Information Retrieval Techniques Quiz

Introduction to Computer Science

• Computer Science is a discipline that builds a scientific foundation for various topics, including hardware and software.
• Hardware comprises the physical components of a computer system (e.g., case, monitor, keyboard, mouse, internal parts).
• Software, or software programs, are sets of instructions dictating computer tasks, encompassing applications and the operating system.
• Programming is the creation of executable computer programs that solve specific tasks.
• Networks connect multiple computers allowing resource sharing, primarily internet access.
• Graphics involve generating images through computers used in various applications (photography, film, gaming).
• Robots are programmable machines capable of performing complex actions automatically.
• Database is an organized collection of data designed for efficient search, retrieval, modification, and deletion.
• Security involves controls that ensure data confidentiality, integrity, and availability for software, hardware and firmware.
• Algorithm is a set of instructions to perform a specific task.

Breadth First Learning

• This course provides a basic introduction to many Computer Science subjects.
• It covers various concepts (e.g., search engines, history of computing, data storage, data manipulation, networking, algorithms, programming languages, software engineering, AI, impacts on society, document processing, spreadsheets, and database systems).
• Emphasis is on how computers function as a cohesive system.
• Data abstraction hides complex tasks.
• Data are organized in a hierarchy using various structures (arrays, lists, stacks, and queues)

Search Engines

• Search engines index web pages and retrieve relevant pages based on user input (queries).
• Popular ones include Google, Yahoo, and Bing.
• Queries are sets of words.
• Google interprets queries, returning relevant pages containing all terms.
• Several search techniques enhance accuracy (e.g., use of quotation marks for exact phrases, excluding terms using -, and using prefixes).

Searching Tricks

• Weather queries return location-specific weather data.
• Calculations can be performed directly within the search engine (e.g., multiplication, division).
• Currency conversions can be performed by including the target currency and desired amount.

Search Operators

• Social Media searches (e.g., "Fifa World cup @facebook").
• Price-based searches (e.g., "Laptop pkr 50000").
• Hashtags on social media (e.g., #education).
• Excluding terms (e.g., "Jaguar -cars").
• Exact phrase searches (“Tallest Building in Pakistan").
• Related websites searches (e.g., related:youtube.com).
• Cached version searches (e.g., cache:youtube.com).
• File type searches ("Virtual University" ext:pdf").

Advanced Search Operators

• intitle, allintitle: Query is included in title.
• inurl, allinurl: Query is included in URL.
• intext, allintext: Query is included in body text.
• AROUND(n): Query elements are separated by up to (n) words.

What not to search on the Internet

• Avoid potentially sensitive/dangerous subjects.
• Avoid cyber-security attacks and threats.
• Avoid searching information capable of causing personal anxiety or distress

Roots of Computing

• Abacus, widely used mechanical device in early calculations
• Gear technology was used in earlier models of calculating machines.
• Punch Cards played a significant role.
• Electronic numerical integrator and calculator (ENIAC) a highly significant stage of progress toward modern computers
• Factsheet of ENIAC, detailing its components and specifications.
• Rapid advancements that followed led to transistors, integrated circuits.

Bits

• The fundamental unit of information in computers, each representing a 0 or 1 state.
• Bits can represent numerous forms of data (numbers, text, images).
• Several bit units are combined (e.g., a byte is 8 bits).

Boolean Operations

• AND, OR, XOR: Boolean logic operations on bits (True/False) used in computer work.

Storing Bits

• Main Memory (RAM): Devices for storing data in computers.
• Byte size organization, bit significance
• Memory addresses, identifying unique locations.
• DRAM, SDRAM concepts
• Main memory Organization.

Magnetic Systems

• Mass storage devices (e.g., hard drives, CDs, DVDs, tapes).
• Zoned-bit recording and how it works
• Seek Time, Rotation Delay, and transfer rate concepts

Optical Systems

• Optical storage media (CDs, DVDs, and Blu-ray Disks).
• Data storage formats (spiral tracks, sectors)

Flash Drives

• Technology and advantages

Representing Text

• Character codes (ASCII, Unicode).
• Representing characters, symbols

Representing Numeric Values

• Binary notation: Representing numbers using 0s and 1s
• Two's complement and Floating point notation system
• Binary Representation and it's use

Representing Images

• Pixels: Fundamental unit for representing images
• Encoding methods (black & white, shades of gray, RGB)
• Brightness and Chrominance,
• Geometry and Image scaling
• Usage

Representing Sound

• Representing audio: Sound Amplitude and how it's encoded
• Sample Intervals.
• Alternative methods (e.g. MIDI)

Binary Notation

• Power method - converting decimal to binary and vice versa.
• Algorithm to convert decimal to binary

2's Complement Notation

• Representing Integer values, positive and negative

Excess Notation

• Integer Representation
• Representation and usage

Floating Point Notation

• Representing Fractional Numbers (with radix points)
• Components (sign, exponent, Mantissa)
• Truncation Errors

Data Compression

• Generic techniques, Lossy and Lossless

Compressing Images (GIF, JPEG, TIFF)

Compressing Audio and Video (MPEG, MP3)

Data Manipulation: CPU Basic

• CPU components (Arithmetic logic unit, Control unit, Register unit).
• General-purpose registers, special purpose registers
• The fetch, decode and execute model for using instructions in the CPU
• Steps for adding two values stored in memory (fetching, interpreting, executing)

Data Manipulation: Logic Operators

• Bitwise operations - AND, OR, and XOR, their usage, and related masking techniques
• Not operation - inverting bits

Data Manipulation: Rotation and Shift

• Using Bitwise operations to shift data within bit patterns

Data Manipulation: Arithmetic Operators

• Arithmetic operators for representing computation

Data Manipulation: Role of Controller

• Controller hardware (e.g. for printers, disks)
• Functions and advantages (eg DMA)
• Communication on a computer bus between controller and CPU

Data Manipulation: Direct Memory Access and Handshaking

• DMA, how it speeds up data retrieval
• Advantages of using DMA in computer operations

Data Manipulation: Communication media and communication rates

• Transmission,
• Parallel & Serial communication methods

Data Manipulation: Program Execution

• Fetching, decoding, and executing instructions
• Using registers, memory, & program counters
• Executing programs using the machine cycle

Data Management:Handling Competition Between Processes

• Importance of resources (hardware & software)
• Resource Allocation Issues

Data Management: Semaphores

• Controlling access to shared resources,
• Handling race conditions and preventing data corruption

Data Management: Deadlock

• Problems: When multiple programs block for resources
• Addressing Deadlocks: Preventing them or recovering from them, using techniques like deadlock detection.

Networking and the Internet: Network Classification

• Various network types (PAN, LAN, MAN, WAN)
• Open versus proprietary networks
• Network topologies (bus and star networks)

Networking and the Internet: Internet Architecture

• Hierarchy of ISPs (Tier 1, Tier 2, Tier 3)
• Role of ISPs; their services to various parties.
• Connection to end-user computers (“hosts”)

Networking and the Internet: Addressing

• Unique addresses (IP addresses)
• Dotted-decimal notation
• Domain names, DNS lookup

Networking and the Internet: Applications

• Email (SMTP, MIME, POP3, IMAP),
• VoIP (Voice over Internet Protocol)
• Streaming of multimedia content

Networking and the Internet: World Wide Web, HTML, and Web implementations

• HTML, a document format for describing web pages
• Client and Server roles
• URLs (Uniform Resource Locators)
• How URLs work, formats

Networking and the Internet: More on HTML

• HTML tags
• How different kinds of tags represent different components of a web page and their attributes

Networking and the Internet: XML

• Syntax and design of XML (eXtensible Markup Language)
• How it is used to create other forms of data representation (such as representing musical pieces)

Algorithm, an Informal Review

• Set of steps determining/describing a task
• Example of a simple algorithm to make a cup of tea

Algorithm: Formal Definition of Algorithm

• Ordered, unambiguous steps with a guaranteed termination for a given input

Algorithm: Abstract Nature of Algorithms

• Distinguishing between algorithms and their representations (abstract vs concrete)

Algorithm: Representation (Primitives)

• Primitives, components that form the basic building blocks of computation or programming, in machine languages.

Algorithm: Representation (Pseudocode)

• Pseudocode (a notational style) representing algorithms in a simpler structure than actual code.
• while and if blocks inside pseudo code expressions or statements

Algorithm: Representation (Pseudocode) While-Structure

• while loops (repeated execution of a set of statements as long as a given condition is true)

Algorithm: Representation (Pseudocode) Function-Structure

• Functions (or procedures): Reusable blocks of code or activity that can perform certain computations

Algorithm: Discovery (The Art of Problem Solving)

• Four steps to solving tasks: understanding the problem, creating a plan, executing the plan, evaluating the solution.

Algorithm: Algorithm Discovery Strategies

• Stepwise Refinement: Tackling complex tasks in smaller, more manageable subtasks.
• Using known algorithms for similar problems (analogous problem-solving)

Algorithm: Algorithm Efficiency

• Analyzing the efficiency of algorithms
• Comparing algorithms for performance in terms of time and/or space usage

Algorithm: Software Verification

• Validating that an algorithm or program behaves exactly as intended, finding and correcting errors

Software Engineering: Software Life Cycle

• Phases, steps of developing software: requirement analysis, design, implementation, testing, maintenance

Software Engineering: Requirement Analysis Phase

• Identifying user needs, goals of the software, and related constraints
• Software requirements specifications (SRS) that detail all requirements

Software Engineering: Design Phase

• Internal structure of a software system is determined and defined

Software Engineering: Implementation Phase

• Actual writing of the code for various software processes
• Programming, creating data files, and creating databases

Software Engineering: Testing Phase

• Testing for bugs and errors in the program (and other system artifacts)
• Methods such as glass-box testing, black-box testing
• Identifying error patterns, especially within modules

Software Engineering: Coupling

• Understanding intermodule coupling (how much interaction does one module of a program have with others, and how does that affect performance)
• Data coupling and Control Coupling: types of inter-module interactions
• Global data, which is available to all modules in the whole program, as opposed to local data. Global data can negatively impact modular design, flexibility, and potentially the quality of a software product.

Software Engineering: Cohesion

• Measures the relatedness or similarity of the components within a module.
• Logical cohesion signifies internally similar activities.
• Functional Cohesion focuses on a single function

Software Engineering: Information Hiding

• Keeping internal details of a module hidden from other modules, encouraging modular design and minimizing the negative impact of any later code changes or errors.

Software Engineering: Components

• Components as reusable program units or modules
• How components are constructed and used in large systems (e.g. smartphones, user interfaces, database systems).

Software Engineering: Design Patterns

• Methods for solving recurring design problems
• Examples: Adapter, Decorator

Software Engineering: Design Patterns Examples

• Examples of patterns (e.g., Factory, Shopping Cart) that demonstrate their use and applicability

Software Engineering Scope of Quality Assurance

• Defining quality in software
• Techniques or methods for evaluating the software (or related work products)
• Reviews, testing, and documentation

Software Engineering: Software Ownership and Liability

• Legal aspects of controlling the use of software
• Understanding Copyright, Patents, etc.
• Ensuring ownership and liability when sharing or using software created by others.

Database Systems: Role of Schema

• Database organization through schemas, specifying the structure of the database and the relationships between its various parts
• Separate schemas for different users help protect data

Database Systems: Database Management Systems (DBMS)

• Software-based systems that handle the complexity of accessing and maintaining database files, abstracting the interactions between users and the actual organization of data in a database system.
• Importance: data independence (users do not need to know how data is stored; DBMS hides that complexity)
• Advantages: data security

Database Systems: Relational Database model

• Representing data in tables

Database Systems: Issues of Relational Designs

• Problems with data redundancy and inconsistencies
• The necessity of splitting data across multiple tables to improve data efficiency, integrity, and organization

Database Systems: Select Operation

• Subsetting (or filtering) data via selecting parts of a database from a particular file

Database Systems: Project Operation

• Extracting columns of data (from one or many tables)

Database Systems: Join Operation

• Combining data from multiple related relations/tables

Database Systems: Sequential Files

• Recording data in order (files, records)
• Techniques used for finding specific records, how end-of-file is determined (EOF/Sentinel)

Database Systems: Indexed Files

• Arrangement of data to locate records quickly
• Lookup table (indexes): Linking keys to data location

Database Systems: Hash Files

• Using hashing algorithms to convert keys to storage locations

Database Systems: Data Mining

• Exploring datasets and identifying patterns
• Using data mining in many domains (e.g., marketing, medicine).

Database Systems: Data Mining Examples and Implications

• Various data-mining methods and real-world use cases.

Artificial Intelligence/Intelligent Agents

• Intelligent agents, their characteristics

Artificial Intelligence: Research Methodologies

• Simulating and designing for intelligent agents

Artificial Intelligence: Turing Test

• Benchmarking intelligent agents using a test to measure a potential machine's ability to exhibit human-like intelligence

Artificial Intelligence: Understanding Images

• Recognizing features in images for computer understanding
• Techniques and methods involved (e.g., edge enhancement, region finding, smoothing).

CS Impact on Society

• Both positive and negative impacts of computer science on various life aspects (communication, healthcare, education, business).

CS Impact on Health

• Positive and negative health impacts from the use of computers.

CS Impact on Environment

• Environmental impacts (e.g., consumption of paper, waste generation, energy use).

CS Impact: Ethical Issues

• Privacy in the digital world
• Digital property (copyright, ownership).
• Data gathering/tracking

CS Impact: Software Licenses and Information Privacy

• Licenses for using software, their legal aspects
• Software licenses, protecting intellectual property, considerations of liability.

CS Impact: Intellectual Property

• Patents and copyrights: Establishing ownership of intellectual property in general.

CS Impact: Security

• Protecting digital information,
• Threats from cybercrime
• Examples of security concerns, such as confidentiality, integrity, availability, and authentication

Test your knowledge on various information retrieval techniques and functionalities used in search engines. This quiz covers essential methods, operations, and features for effective searches, including handling numeric values and encoding methods for images. Challenge yourself and see how well you understand these concepts!