(8) ECT200_Ch08 Databases and Information Systems.pptx

The Era of Big Data: Databases, Information Systems, & Artificial Intelligence 8 Chapter © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, fo...

The Era of Big Data: Databases, Information Systems, & Artificial Intelligence 8 Chapter © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Chapter Topics UNIT8A: 8A:Files Files&&Databases Databases UNIT 8.1 8.1 8.2 8.2 8.3 8.3 8.4 8.4 Managing Files: Basic Concepts Managing Files: Basic Concepts Database Management Systems Database Management Systems Database Models Database Models Data Mining Data Mining UNIT8B: 8B:Big BigData, Data,Information InformationSystems, Systems,&& UNIT ArtificialIntelligence Intelligence Artificial 8.5 The Evolving World of Big Data 8.5 The Evolving World of Big Data 8.6 Artificial Intelligence 8.6 Artificial Intelligence 8.7 Artificial Life, the Turing Test, & the Singularity 8.7 Artificial Life, the Turing Test, & the Singularity 2 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e 8.1 Managing Files Basic Concepts 3 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Database Management Using Information Technology, 11e • In all information systems, data resources must be organized and structured in some logical manner so that they can be accessed easily, processed efficiently, retrieved quickly, and managed effectively. • A database is a logically organized collection of related data designed and built for a specific purpose. • Data is stored hierarchically for easier storage and retrieval. • File (table): collection of related records • Records (row): collections of related fields • Field (column): unit of data containing 1 or more characters • Character [Byte]: a letter number or special character made of bits • Bit: 0 or 1 4 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Logical Data Elements Using Information Technology, 11e • Data may be logically organized into: charac ter field record file databa se © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Logical Data Elements Charact er • A single alphabetic, numeric, or other symbol Field (data item) • Consists of a grouping of related characters. • Represents an attribute (characteristi c) of some entity (object, person, place, event) Record • Grouping of all the fields used to describe the attributes of an entity File (table, flat file) • Group of related records Databas e • Integrated collection of logically related data elements • It consolidates • Example… records payroll records previously with name, stored in SSN, pay rate separate files into a • Primary Key. common pool • Examples… of data salary, job elements that title © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, provides data forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e A key field (Primary key) is a field (or fields) in a record that holds unique data that identifies that record from all the other records in the table and in the database. • Often an identifying number, such as social security number or a student ID number. • Keys are used to sort records in different ways. • Primary keys must be unique make records distinguishable from one another. • Foreign keys appear in other tables and usually refer to primary keys in particular tables; they are used to relate one table to another (to cross-reference data). 7 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e 8.2 Database Management Systems 8 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Database Management System (DBMS): Set of programs which are used to define, construct and manipulate the database. Database + DBMS= Database Systems • DBMS benefits: • Reduced data redundancy (redundant data is stored in multiple places, which causes problems keeping all the copies current) • Speed—Modern DBMSs are much faster than manual data-organization systems and faster than older computer-based database arrangements • Improved data integrity—the data is accurate, consistent, and up to date • Timeliness—The speed and efficiency of DBMSs generally ensure that data can be supplied in a timely fashion—when people need it 9 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e • Ease of sharing—The data in a database belongs to and is shared, usually over a network, by an entire organization. The data is independent of the programs that process the data, and it is easy for nontechnical users to access it. • Ease of data maintenance—DBMS offers validation checks, backup utilities, and standard procedures for data inserting, updating, and deletion • Forecasting capabilities—DBMSs can hold massive amounts of data that can be manipulated, studied, and compared in order to forecast behaviors in markets and other areas that can affect sales and marketing managers’ decisions as well as the decisions of administrators of educational institutions, hospitals, and other organizations • Increased security—Although various departments may share data, access to specific information can be limited to selected users—called Authorization Control. 10 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e 3 Principal Database Components • Data Dictionary • Repository that stores the data definitions and descriptions of the structure of the data and the database • DBMS Utilities • Programs that allow you to maintain the database by creating, editing, deleting data, records, and files • Also include automated backup and recovery • Report Generator • Program for producing on-screen or printed readable documents from all or part of a database 11 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Data Dictionary © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Report Generator © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Database Administrator (DBA) • Coordinates all related activities and needs for an organization’s database • Ensures the database’s: • • • • • • Recoverability Integrity Security Availability Reliability Performance 14 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Database Development Using Information Technology, 11e • Developing a large DB of complex data types can be a complicated task. • DBA and the database Design Analyst work with end users and system analysts to model the business processes and the data they require. Then they determine: • What Data Definitions should be included in the DB. • What Relationships should exist among the data elements. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e 8.3 Database Models 16 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Database Models • Database management system (DBMS) packages are designed to use a specific data structure to provide end users with quick, easy access to information stored in databases. • Five fundamental database structures: • Hierarchical , Network , Relational, Object-Oriented and Multidimensional Models. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Hierarchical Database • Fields or records are arranged in related groups resembling • • • • • a family tree with child (low-level) records subordinate to parent (high-level) records Root record is the parent record at the top of the database, and data is accessed top-down, through the hierarchy Oldest and simplest; used in mainframes in 1970s Is rigid in structure and difficult to update Records arranged in a hierarchy or tree-like structure Relationships are one-to-many 18 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Hierarchical Database 19 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Hierarchical Database 20 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Network Database: created to represent a more complex data relationship effectively, improve database performance, and impose a database standard. • Similar to a hierarchical database but more flexible-- each child record can have more than one parent record • Requires the database structure to be defined in advance; flexibility still lacking. 21 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Network Database 22 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Common Database Structures: Relational • Most widely used structure • Data elements are stored in tables (sometimes referred to as relations). • Row represents a record; column is a field. • DBMS packages based on relational model can relate data in one table with data in another, if both tables share a common data element. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e • Relational Database: grew out of the hierarchical and network database models • More flexible than previous models; built with SQL • Mainframe relational DB applications: • Oracle10g from Oracle • DB2 from IBM • Midrange DB applications: • SQL Server from Microsoft. • Examples for microcomputers are Paradox and Microsoft Access • Users don’t need to know data structure to use the database 24 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Relational Databases SQL is a database computer language designed for the retrieval and management of data in a relational database. SQL stands for Structured Query Language. Users employ SQL (structured query language) to create, modify, maintain, and query the database Applications of SQL: • Allows users to access data in the relational database management systems. • Allows users to describe the data. • Allows users to define the data in a database and manipulate that data. • Allows users to create and drop databases and tables. • Allows users to create view and set permissions on the table © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Object-Oriented Database • The object-oriented model is considered one of the key technologies of a new generation of multimedia Web-based applications. • An object consists of • Data values describing the attributes of an entity • Operations that can be performed on the data • Encapsulation Combine data and operations • Inheritance  New objects can be created by replicating some or all of the characteristics of parent objects • OODBMS now is popular in CAD and in multimedia Web-based applications. • Supports complex data types more efficiently than relational databases • Examples: graphic images, video clips, web pages © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Object-Oriented Using Information Technology, 11e Database • Major relational DBMS vendors add object-oriented modules to their relational software. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Multidimensional Database • Models data as facts, dimensions, or numerical answers for use in the interactive analysis of large amounts of data for decision-making purposes.. • Allows users to ask questions in colloquial language. • Use OLAP* (Online Analytical Processing) software to provide answers to complex database queries. *OLAP (online analytical processing) is a computing method that enables users to easily and selectively extract and query data in order to analyse it from different points of view. 28 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Multidimensional Database Using Information Technology, 11e • Variation of relational model that uses multidimensional structures to organize data relationships between them. and express the • Data elements are viewed as being in cubes. Each side of the cube is considered a dimension of the data. • Each dimension represent a different category. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Multidimensional Database 2- Dimensional data Data © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Multidimensional Database 3 - Dimensional data Data © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Brief Database Model Overview Database Type Description Hierarchical database Fields or records are arranged in a family tree, with child records subordinate to parent or higher-level records Network database Like a hierarchical database, but each child record can have more than one parent record Relational database Relates, or connects, data in different files (tables) through the use of a key, or common data element Object-oriented database Uses objects (software written in small, reusable chunks) as elements within database files; multimedia Multidimensional database Models data as facts, dimensions, or numerical measures for use in the interactive analysis of large amounts of data 33 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e 8.4 Data Mining 34 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Data mining is the computer-assisted process of sifting through and analyzing vast amounts of data to extract hidden patterns and meaning and to discover new knowledge. • Transforms Information into Knowledge. • Data is fed into a data warehouse through the following steps: 1. Identify and connect to data sources 2. Perform data fusion and data cleansing 3. Obtain both data and metadata (data about the data) 4. Transport data and metadata to the data warehouse • Data warehouse is a special database of cleaned-up data and metadata. 35 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Data Mining 36 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Methods for searching for patterns in the data and interpreting the results • Regression analysis • Develops mathematical formula to fit patterns in the data that has been extracted • Formula is then applied to other data sets of the same type to predict future trends • Classification analysis • Statistical pattern-recognition process that is applied to data sets with more than just numerical data 37 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Regression Analysis 1. A regression problem is when the output variable is a real or continuous value. We have a Housing data set and we want to predict the price of the house. The red line indicates the best fit line for predicting the price. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Classification Analysis • A classification problem is when the output variable is a category. Using Information Technology, 11e Example: Predicting if the loan should be approved or not © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e UNIT 8B: Big Data and Artificial Intelligence • Big Data aims to tap all the web data and other data that is outside corporate databases. • Big Data typically means applying the tools of Artificial Intelligence to vast new sources of data beyond that captured in standard databases. • The new data sources include web-browsing data trails, social network communications, sensor data, and surveillance data. 40 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e 8.5 The Evolving World of Big Data 41 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e BIG DATA COMPANIES TO KNOW •IBM •Salesforce •Alteryx •Cloudera •Crunchbase •Google •Oracle •VMware •Unacast •Databricks © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Three Implications of Big Data: 1. Big Data derives from a bundle of old & new data sources, • both old and new— To make sense of the oceans of data, there is advanced computer processing and storage plus complex software taken from the evolving world of artificial intelligence. The software applies Big Data Analytics -- the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. A specific kind of analytics is Web analytics, the measurement and analysis of Internet data to understand web usage. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e 2. Big data could lead to a revolution in measurement: The volume and variety of data, along with the powerful smart software, could revolutionize how things are measured. —just as the invention of the telescope opened up the heavens and the microscope unveiled the mysteries of biological life down to the cellular level. In business management, for example, new kinds of measurement could replace old ideas, organizations, and ways of thinking about the world. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e 3. Big data could lead to better decision making: Not only can data-driven insights be used to make sense of incredibly complex situations. Big Data “can help compensate for our overconfidence in our own intuitions and can help reduce the extent to which our desires distort our perceptions.” In short, Big Data is a term for a process that has the potential to transform everything. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Uses of Big Data: • Big Data is finding major uses in: • Medical research, • • • • • Marketing, Politics, Entertainment Use demand prediction for ridesharing companies Discovering consumer shopping habbits © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e 8.7 Artificial Intelligence 49 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Artificial intelligence is the branch of computer science concerned with making computers behave like humans. • Attempts to mimic human intelligence through logic and symbol manipulation, as well as statistics. • This branch of AI is based on machine learning, which is the development of techniques that allow a computer to simulate learning by generating rules from raw data fed into it. • Expert systems, for example, make heavy use of this kind of AI. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e AI Areas include: • • • • • • Expert systems Natural language processing Pattern recognition Robotics Fuzzy logic And many more 51 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Expert Systems • Built by knowledge engineers • Include surface knowledge and deep knowledge • Three components of an expert system: • Knowledge base: an expert system’s database of knowledge about a particular subject • Inference engine: the software that controls the search of the expert system’s knowledge base and produces conclusions • User interface: the display screen for the user to interact with the expert system 52 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Expert Systems: Examples Examples: There are many examples of expert system. Some of them are given below: • MYCIN: One of the earliest expert systems based on backward chaining. It can identify various bacteria that can cause severe infections and can also recommend drugs based on the person’s weight. • DENDRAL: It was an artificial intelligence based expert system used for chemical analysis. It used a substance’s spectrographic data to predict it’s molecular structure. • PXDES: It could easily determine the type and the degree of lung cancer in a patient based on the data. • CaDet: It is a clinical support system that could identify cancer in its early stages in patients. • DXplain: It was also a clinical support system that could suggest a variety of diseases based on the findings of the doctor. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Expert System 54 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Natural language processing • Allows users to interact with a system using normal language • The study of ways for computers to recognize and understand human language • • • • • • Spell check. Autocomplete. Voice text messaging. Spam filters. Related keywords on search engines. Siri, Alexa, or Google Assistant. 55 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Robotics • The development and study of machines that can perform actions that are normally done by people • Robots grouped by locomotion system: grouped according to their means of locomotion, which defines their shape. Thus, there are stationary, wheeled, legged, swimming, flying, rolling, swarm, modular, micro, nano, soft elastic, snake, and crawler robots (includes drones). • Robots grouped by application: grouped according to the application they are supposed to perform, so that shape is not important. Thus, in health and medicine, there are wearable machines to help amputees walk, wheeled robots (medi-bots) that roam hospital halls and make visits to patients on behalf of their doctors, and robots used in surgery that perform actual operations. 56 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Fuzzy logic • A method of dealing with imprecise data and uncertainty, with problems that have many answers rather than one • The conventional logic block that a computer can understand takes precise input and produces a definite output as TRUE or FALSE, which is equivalent to human’s YES or NO. • Fuzzy Logic (FL) is a method of reasoning that resembles human reasoning. The approach of FL imitates the way of decision making in humans that involves all intermediate possibilities between digital values YES and NO. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Ethics in A.I. • Ethics underlies everything having to do with AI. • Computer software is subtly shaped by the ethical judgments and assumptions of its creators; there is no human-values-free / bias-free software. • Safety • Responsibility • Privacy • Will AI cause humans to lose control of computer systems? 59 © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part. Using Information Technology, 11e Databases: Concerns about Privacy & Identity Theft • Databases have facilitated loss of privacy and identity theft, which have become significant concerns for many people. © 2015 by McGraw-Hill Education. This proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part.