What is involved in Natural-Language Understanding
Find out what the related areas are that Natural-Language Understanding connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Natural-Language Understanding thinking-frame.
How far is your company on its Natural-Language Understanding journey?
Take this short survey to gauge your organization’s progress toward Natural-Language Understanding leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.
To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.
Start the Checklist
Below you will find a quick checklist designed to help you think about which Natural-Language Understanding related domains to cover and 68 essential critical questions to check off in that domain.
The following domains are covered:
Natural-Language Understanding, American Association for Artificial Intelligence, Artificial intelligence, Attempto Controlled English, Augmented transition network, Computational semantics, Conceptual dependency theory, Deep linguistic processing, Discourse representation structure, Finite state automata, First order logic, Graphic user interface, Information extraction, Logical deduction, Naive semantics, Open Information Extraction, Part-of-speech tagging, Phrase structure rules, Predicate logic, Reading comprehension, SRI International, Speech recognition, Stochastic semantic analysis, Symantec Corporation, Wolfram Alpha:
Natural-Language Understanding Critical Criteria:
Categorize Natural-Language Understanding management and visualize why should people listen to you regarding Natural-Language Understanding.
– Consider your own Natural-Language Understanding project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?
– How do we go about Securing Natural-Language Understanding?
American Association for Artificial Intelligence Critical Criteria:
Revitalize American Association for Artificial Intelligence visions and give examples utilizing a core of simple American Association for Artificial Intelligence skills.
– What are your key performance measures or indicators and in-process measures for the control and improvement of your Natural-Language Understanding processes?
– What tools and technologies are needed for a custom Natural-Language Understanding project?
– Are there recognized Natural-Language Understanding problems?
Artificial intelligence Critical Criteria:
Distinguish Artificial intelligence adoptions and cater for concise Artificial intelligence education.
– When a Natural-Language Understanding manager recognizes a problem, what options are available?
– What are specific Natural-Language Understanding Rules to follow?
– Do we have past Natural-Language Understanding Successes?
Attempto Controlled English Critical Criteria:
Conceptualize Attempto Controlled English tasks and mentor Attempto Controlled English customer orientation.
– Do we monitor the Natural-Language Understanding decisions made and fine tune them as they evolve?
– What new services of functionality will be implemented next with Natural-Language Understanding ?
– How would one define Natural-Language Understanding leadership?
Augmented transition network Critical Criteria:
Incorporate Augmented transition network tactics and devote time assessing Augmented transition network and its risk.
– What will be the consequences to the business (financial, reputation etc) if Natural-Language Understanding does not go ahead or fails to deliver the objectives?
– How do we maintain Natural-Language Understandings Integrity?
Computational semantics Critical Criteria:
Probe Computational semantics tactics and correct Computational semantics management by competencies.
– What are the disruptive Natural-Language Understanding technologies that enable our organization to radically change our business processes?
– How can we incorporate support to ensure safe and effective use of Natural-Language Understanding into the services that we provide?
– How do we make it meaningful in connecting Natural-Language Understanding with what users do day-to-day?
Conceptual dependency theory Critical Criteria:
Deliberate over Conceptual dependency theory management and budget for Conceptual dependency theory challenges.
– Are accountability and ownership for Natural-Language Understanding clearly defined?
Deep linguistic processing Critical Criteria:
Analyze Deep linguistic processing engagements and visualize why should people listen to you regarding Deep linguistic processing.
– Do we cover the five essential competencies-Communication, Collaboration,Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new Natural-Language Understanding in a volatile global economy?
– What are the short and long-term Natural-Language Understanding goals?
Discourse representation structure Critical Criteria:
Participate in Discourse representation structure outcomes and devise Discourse representation structure key steps.
– Is there a Natural-Language Understanding Communication plan covering who needs to get what information when?
– How can skill-level changes improve Natural-Language Understanding?
Finite state automata Critical Criteria:
Communicate about Finite state automata visions and acquire concise Finite state automata education.
– Have you identified your Natural-Language Understanding key performance indicators?
– Are assumptions made in Natural-Language Understanding stated explicitly?
First order logic Critical Criteria:
Test First order logic adoptions and develop and take control of the First order logic initiative.
– What other organizational variables, such as reward systems or communication systems, affect the performance of this Natural-Language Understanding process?
– What are the usability implications of Natural-Language Understanding actions?
Graphic user interface Critical Criteria:
Judge Graphic user interface results and gather Graphic user interface models .
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Natural-Language Understanding?
– Does Natural-Language Understanding appropriately measure and monitor risk?
– How do we keep improving Natural-Language Understanding?
Information extraction Critical Criteria:
Contribute to Information extraction strategies and get answers.
– Do several people in different organizational units assist with the Natural-Language Understanding process?
– How will we insure seamless interoperability of Natural-Language Understanding moving forward?
Logical deduction Critical Criteria:
Derive from Logical deduction engagements and describe which business rules are needed as Logical deduction interface.
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Natural-Language Understanding services/products?
– What role does communication play in the success or failure of a Natural-Language Understanding project?
– What threat is Natural-Language Understanding addressing?
Naive semantics Critical Criteria:
Discourse Naive semantics decisions and reduce Naive semantics costs.
– Think about the kind of project structure that would be appropriate for your Natural-Language Understanding project. should it be formal and complex, or can it be less formal and relatively simple?
Open Information Extraction Critical Criteria:
Have a session on Open Information Extraction results and maintain Open Information Extraction for success.
– Think about the people you identified for your Natural-Language Understanding project and the project responsibilities you would assign to them. what kind of training do you think they would need to perform these responsibilities effectively?
– What potential environmental factors impact the Natural-Language Understanding effort?
Part-of-speech tagging Critical Criteria:
Face Part-of-speech tagging governance and triple focus on important concepts of Part-of-speech tagging relationship management.
– How do we ensure that implementations of Natural-Language Understanding products are done in a way that ensures safety?
– Who is the main stakeholder, with ultimate responsibility for driving Natural-Language Understanding forward?
– How do we go about Comparing Natural-Language Understanding approaches/solutions?
Phrase structure rules Critical Criteria:
Mix Phrase structure rules outcomes and visualize why should people listen to you regarding Phrase structure rules.
– Among the Natural-Language Understanding product and service cost to be estimated, which is considered hardest to estimate?
– Is the Natural-Language Understanding organization completing tasks effectively and efficiently?
Predicate logic Critical Criteria:
Accumulate Predicate logic management and handle a jump-start course to Predicate logic.
– At what point will vulnerability assessments be performed once Natural-Language Understanding is put into production (e.g., ongoing Risk Management after implementation)?
– Do Natural-Language Understanding rules make a reasonable demand on a users capabilities?
– Is Supporting Natural-Language Understanding documentation required?
Reading comprehension Critical Criteria:
Collaborate on Reading comprehension leadership and differentiate in coordinating Reading comprehension.
– Will Natural-Language Understanding have an impact on current business continuity, disaster recovery processes and/or infrastructure?
SRI International Critical Criteria:
Interpolate SRI International results and display thorough understanding of the SRI International process.
– What are your current levels and trends in key measures or indicators of Natural-Language Understanding product and process performance that are important to and directly serve your customers? how do these results compare with the performance of your competitors and other organizations with similar offerings?
– To what extent does management recognize Natural-Language Understanding as a tool to increase the results?
Speech recognition Critical Criteria:
Mine Speech recognition failures and describe which business rules are needed as Speech recognition interface.
– How do we measure improved Natural-Language Understanding service perception, and satisfaction?
– Who sets the Natural-Language Understanding standards?
Stochastic semantic analysis Critical Criteria:
Test Stochastic semantic analysis risks and interpret which customers can’t participate in Stochastic semantic analysis because they lack skills.
– Who are the people involved in developing and implementing Natural-Language Understanding?
Symantec Corporation Critical Criteria:
Concentrate on Symantec Corporation strategies and arbitrate Symantec Corporation techniques that enhance teamwork and productivity.
– How likely is the current Natural-Language Understanding plan to come in on schedule or on budget?
– Is a Natural-Language Understanding Team Work effort in place?
Wolfram Alpha Critical Criteria:
Inquire about Wolfram Alpha tasks and display thorough understanding of the Wolfram Alpha process.
– What are the barriers to increased Natural-Language Understanding production?
– What are the Key enablers to make this Natural-Language Understanding move?
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Natural-Language Understanding Self Assessment:
Author: Gerard Blokdijk
CEO at The Art of Service | http://theartofservice.com
Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.
To address the criteria in this checklist, these selected resources are provided for sources of further research and information:
Natural-Language Understanding External links:
Natural-Language Understanding – Gartner IT Glossary
American Association for Artificial Intelligence External links:
American Association for Artificial Intelligence …
Artificial intelligence External links:
Artificial Intelligence for B2B Sales | Collective[i]
RPA and Artificial Intelligence Summit 2017 – Official Site
Attempto Controlled English External links:
CiteSeerX — Attempto Controlled English (ACE
Augmented transition network External links:
Augmented transition network – How is Augmented …
[PDF]Augmented Transition Network as a Semantic Model …
Computational semantics External links:
Computational Semantics (June 1976 edition) | Open Library
computational semantics | ACL Member Portal
Conceptual dependency theory External links:
conceptual dependency theory – oi
[PDF]Conceptual Dependency Theory (CD), Schank 1975 …
Deep linguistic processing External links:
Deep linguistic processing
http://Deep linguistic processing is a natural language processing framework which draws on theoretical and descriptive linguistics. It models language predominantly by way of theoretical syntactic/semantic theory (e.g. CCG, HPSG, LFG, TAG, the Prague School).
Finite state automata External links:
[PPT]Finite State Automata: A Brief Introduction
Finite State Automata in Java – Programming Tutorials
[PDF]Section 12.5 Finite State Automata – math.drexel.edu
Graphic user interface External links:
Rite-Hite Door’s Graphic User Interface (GUI) – YouTube
Chroma – Graphic User Interface – YouTube
Information extraction External links:
[PDF]Title: Information Extraction from Muon …
http://Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents. In most of the cases this activity concerns processing human language texts by means of natural language processing (NLP).
[PDF]Information Extraction – CS 452 HOMEPAGE
Logical deduction External links:
Logical deduction puzzles (Book, 2006) [WorldCat.org]
Natural logical deduction – Encyclopedia of Mathematics
Logical Deduction Puzzles by George J. Summers
Open Information Extraction External links:
[PDF]MT/IE: Cross-lingual Open Information Extraction …
Ollie – Open Information Extraction Software
Part-of-speech tagging External links:
[PDF]Part-of-Speech Tagging – UMD Department of …
[1603.03144] Part-of-Speech Tagging for Historical English
“Part-of-Speech Tagging Guidelines for the Penn …
Phrase structure rules External links:
ERIC – TEACHER’S MANUAL FOR PHRASE STRUCTURE RULES …
[PDF]Phrase Structure Rules, Tree Rewriting, and …
[PDF]Phrase Structure Phrase Structure Rules
Predicate logic External links:
Predicate Logic Truth Trees – University of Houston
SEM122 – Predicate Logic I – YouTube
[PDF]Predicate logic – University of Pittsburgh
Reading comprehension External links:
FREE Reading Comprehension Worksheets
Reading Comprehension Worksheets – 2nd Grade
1st Grade Reading Comprehension Worksheets
SRI International External links:
SRI International – Official Site
Technology Solutions | SRI International
SRI International Conference Center – VLAB
Speech recognition External links:
eCareNotes – Speech Recognition Software
Speech API – Speech Recognition | Google Cloud Platform
Stochastic semantic analysis External links:
CiteSeerX — Stochastic Semantic Analysis PhD Study Report
What Is Stochastic Semantic Analysis? – Quora
Symantec Corporation External links:
Symantec Corporation (SYMC) After Hours Trading – NASDAQ.com
Symantec Corporation – SYMC – Stock Price Today – Zacks
Symantec Corporation – The Bellevue Collection
Wolfram Alpha External links:
Software Site Licensing: Wolfram Alpha Pro
Wolfram Alpha – Official Site