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Course10610685271 lectures

Introduction to Information Retrieval

Prof. Dwaipayan Roy · IISER Kolkata

Start with lecture 1 At NPTEL

Lectures

Week 1

  1. Introduction to the course Video
  2. Introduction to Information Retrieval Video
  3. Text Processing: Term Selection Video
  4. Text Processing: Term Filtering and Linguistic Processing Video
  5. Indexing Video
  6. Inverted Index Video

Week 2

  1. Making of the Inverted Index Video
  2. Storing Inverted Index Video
  3. Inverted Index Summary Video
  4. Statistical Properties of Text - Zipf's Law Video
  5. Statistical Properties of Text - Heap's Law Video
  6. Index Compression Video

Week 3

  1. Getting started with PyLucene Video
  2. Installing Docker and PyLucene Video
  3. Understanding Different Fields in PyLucene - 1 Video
  4. Understanding Different Fields in PyLucene - 2 Video
  5. Reading a Small Toy Dataset for Indexing using PyLucene Video
  6. Different Analyzers in PyLucene Video

Week 4

  1. Indexing using PyLucene - Setting the Parameters Video
  2. Indexing using PyLucene - 2 Video
  3. Non-English Text Analysis using PyLucene Video
  4. Exploring Luke: The Lucene Index Viewer Video
  5. Experimenting with Different Options in Indexing Video
  6. PyLucene Practice Programs - 1 Video
  7. PyLucene Practice Programs - 2 Video
  8. Query Processing Video

Week 5

  1. Introduction to Ranked Retrieval Video
  2. Introduction to Term Weightings for Retrieval - TF Video
  3. Introduction to Term Weightings for Retrieval - IDF Video
  4. Vector Space Model - 1 Video
  5. Vector Space Model - 2 Video
  6. Vector Space Model - 3 Video

Week 6

  1. Vector Space Model - Problem Solving - 1 Video
  2. Vector Space Model - Problem Solving - 2 Video
  3. Probabilistic Model - Introduction Video
  4. Binary Independence Model (BIM) Video
  5. Best Match Model, BM1, BM11, BM15, BM25 Video
  6. Dissecting BM25, BM25 vs VSM, BM25 for long queries, BM25F, BM25+ Video
  7. BM25, After 30 years Video

Week 7

  1. Introduction to Language Model for Information Retrieval Video
  2. Introducing Unigram Language Model Video
  3. Estimating Document Language Model Video
  4. Zero Frequency Problem and introduction to Smoothing Video
  5. Jelinek-Mercer and Dirichlet Smoothed Language Model Video
  6. Comparing Smoothing with IDF and Summary of LM based Retrieval Video

Week 8

  1. Using Divergence Measures for Document Scoring Video
  2. PyLucene for Retrieval Video
  3. PyLucene - Varius Query Classes 1 - TermQuery Video
  4. PyLucene - Varius Query Classes 2 - PhraseQuery, TermRangeQuery, Numerical Range Query, PrefixQuery Video
  5. PyLucene - Varius Query Classes 3 - BooleanQuery, WildcardQuery, FuzzyQuery, MatchAllDocsQuery Video

Week 9

  1. Evaluating Information Retrieval Systems 1 - Set Based Evaluation Metrics Video
  2. Evaluating Information Retrieval Systems 2 - Precision@K, R-Prec, Incorporating Ranking in Precision and Recall Video
  3. Evaluating Information Retrieval Systems 3 - AP, MAP, GMAP, MRR Video
  4. Evaluating Information Retrieval Systems 4 - Graded relevance, nDCG Video
  5. Evaluating Information Retrieval Systems 5 - Hypothesis Testing, Role of Evaluation Forums, Kappa measure Video

Week 10

  1. Indexing in Benchmark Dataset - Indexing TREC-like Benchmark Datasets Video
  2. Retrieval in Benchmark Dataset - Retrieval in TREC-like Benchmark Datasets, and Evaluation using TREC_EVAL Video
  3. Comparing Retrieval Models - Hypothesis Testing in Information Retrieval Video
  4. Relevance Feedback 1 - An Introduction Video
  5. Relevance Feedback 2 - Rocchio's Algorithm Video
  6. Relevance Feedback 3 - Incorporating Pseudo Feedback using Relevance based Language Model, RM3 Video

Week 11

  1. Web Search And Crawler Video
  2. PageRank Algorithm Video
  3. PageRank - Random Surfer's Algorithm Video
  4. HITS Algorithm: Hubs and Authorities Video
  5. Search Engine Optimization Video

Week 12

  1. Learning to Rank for Information Retrieval Video
  2. Latent Semantic Indexing Video
  3. Introduction to Embeddings for Information Retrieval Video
  4. From Embeddings to Transformers Video
  5. Large Language Models for Information Retrieval Video

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IISER Kolkata
Department
Computer Science and Engineering
Teacher
Prof. Dwaipayan Roy
Level
Undergraduate
Language
English
Subjects
Computer science, Engineering
Source
NPTEL
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
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