Natural Language Processing in Artificial Intelligence

Brojo Kishore Mishra, Raghvendra Kumar, Brojo Kishore Mishra, Raghvendra Kumar

• Publisher: Apple Academic Press
• Year: 2020
• Print ISBN: 9781771888653
• eBook ISBN: 9781000711691
• Edition: 1
• Topic: Biological Sciences
• Subtopic: Computer Science General
• Index: Biological Sciences

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.

CHAPTER 1

A Survey on Social Business Intelligence: A Case Study of Application of Dynamic Social Networks for Decision Making

SUBRATA PAUL,¹ CHANDAN KONER,² and ANIRBAN MITRA³

1 Research Scholar, MAKAUT, and Annex College, Kolkata, West Bengal, India, E-mail: [email protected]

2 Dr. B C Roy Engineering College, Durgapur, West Bengal, India

3 Amity University, Kolkata, West Bengal, India

ABSTRACT

Over the years, the popularity of social network platforms has increased alarmingly as they are castoff by people for expression of thoughts. Platforms are also used by firms for acknowledgment of numerous opportunities which would lead to the fulfillment of their objectives. The demand for information by firms brings out its fundamental inclinations and dependences that would largely affect performance of the firms. Business intelligence systems are used for obtaining these perceptions. The systems aimed in the derivation of actionable information from social media platforms for the provision of managerial decision-making are demonstrated as social business intelligence (SBI) systems. Numerous queries being raised ranging from ways firms process the external data, the management information derived from new data sources and successful implication of the SBI. In this chapter, we had presented a review of the entire process of business intelligence and then brought out insights on how this platform is used in order to undertake any decision by means of the social network. This work is purely a review paper.

1.1 INTRODUCTION

Social network enlightens the collection of associates amongst personages, where every personage is elaborated as a social entity. The assemblage of knots between communities with supremacy of those knots is established through social networks. Commencing the mathematical perspective, this social structure contains nodes of personages or organizations which are further narrated with distinct or compound-specific varieties of alliance regulations [1].

In addition, social networks can also have a dynamic behavior. Ties are assembled, which might flourish producing close association and silent liquefaction or unexpectedly revolve sour and perish further. Dynamic social networks might be fruitful in modeling and analysis of human associations in numerous possible circumstances including informal social relationship among personages surrounded by family or cluster of pals; the ordered alliance of employees in outsized endeavors; extensive correlations during social networking services; or conversion of activities of minute, interrelated terrorist cells [2].

Business intelligence can be described as a procedure of translation of data into information which would facilitate in managerial decision-making. Elbashir et al. [3] described that “business intelligence a system provides ability in analysis of the business information for the support and improvement of managerial decision making within a wide aspect of business activities.” Van Beek [4] has characterized business intelligence as “an uninterrupted procedure which will help organization to gather and register data, analyze it with subsequent application of resultant information and knowledge towards decision-making procedure for the improvement of organizational presentation.” Rouibah and Ould-Ali [5] further illustrated business intelligence as “a tactical approach for methodically boarding, pursuing, communication, and transformation of applicable pathetic indications hooked on actionable facts which formed the basis of premeditated decision-making.” Even though these explanations differ marginally, the related characteristics lies on the fact that business intelligence is supposed as a procedure of translation of data into interpretable information that will finally lead to managerial decision-making.

The performance of an organization should be measurement criteria for calculation of the effects of social media activities. In order to measure the performance of a firm against its strategy, there lies a requirement of key performance indicator which should be defined by the process of business intelligence. This value-based management method is commonly functional inside firms which will suggest when they will follow to accomplish social media happenings that would count the shortcomings of these happenings in comparison with the performance of organization. Prevailing social media monitoring tools primarily disclose organizational performance on social media wherein its constituent on a firm is granted as a discrete business unit accomplishing its specific approach. Although the persistence of business intelligence lies on the exposure of the essential parameters which determine the performance of an organization, it is merely dependent on the presentation of social media. For assisting the authority of social media content towards the performance of organization, there lies a necessity of links among the organization’s primary-performance indicators and clear social media constraints.

Frequently an argument is seen beneath potentials of social media towards business intelligence resolutions that influences supplementary amongst modules which are presently obtainable with social media methodical apparatus. Main assistances shall sum up every time a link is made between KPIs of organizations and their constraints which might be distinguished through social media apparatus. Within social business, intelligence there lays the social media happenings being associated with a firm which transforms in organizational presentation.

1.2 BUSINESS INTELLIGENCE PERSPECTIVES

Van Beek [4] pictures business intelligence (“BI”) as a cycle, comprising of three key procedures:

1. Register: BI cycle commences sensibly by listening-registration—to 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.
2. 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 ‘small BI cycle’ inside the procedure; statistics are collected, there is an analysis, assembling, and circulation till the correct administrative subdivisions.
3. 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 corporations’ dissimilarities in communications, ensuing in novel indications for the company’s BI cycle.

1.2.1 TYPOLOGY OF PERFORMANCE INDICATORS

Performance indicators consist of vital components in business intelligence, because of facts which they imitate the presentation of the happenings that subsidize to the firm’s strategy.

1. 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 ‘(value) drivers.’ Lagging indicators are the significances which amounts on productivity of historical happenings, besides recognized as ‘consequences’ [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

1. 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.
2. Key Performance Indicators: To distinguish amongst performance indicators that are more prime than others, some indicators are called ‘key-performance indicators’ (KPIs). According to Tsai and Cheng [7], KPIs are “the groundwork of the performance system which turns the strategic goals of a company into long-term objectives.” Along with the word ‘key,’ 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...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• About the Editors
• Contents
• Contributors
• Abbreviations
• Preface
• 1. A Survey on Social Business Intelligence: A Case Study of Application of Dynamic Social Networks for Decision Making
• 2. Critical Concepts and Techniques for Information Retrieval System
• 3. Futurity of Translation Algorithms for Neural Machine Translation (NMT) and Its Vision
• 4. Role of Machine Learning and Application Towards Information Retrieval in Cloud
• 5. Ontology-Based Information Retrieval and Matching in IoT Applications
• 6. Parts-of-Speech Tagging in NLP: Utility, Types, and Some Popular POS Taggers
• 7. Text Mining
• 8. A Brief Overview of Natural Language Processing and Artificial Intelligence
• 9. Use of Machine Learning and a Natural Language Processing Approach for Detecting Phishing Attacks
• 10. Role of Computational Intelligence in Natural Language Processing
• Index