Syllabus B Tech Computer Science Seventh Semester Modern Information Retrieval CS7004

Computer-Science-Engineering-7

Syllabus B Tech Computer Science Seventh Semester Modern Information Retrieval CS7004

The concepts developed in this course will aid in quantification of several concepts in Computer Science Engineering that have been introduced at the Engineering courses. Technology is being increasingly based on the latest Syllabus B Tech Computer Science Seventh Semester Modern Information Retrieval CS7004 is given here.

The objective of this course Syllabus B Tech Computer Science Seventh Semester Modern Information Retrieval CS7004 is to develop ability and gain insight into the process of problem-solving, with emphasis on thermodynamics. Specially in following manner: Apply conservation principles (mass and energy) to evaluate the performance of simple engineering systems and cycles. Evaluate thermodynamic properties of simple homogeneous substances. Analyze processes and cycles using the second law of thermodynamics to determine maximum efficiency and performance. Discuss the physical relevance of the numerical values for the solutions to specific engineering problems and the physical relevance of the problems in general and Critically evaluate the validity of the numerical solutions for specific engineering problems. More precisely, the objectives are:

  • To enable young technocrats to acquire mathematical knowledge to understand Laplace transformation, Inverse Laplace transformation and Fourier Transform which are used in various branches of engineering.
  • To introduce effective mathematical tools for the Numerical Solutions algebraic and transcendental equations.
  • To acquaint the student with mathematical tools available in Statistics needed in various field of science and engineering.

CS 7004 – Modern Information Retrieval

Unit 1
Introduction: Information versus data retrieval, the retrieval process, taxonomy of Information Retrieval Models.
Unit 2
Classic Information Retrieval Techniques: Boolean Model, Vector model, Probabilistic Model, comparison of classical models. Introduction to alternative algebraic models such as Latent Semantic Indexing etc.
Unit 3
Keyword based Queries, User Relevance Feedback: Query Expansion and Rewriting, Document preprocessing and clustering, Indexing and Searching: Inverted Index construction, Introduction to Pattern matching.
Unit 4
Web Search: Crawling and Indexes, Search Engine architectures, Link Analysis and ranking algorithms such as HITS and PageRank, Meta searches, Performance Evaluation of search engines using various measures, Introduction to search engine optimization.
Unit 5
Introduction to online IR Systems, Digital Library searches and web Personalization.

Books Recommended

1. Amy N. Langville and Carl D. Meyer, “Google’s PageRank and Beyond: The Science of Search Engine Rankings”, Princeton University Press
2. Pierre Baldi, Paolo Frasconi and Padhraic Smythe, “Modelling the internet and the web: Probabilistic methods and Algorithms”, John Wiley

3. Ricardo Baeza-Yates and Berthier Ribeiro-Neto, “Modern Information Retrieval” Pearson Education
4. C. Manning, P. Raghvan and H. Schutze, “Introduction to Information Retrieval”, Cambridge University Press.