aut aut      aut aut
   
Saeede Momtazi
  Courses 

 Advanced Topics in Information Retrieval and Web Search(FALL_2017)

Aims:

By increasing the amount of data on the Web retrieving information become a challenging issue in the last years such that using traditional methods cannot answer user information need. To increase the performance of information search advanced retrieval techniques is required. The goal of this course is expanding the basic knowledge of students about information retrieval and web search and introducing advanced topics to be used for these tasks

Syllabus:

  • Intorduction to IR and web search
  • Search engine architecture
  • Overview of traditional IR methods
  • IR evaluation
  • Advanced IR methods: language model-based, learning to rank
  • Overcoming word mismatch problem: language model-based approaches and query expansion approaches
  • Query log data analysis and Query Suggestion
  • Personalized search
  • Information extraction
  • Cross-Language IR
  • Question answering systems
  • Recommendation systems
  • Expert finding
  • Digital library
  • Multimedia retrieval

Text Book:

  • Search Engines: Information Retrieval in Practice, W. Bruce Croft, Donald Metzler, Trevor Strohman, Pearson Education, 2010
  • Ricardo Baeza-Yates, Berthier Ribeiro-Neto, Modern Information Retrieval: The Concepts and Technology behind Search (2nd Edition), ACM Press Books, 2010
  • Introduction to Information Retrieval, C. Manning, P. Raghavan, and H. Schütze. Cambridge University Press, 2008.


 Principles of Compiler Design(FALL_2017)

Aims:

The goal of this course is familiarity with the principles, techniques, and tools that are used to bild a compiler. This goal is achieved using 7 different steps that will be taught in this course.

Syllabus:

  • Introduction to compiler structure
  • lexical analysis
  • syntax analysis
  • semantic analysis
  • intermediate code generation
  • IC Optimization
  • target code generation
  • target code optimization

Text Book:

  • Compilers: Principles, Techniques & Tools, Aho, Lam, Sethi, and Ullman, 2 nd ed., 2007, Addison-Wesley


 Principles of Database Design(SPRING_2017)

Aims:

Database management has evolved from a specialized computer application to a central component of a modern computing environment, and, as a result, knowledge about database systems has become an essential part of an education in computer science. In this course, the fundamental concepts of database management including aspects of database design, database languages, and database-system implementation will be presented.

Syllabus:

  • Introduction to Database
  • Introduction to the Relational Model
  • Introduction to SQL
  • Intermediate SQL
  • Advanced SQL
  • Formal Relational Query Languages
  • Database Design and the E-R Model
  • Relational Database Design
  • XML
  • Object-based Data Models

Text Book:

  • ‌Database System Concepts, Abraham Silberschatz, Henry F. Korth, and S. Sudarshan, SIXTH EDITION, McGraw-Hill


 Special Topics (Statistical Natural Language Processing)(SPRING_2017)

Aims:

Natural language processing (NLP) is one of the active topics in artificial intelligence. The main goal of this field is giving the ability of understanding human language to computers. Various systems such as question answering, sentiment analysis, information extraction and retrieval, machine translation, and summarization which have recently received researchers attention are working based on NLP. The basis of designing and implementing such systems is statistical methods for processing natu

Syllabus:

  • Introduction to NLP
  • Linguistics Levels and NLP Challenges
  • Matematical Fundations
  • Language Models, Smoothing, and evaluation
  • Machine Learning Overview
  • Part-of-Speech Tagging
  • Parsing
  • Named Entity Recognition
  • Semantic Analysis, Word Similarity, Word Sense Disambiguation
  • Semantics Role Labeling
  • Text Classification and Clustering
  • Topic Detection
  • NLP Application Systems

Text Book:

  • SPEECH AND LANGUAGE PROCESSING: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, Daniel Jurafsky and James H. Martin. Second Edition, 2008,McGraw Hill
  • Foundations of Statistical Natural Language Processing, Christopher D. Manning, Hinrich Schuetze, 1999, The MIT Press


 Technical English(SPRING_2017)

Aims:

The goal of this course is improving the English language skills of students in the domain of computer engineering and information technology. The skills includes reading comprehension, listening and writing. To this aim, weekly exercises will be organized.

Syllabus:

  • Information technology
  • Computer software and hardware
  • Cloud computing
  • Linux
  • Search engines
  • Database and data mining
  • Artificial intelligence
  • Latex

Text Book:

  • Oxford English for Infomation Technology
  • Professional English in Use - ICT
  • Selected TED Talks


 Advanced Topics in Information Retrieval and Web Search(FALL_2016)

Aims:

By increasing the amount of data on the Web retrieving information become a challenging issue in the last years such that using traditional methods cannot answer user information need. To increase the performance of information search advanced retrieval techniques is required. The goal of this course is expanding the basic knowledge of students about information retrieval and web search and introducing advanced topics to be used for these tasks

Syllabus:

  • Intorduction to IR and web search
  • Search engine architecture
  • Overview of traditional IR methods
  • IR evaluation
  • Advanced IR methods: language model-based, learning to rank
  • Overcoming word mismatch problem: language model-based approaches and query expansion approaches
  • Query log data analysis and Query Suggestion
  • Personalized search
  • Information extraction
  • Cross-Language IR
  • Question answering systems
  • Recommendation systems
  • Expert finding
  • Digital library
  • Multimedia retrieval

Text Book:

  • Search Engines: Information Retrieval in Practice, W. Bruce Croft, Donald Metzler, Trevor Strohman, Pearson Education, 2010
  • Ricardo Baeza-Yates, Berthier Ribeiro-Neto, Modern Information Retrieval: The Concepts and Technology behind Search (2nd Edition), ACM Press Books, 2010
  • Introduction to Information Retrieval, C. Manning, P. Raghavan, and H. Schütze. Cambridge University Press, 2008.


 Statistical Natural Language Processing(FALL_2016)

Aims:

Natural language processing (NLP) is one of the active topics in artificial intelligence. The main goal of this field is giving the ability of understanding human language to computers. Various systems such as question answering, sentiment analysis, information extraction and retrieval, machine translation, and summarization which have recently received researchers attention are working based on NLP. The basis of designing and implementing such systems is statistical methods for processing text

Syllabus:

  • Introduction to NLP
  • Linguistics Levels and NLP Challenges
  • Matematical Fundations
  • Language Models, Smoothing, and evaluation
  • Machine Learning Overview
  • Part-of-Speech Tagging
  • Parsing
  • Named Entity Recognition
  • Semantic Analysis, Word Similarity, Word Sense Disambiguation
  • Semantics Role Labeling
  • Text Classification and Clustering
  • NLP Application Systems

Text Book:

  • SPEECH AND LANGUAGE PROCESSING: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, Daniel Jurafsky and James H. Martin. Second Edition, 2008,McGraw Hill
  • Foundations of Statistical Natural Language Processing, Christopher D. Manning, Hinrich Schuetze, 1999, The MIT Press


 Technical English(FALL_2016)

Aims:

The goal of this course is improving the English language skills of students in the domain of computer engineering and information technology. The skills includes reading comprehension, listening and writing. To this aim, weekly exercises will be organized.

Syllabus:

  • Information technology
  • Computer software and hardware
  • Cloud computing
  • Linux
  • Search engines
  • Database and data mining
  • Artificial intelligence
  • Latex

Text Book:

  • Selected short articles in CE and IT - from different authors
  • Professional English in Use - ICT
  • Selected TED Talks


 Principles of Database Design(SPRING_2016)

Aims:

Database management has evolved from a specialized computer application to a central component of a modern computing environment, and, as a result, knowledge about database systems has become an essential part of an education in computer science. In this course, the fundamental concepts of database management including aspects of database design, database languages, and database-system implementation will be presented.

Syllabus:

  • Introduction to Database
  • Introduction to the Relational Model
  • Introduction to SQL
  • Intermediate SQL
  • Advanced SQL
  • Formal Relational Query Languages
  • Database Design and the E-R Model
  • Relational Database Design

Text Book:

  • ‌Database System Concepts, Abraham Silberschatz, Henry F. Korth, and S. Sudarshan, SIXTH EDITION, McGraw-Hill


 Special Topics (Statistical Natural Language Processing)(SPRING_2016)

Aims:

Natural language processing (NLP) is one of the active topics in artificial intelligence. The main goal of this field is giving the ability of understanding human language to computers. Various systems such as question answering, sentiment analysis, information extraction and retrieval, machine translation, and summarization which have recently received researchers attention are working based on NLP. The basis of designing and implementing such systems is statistical methods for processing natu

Syllabus:

  • Introduction to NLP
  • Linguistics Levels and NLP Challenges
  • Matematical Fundations
  • Language Models, Smoothing, and evaluation
  • Machine Learning Overview
  • Part-of-Speech Tagging
  • Parsing
  • Named Entity Recognition
  • Semantic Analysis, Word Similarity, Word Sense Disambiguation
  • Semantics Role Labeling
  • Text Classification and Clustering
  • Topic Detection
  • NLP Application Systems

Text Book:

  • SPEECH AND LANGUAGE PROCESSING: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, Daniel Jurafsky and James H. Martin. Second Edition, 2008,McGraw Hill
  • Foundations of Statistical Natural Language Processing, Christopher D. Manning, Hinrich Schuetze, 1999, The MIT Press


 
 
© AUT All rights reserved.
AUT is not responsible for the content of external sites.
 
424 Hafez Ave, Tehran, Iran, 15875-4413. +98 (21) 64540