual users. This project discusses the concepts and implementations of a natural query language system which satisfy the nature and information needs of casual users by allowing them to communicate with the system in the form of their native (natural) language.

CONCEPTS OF NATURAL LANGUAGE QUERY SYSTEMS The primary objective of a natural language query system is to permit casual users to engage in effective comnunication with a formatted database system by applying their native language. To develop such a query system, it is necessary to understand the.

Natural Language Queries - Oracle. lem, we present a hybrid natural language query recommendation framework that combines natural language generation with query retrieval. When re-ceiving a problematic user query, our system dy-namically recommends valid queries that are most relevant to the current user request so that the user can revise his request accordingly.

Compared with. Natural Language Queries A natural language query consists only of normal terms in the user’s language, without any special syntax or format. ATG Search allows a user to enter terms in any form, including a statement, a question, or a simple list of keywords. the information that is being sought from a natural language style query.

Bytesting the system on a small sample of user queries, Liddy et al found that 95% of the new user queries could be covered and covered accurately by their system. NLP-SIR System Overview When the concept of a natural language interface to spreadsheets was first.

we evaluate this system on the precision and the run-time of answering the Vietnamese questions. Keywords: Natural Language Processing, Document Retrieval, Search, Question Answering, Knowledge Base.

Introduction The necessary of buiding the searching system being able to support users expressing their searching by natural languageCited by: 7. By this, we present an architecture that combines the rich features of html, Natural Language (NL) with Query-By-Form (QBF) method and MySQL to enable our proposed system accept user queries in.

In natural language processing, the work has been done in different directions (such as text, speech). In this book, the NLIDB for English/Urdu and similar languages has been covered. The book presents a column-value or attribute-value mapping algorithm that optimizes the transformation of a natural language query to SQL, hence improves the Reviews: 1.

The user of this e-book is prohibited to reuse, retain, copy, distribute or republish 9. Natural Language Processing — Natural Language Inception Natural Language Tools along with more operational and commercial systems, e.g.

for database query. This paper is an introduction to natural language interfaces to databases (NLIDBS). A brief overview of the history of NLIDBS is first given. Some advantages and disadvantages of NLIDBS are then discussed, comparing NLIDBS to formal query languages, form Cited by:   14 Excellent Free Books to Learn Prolog.

for understanding elementary computational linguistics and as tools for implementing the basic components of natural-language-processing systems. Language Analysis is to provide a working understanding of basic computational linguistic and logic programming concepts.

Throughout this book, the. A Natural Language Query Interface to Structured Information 3 2 Context Tools for accessing data contained in ontologies and knowledge bases are not new, several have been implemented before using di erent design approaches which reach various levels of expressivity and user-friendliness.

I'm curious about natural language querying. Stanford has what looks to be a strong set of software for processing natural language.I've also seen the Apache OpenNLP library, and the General Architecture for Text Engineering. There are an incredible amount of uses for natural language processing and that makes the documentation of these projects difficult to quickly absorb.

Natural language processing (NLP) can be dened as the automatic (or semi-automatic) processing of human language. The term ‘NLP’ is sometimes used rather more narrowly than that, often excluding information retrieval and sometimes even excluding machine translation.

NLP is sometimes contrasted with ‘computational linguistics’, with NLP. UsingNaturalLanguagefor DatabaseQueries NaturalLanguage Processing is described, together with a small naturallanguage front-end processor called NBASE. The requirements and goals ofa natural language system along with existing alternatives, are discussed.

The necessity ofpreprocessing a knowledge base andtheimplementationofJPREP,apreprocessinginterfacetoNBASE, is presented. Lexi. This is a hands-on, practical course on getting started with Natural Language Processing and learning key concepts while coding. No guesswork required. Throughout the book you'll get to touch some of the most important and practical areas of Natural Language Processing.

Everything you. Handbook of Natural Language Processing: “The Second Edition presents practical tools and techniques for implementing natural language processing in computer systems.

Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.”. It is very evident that natural language includes an abundance of vague and indefinite phrases and statements that correspond to imprecision in the underlying cognitive concepts.

Terms such as 'tall,' 'short,' 'hot,' and 'well' are extremely difficult to translate into knowledge representation, as required for the reasoning systems under Author: Richard Nordquist. Natural Language Processing1 INTRODUCTION Natural Language Processing (NLP) is the computerized approach to analyzing text that is based on both a set of theories and a set of technologies.

And, being a very active area of research and development, there is. Probably Chris Date's work is where you'd want to start if you want to get deep into the theory of it all.

If you're just looking for basic design, reading wikipedia is enough to get you 80% of the way there IF you follow the rules pretty strictl. The flip side of natural language querying on the front end lies in applying natural language processing techniques to make sense of unstructured data.

"NLP makes sense of that unstructured data, making it organized, queryable and searchable," said Stephen Blum, founder and CTO of PubNub, a data management API : George Lawton. to a database query language. Implementing natural language inter-faces for databases that can map user utterances to a query language can thus be challenging.

The grammar rules underlying their syntax must be coerced into Chomsky Normal Form [9] to be available for standard natural language parsing techniques. While statistical andFile Size: KB. Step 4: create vector representation for Bag_of_words, and create the similarity matrix. The recommender model can only read and compare a vector (matrix) with another, so we need to convert the ‘Bag_of_words’ into vector representation using CountVectorizer, which is a simple frequency counter for each word in the ‘Bag_of_words’ I have the matrix containing the count for.

I bought this book's Kindle Edition for only $5. Interestingly, this was one of the most expensive items in the series. I am glad to have taken this short (page) book for a perusal. It reviewed some of my prior knowledge about Natural Language Processing (NLP) as /5. The Structured Query Language (SQL) norms are been pursued in almost all languages for relational database systems.

However, not everybody is able to write SQL queries as they may not be aware of. Key Concepts: Terms in this set (30) In which information system would the data element "principal procedure" be found.

was typed into the system: "how many patients were discharged on November, 12 ?" this is an example of what type of query query by example natural language query data manipulation query structured query language.

Today’s natural language processing (NLP) systems can do some amazing things, including enabling the transformation of unstructured data into structured numerical and/or categorical data. Why is this important. Because once the key information has been identified or a key pattern modeled, the newly created, structured data can be used in predictive models or visualized to explain.

Benefits of Natural Language Query Easier for users to interact with. No need to learn complex query forms or keyword syntax; Information is found faster, with better accuracy.

Users are able to provide more specifics and detail when composing their query, allowing faster response and higher quality results. Natural Language Computing (NLC) Group is focusing its efforts on machine translation, question-answering, chat-bot and language gaming.

Since it was foundedthis group has worked with partners on significant innovations including IME, Chinese couplets, Bing Dictionary, Bing Translator, Spoken Translator, search engine, sign language translation, and most recently on Xiaoice, Rinna.

Edward Loper's book is an introduction to the Natural Language Toolkit (NLTK) for the Python programming language. concepts or try a few calculations or code segments. This book's questions go far beyond the norm. They introduce new concepts, encourage writing and comparing several versions of a program, and otherwise extend each chapter's 4/5(52).

Here, dep(x, y) is a dependency that exists between words x and words of a sentence compose the constants of a domain over which the functions operate.

The rules in and apply in a non relation query (see Section for definition of a relational and non-relational query). They basically identify the nominal subjects in the user submitted query and flags them as : Peter Ochieng.

Particular topics vary. Possible topics include information retrieval/extraction, natural language query systems, dialogue systems, augmentative and alternative communications, computer-assisted language learning, language documentation, spell/grammar checking, and software localization.

Prerequisite: LINGLINGLING Examples. Examples include: Atomese, the graph query language for the OpenCog graph database, the AtomSpace.

Attempto Controlled English is a query language that is also a controlled natural language. AQL is a query language for the ArangoDB native multi-model database system.

Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national.

FREyA is a Natural Language Interface which can be used to query ontologies in RDF/OWL format. It maps Natural Language Query such as 'what is the capital of England?' to SPARQL - which then when executed against an RDF/OWL repository returns an answer. A relational database is a digital database based on the relational model of data, as proposed by E.

Codd in A software system used to maintain relational databases is a relational database management system. Many relational database systems have an option of using the SQL for querying and maintaining the database. Is there a good natural language processing library [closed] Ask Question although I don't know whether there are any readily available Java implementations (and maybe that's too big of a gun for your problem anyway:) Natural language query processing libraries.

Failed to load the JNI shared Library (JDK). If the old and new systems are operated side by side until the new system has proven itself, this type of system conversion plan is parallel implementation. True If a company stops using the old system all at once and then starts using the new system, this is called direct implementation.Natural Language Understanding in Prolog Because of its declarative semantics, built-in search, and pattern matching, Prolog provides an important tool for programs that process natural language.

Indeed, natural language understanding was one of Prolog’s earliest applications.Grant Ingersoll - Grant is the CTO and co-founder of Lucidworks, co-author of “Taming Text” from Manning Publications, co-founder of Apache Mahout and a long-standing committer on the Apache Lucene and Solr open source ’s experience includes engineering a variety of search, question answering and natural language processing applications for a variety of domains and .

18275 views Thursday, November 12, 2020