Information Retrieval Systems
(JNTU)
 

UNIT-1 (PDF)
Introduction to Information Retrieval Systems

UNIT-2 (PDF)
UNIT-3 (PDF)
Automatic Indexing: 
Classes of Automatic Indexing
Statistical Indexing - Probabilistic Weighting, Vector Weighting, Bayesian Model
Natural Language
Concept Indexing
Hypertext Linkages 
Document and Term Clustering: 
Introduction to Clustering
Thesaurus Generation
Item Clustering
Hierarchy of Clusters

UNIT-4 (PDF)
User Search Techniques: Search Statements and Binding
Similarity Measures and Ranking
Relevance Feedback
Selective Dissemination of Information Search
Weighted Searches of Boolean Systems 
Searching the INTERNET and Hypertext 
Information Visualization: Introduction to Information Visualization
Cognition and Perception
Information Visualization Technologies 

UNIT-5 (PDF)
Text Search Algorithms: Introduction to Text Search Techniques
Software Text Search Algorithms
Hardware Text Search Systems 
Multimedia Information Retrieval: Spoken Language Audio Retrieval
Non-Speech Audio Retrieval
Graph Retrieval
Imagery Retrieval, Video Retrieval

2 comments:

Data Analytics

Data Analytics
(JNTUH)

UNIT - I Data Management: (UNIT-1 PDF)
1.1 Design Data Architecture
1.2 Understand various sources of Data
1.3 Data Quality
1.4 Preprocessing

UNIT - II Data Analytics: (UNIT-2 PDF)
2.1 Introduction to Analytics
2.2 Introduction to Tools and Environment
2.3 Application of Modeling in Business
2.4 Databases & Types of Data and variables
2.5 Data Modeling Techniques Overview
2.6 Missing Imputations

UNIT - III: (UNIT-3 PDF)
Regression:
3.1 Concepts
3.2 Blue property assumptions
3.3 Least Square Estimation
Logistic Regression: 
3.5 Model Theory
3.6 Model fit Statistics
3.7 Model Construction
3.8 Analytics applications to various Business Domains etc.

UNIT-IV (UNIT-4 PDF)
Object Segmentation: 
4.1 Regression Vs Segmentation
4.2 Supervised and Unsupervised Learning
4.3 Tree Building
Time Series Methods: 
4.4 Arima
4.5 Measures of Forecast Accuracy 
4.5 Measures of Forecast Accuracy (Another version)
4.6 ETL approach

UNIT - V Data Visualization: (UNIT-5 PDF)
5.1 Pixel-Oriented Visualization Techniques
5.2 Geometric Projection Visualization Techniques
5.3 Icon-Based Visualization Techniques
5.4 Hierarchical Visualization Techniques
5.5 Visualizing Complex Data and Relations
PPT UNIT V - another version




2 comments:

Design Patterns

As per JNTUH syllabus

 Text Book PDF

 Unit 1 pdf
Unit 2 pdf
Unit 3 pdf
Unit 4 pdf
Unit 5 pdf

 UNIT-1- INTRODUCTION
1.1 What Is a Design Pattern?
1.2 Design Patterns in Smalltalk MVC
1.3 Describing Design Patterns
1.4 The Catalog of Design Patterns
1.5 Organizing the Catalog
1.6 How Design Patterns Solve Design Problems
1.7 How to Select a Design Pattern
1.8 How to Use a Design Pattern

 UNIT-2 
A CASE STUDY: DESIGNING A DOCUMENT EDITOR
2.1 Design Problems
2.2 Document Structure
2.3 Formatting
2.4 Embellishing the User Interface
2.5 Supporting Multiple Look-and-Feel Standards
2.6 Supporting Multiple Window Systems
2.7 User Operations
2..8 Spelling Checking and Hyphenation
CREATIONAL PATTERNS:
2.9  Abstract Factory
2.10 Builder
2.11 Factory Method
2.12 Prototype
2.13 Singleton
2.14 Discussion on Creational Patterns

 UNIT-3 
STRUCTURAL PATTERN PART-I: 
3.1 Adapter
3.2 Bridge
3.3 Composite
STRUCTURAL PATTERN PART-II: 
3.4 Decorator
3.5 Façade
3.6 Flyweight
3.7 Proxy

 UNIT-4
BEHAVIORAL PATTERNS PART-I 
4.1 Chain of Responsibility
4.2 Command
4.3 Interpreter
BEHAVIORAL PATTERNS PART-II 
4.4 Iterator
4.5 Mediator
4.6 Memento
4.7 Observer

 UNIT-5
BEHAVIORAL PATTERNS PART-III
5.1 State
5.2 Strategy
5.3 Template Method
5.4 Visitor

 5.5 Discussion of Behavioral Patterns
5.6 What to Expect from Design Patterns
5.7 A Brief History
5.8 The Pattern Community
5.9 An Invitation
5.10 A Parting Thought

 SAMPLE QUESTION PAPERS
1
2



11 comments:

Distributed Systems

As per JNTUH

Chapter-wise
1.1 Introduction
1.6 Fundamental Model

2.1 Clocks, Events and Process States
2.2 Synchronizing physical clocks
2.3 Logical time & logical clocks
2.4 Global states
2.5 Coordination and Agreement Intro
2.6 Mutual Exclusion
2.7 Elections
2.8 Multicast communication
2.9 Consensus

3.1 Introduction to IPC
3.2 The API for the Internet protocols
3.3 External data representation and marshalling
3.4 Group (Multicast) communication
3.5 Client – Server Communication (Request-reply protocols)
3.6 Case study - IPC in unix
3.7 Communication between Distributed Objects (RMI)
3.8 Remote Procedure Call
3.9 Events and Notifications
3.10 Case study - Java RMI

4.1 DFS Intro -Characteristics of file systems
4.2 File service architecture
4.3 Case study - Sun Network File System
4.4 Case study The Andrew File System
4.5 Name service Introduction
4.6 Name Services and Domain Name System
4.7 Directory Services
4.8 Case Study of The Global Name Services
4.9  Distributed shared Memory - Introduction
4.10 Design and implementation issues in Distributed shared Memory
4.11 Sequential consistency and IVY case study
4.12 Release consistency and MUNIN case study
4.13 Other consistency models

5.1 Concurrency Intro
5.2 Transactions
5.3 Nested Transactions
5.4 Locks
5.5 Optimistic concurrency control
5.6 Timestamp ordering
5.7 Comparison of methods for concurrency control
5.8 Distributed Transactions Introduction
5.9 Flat and nested distributed transactions
5.10 Atomic commit protocols
5.11 Concurrency control in distributed transactions
5.12 Distributed deadlocks
5.13 Transaction recovery

 Unit-wise
UNIT 1 DOCX PDF
UNIT 2 DOCX PDF
UNIT 3 DOCX PDF
UNIT 4 DOCX PDF  OTHER PDF
UNIT 5 DOCX PDF

Sample Questions
No comments:

Theory of Computation

Theory of Computation by Michael Sipser
Slides
No comments:

Computer Security

Computer Security Art and Science by Matt Bishop
Slides
No comments:

Object Oriented Programming with C++

No comments:

Data Mining

JNTUH
Ref: Introduction To Data Mining P N Tan M Steinbach V Kumar

1.0 what is data mining
1.1 KDD
1.2 Challenges
1.3 Data mining Tasks
1.4 Preprocessing
1.7 Dimensionality reduction
1.8 Feature subset selection
1.9 Discretization and Binaryzation
1.10 Variable Transformation
1.11 Measures of Similarity and Dissimilarity

2.1 Association Analysis Problem Definition
2.2 Frequent Itemset Generation
2.3 Apriori Principle
2.5 Rule generation
2.6 Apriori Algorithm
2.7 FP Growth algorithm
2.8 Compact Representation of Frequent Itemset
2.8a Compact Representation of Frequent Itemset

3.1 Classification - Problem definition
3.2 General Approaches to solving a classification  problem  & 3.3 Evaluation of Classifiers
3.4 Classification technique
3.5 Decision tree construction
3.6 Methods for Expressing Attribute Test Conditions
3.7 Measures for Selecting the Best Split,
3.8 Algorithm for Decision tree Induction
3.9 Naive bayes
3.10 Bayesian Belief Networks
3.11 Nearest neighbor

4.1 Clustering Overview
4.2 Partitioning Clustering
4.3 K-means algorithm
4.4 K-Means Additional issues
4.4a PAM Algorithm
4.5 Basic Agglomerative Hierarchical Clustering Algorithm
4.6 specific techniques (short notes without examples)
4.6 specific techniques (with examples)
4.7 Key Issues in Hierarchical Clustering
4.8 Strengths and Weakness
4.9 Outlier Analysis

5.0 Web usage Mining
5.2 Mining the World Wide Web

UNIT-1 PDF
UNIT-2 PDF
UNIT-3 PDF
UNIT-4 PDF
UNIT-5 PDF

Anna University
Ref: Data Mining: Concepts and Techniques -  Jiawei Han, Micheline Kamber

1.1 Data Warehouses Introduction
1.2 Multidimensional model
1.3 Data Warehouse Architecture
1.4 Data Warehouse Implementation
1.6 From Data Warehousing to Data Mining

2.1 Needfor Data Cleaning
2.2 Data Cleaning
2.3 Data Integration
2.4 Data Transformation
2.5 Data Reduction
2.6 Data Discretizationand Concept Hierarchy Generation for Numerical Data
2.7 Primitives for Specifying Data Mining Task
2.8 Data Mining Query Language
2.9 Designing Graphical User Interfaces Based On a Data MiningQuery Language
2.11 Concept Description
2.14 Class Comparison

 3.1 Mining Frequent Patterns, Associations, and Correlations
3.2 Single-Dimensional Boolean Association Rules from Transactional Databases-The Apriori Algorithm
3.3 Mining Multilevel Association Rules
3.4 Mining Multidimensional Association Rules

4.1 Classification and Prediction
4.2 Issues regarding classification and prediction
4.3 Decision tree
4.4 Bayesian classification
4.5 Association Rule based classification
4.6 other classification methods
4.7 Prediction
4.9 Cluster Analysis
4.11 Categorization of Clustering Methods
4.13 Outlier Analysis
1 comment:

SOFTWARE ENGINEERING


SOFTWARE ENGINEERING

Unit I SW Process


Unit II SW Requirements


Unit III Software Design

Introduction to Software Design
The Design Process
Design Principles
Design Concepts
Effective Modular Design
Design Heuristics for Effective Modularity
Architectural Design-Importance, Data Design
Architectural Styles
Mapping Requirements into A Software Architecture
Transform Mapping
Transaction Mapping
User Interface Design - The Golden Rules
User Interface Design
User Interface Design - Interface Design Models - The User Interface Design Process
User Interface Design - Task Analysis and Modeling
User Interface Design - Interface Design Activities
User Interface Design - Implementation Tools
Real Time System and Design
Real Time Executives

Unit IV Testing

Software Testing Objective, Principle
Black Box Testing
Black Box Testing - Graph-Based Testing Methods
Black Box Testing - Equivalence Partitioning
Black Box Testing - Comparison Testing
Software Testing Strategies
White Box Testing-Basis Path Testing
Integration Testing - Regression -Smoke Testing
Unit Testing
Validation Testing
System Testing

3 comments:
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