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Natural Language Processing in Artificial Intelligence
Brojo Kishore Mishra, Raghvendra Kumar, Brojo Kishore Mishra, Raghvendra Kumar
- 278 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Natural Language Processing in Artificial Intelligence
Brojo Kishore Mishra, Raghvendra Kumar, Brojo Kishore Mishra, Raghvendra Kumar
About This Book
This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages.
Key features:
- Addresses the functional frameworks and workflow that are trending in NLP and AI
- Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI
- Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world
- Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.
Frequently asked questions
Information
CHAPTER 1
ABSTRACT
1.1 INTRODUCTION
1.2 BUSINESS INTELLIGENCE PERSPECTIVES
- Register: BI cycle commences sensibly by listening-registrationâto environment. Surrounded by environments, dissimilarity is prepared amongst circumstantial besides transactional environments which comprises of features which has effects on the organization and actors having a straight association with company, comparable to customers, suppliers, employees, and competitors respectively.
- Process: Accordingly, when data (in whatever format) is registered, there lies a requirement for its processing enabling the assembled statistics discloses tendencies with the delivery of valued facts. Van Beek [4] sites âsmall BI cycleâ inside the procedure; statistics are collected, there is an analysis, assembling, and circulation till the correct administrative subdivisions.
- React: Subsequently, after dispensation of statistics, the corporation is able in reacting. Van Beek [4] contends that a corporation might respond on three stages; functioning, strategic or intentional. Accordingly, the atmosphere assesses the corporationsâ dissimilarities in communications, ensuing in novel indications for the companyâs BI cycle.
1.2.1 TYPOLOGY OF PERFORMANCE INDICATORS
- Leading and Lagging Indicators: There are dualistic important categories of indicators; leading indicators and lagging indicators. Leading indicators principals to outcomes which in addition are marked as â(value) drivers.â Lagging indicators are the significances which amounts on productivity of historical happenings, besides recognized as âconsequencesâ [6]. Leading indicators deal with the management, while lagging indicators provide a measurement on the intensity of management. With leading indicators, there lies a possibility of direct response during the arousal of low outcomes [6].Illustratively, Table 1.1 illustrates a few scenarios of leading and lagging indicators.
TABLE 1.1 Illustrations of Leading and Lagging Indicators [6] Leading Indicators Lagging Indicators
Pioneering sales currently Proceeds Considered rearticulate currently Price Customer possessions currently uncovered Capability Documented software pollutions Customer consummation Worker conservation Restrictions Trustworthiness
- Quantitative and Qualitative Indicators: Another distinction between metrics is the difference between quantitative or qualitative based indicators. The quantitative indicator uses counting, adding, and averaging, etc. for counting processes. Examples of quantitative measures are inventories, number of orders, number of clients, the delivery time of goods, sales, other financial figures, etc. In comparison to qualitative indicators, quantitative indicators are relatively easy to measure.
- Key Performance Indicators: To distinguish amongst performance indicators that are more prime than others, some indicators are called âkey-performance indicatorsâ (KPIs). According to Tsai and Cheng [7], KPIs are âthe groundwork of the performance system which turns the strategic goals of a company into long-term objectives.â Along with the word âkey,â a performance indicator provides an indication of being more attentive. Table 1.2 lists the constituents which a key-performance indicator should fulfill, namely specific, measurable, attainable, realistic, and time-sensitive (SMART) [8].
TABLE 1.2 Requirements of a Key-Performance Indicator [8] Re...