Unit 2
Goals and history of IR, impact of web in IR, basic concepts- query, document, corpus, text representation and evaluation, Boolean model, TF-IDF, vector-space retrieval models, Probabilistic retrieval models
| Course Name | Information Retrieval |
| Course Code | 23AID473 |
| Program | B.Tech in Artificial Intelligence and Data Science |
| Credits | 3 |
| Campus | Coimbatore , Amritapuri ,Faridabad , Bangaluru, Amaravati |
Goals and history of IR, impact of web in IR, basic concepts- query, document, corpus, text representation and evaluation, Boolean model, TF-IDF, vector-space retrieval models, Probabilistic retrieval models
Text similarity metrics, Tokenizing, language models, KL-divergence, performance metrics, reference collections and evaluation of IR systems, query languages for IR, relevance feedback, query expansion-local and global
Web search, web crawling, link analysis – hits, page rank, matrix decompositions and latent semantic indexing, Deep learning for IR- word embeddings, neural language models
Course Objectives
Course Outcomes
After completing this course, students will be able to
|
CO1 |
Use various techniques to represent a document as a vector |
|
CO2 |
Implement IR systems using various techniques |
|
CO3 |
Apply methods to evaluate IR systems |
|
CO4 |
Develop applications |
CO-PO Mapping
|
PO/PSO |
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
PSO1 |
PSO2 |
PSO3 |
|
CO |
|||||||||||||||
|
CO1 |
3 |
3 |
3 |
3 |
3 |
3 |
1 |
– |
3 |
3 |
2 |
3 |
3 |
1 |
1 |
|
CO2 |
3 |
3 |
3 |
2 |
3 |
2 |
– |
– |
3 |
3 |
2 |
3 |
3 |
2 |
2 |
|
CO3 |
3 |
3 |
3 |
3 |
2 |
1 |
– |
– |
3 |
3 |
3 |
3 |
3 |
3 |
3 |
|
CO4 |
3 |
3 |
3 |
3 |
2 |
1 |
– |
– |
3 |
3 |
3 |
3 |
2 |
3 |
3 |
Evaluation Pattern
|
Assessment |
Internal/External |
Weightage (%) |
|
Assignments (minimum 2) |
Internal |
30 |
|
Quizzes (minimum 2) |
Internal |
20 |
|
Mid-Term Examination |
Internal |
20 |
|
Term Project/ End Semester Examination |
External |
30 |
Text Books / References
Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008. http://nlp.stanford.edu/IR-book/information-retrieval-book.html
ChengXiang Zhai, Statistical Language Models for Information Retrieval (Synthesis Lectures Series on Human Language Technologies), Morgan & Claypool Publishers, 2008.
Stefan Buettcher, Charles L. A. Clarke, Gordon V. Cormack, Information Retrieval: Implementing and Evaluating Search Engines, MIT Press. (2010)
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