Embedded Files
IR-lec01-Intro (1).pdfL-1 (Course Introduction)
IR-lec02-boolean-retrieval.pdfL-2 (Boolean Retrieval)
IR-lec03-vocabulary-postings-list.pdfL-3 (Term Vocabulary & Postings List)
IR-lec04-skip-ptrs-phrase-queries-indexing.pdfL-4 (Skip Pointers, Phrase Queries, Indexing)
chap5 (1)_merged.pdfL-5 (Search Engines)
LSH-IR.pdfL-6 (Locally Sensitive Hashig)
Lecture-03-dict-tolerant-retrieval.pptxL-7 (Dictionaries and tolerant retrieval)
Lecture-06-scoring.pptxL-8 (Scoring, Weighting and the Vector Space Mode)
Lecture-08-evaluation.pptxL-9 (Evaluation)
Lecture-04-index_compression.pptxL-10 (Index Compression)
Lecture-05-posting_compression.pptxL-11 (Posting Compression)
Lecture-10-probabilistic IR.pdfL-12 (Probabilistic IR)
Lecture-11-Language models.pdfL-13 (Language Models for IR)
Lecture-09-queryexpansion.pdfL-14 (Relevance Feedback)
summarization-merged.pdfL-15 (Summarization)
W11L2-pages.pdfL-16 (Integer Linear Programming)
W10L3.pdfL-17 (Information Extraction)
W10L4.pdfL-18 (Relation Extraction)
W10L5.pdfL-19 (Distant Supervision)
IR-on-ecommerce-platforms.pdfL-20 (IR on E-commerce platforms)
Lecture-12 Text Classification Naive Bayes.pdfL-21 (Text Classification & Naive Bayes)Â
Lecture-14-Learning to rank.pdfL-22 (Learning to Rank)
Lecture-17-LatentSemanticIndexing.pdfL-23(Learning Semantic Indexing)
Lecture-18-pagerank.pdfL-24(Page Rank Citation Ranking)
1704.01347v1.pdfL-25 (Quantifying Search Bias)
L-25 (Quantifying Search Bias)
Lecture-13-Vector Space Classification.pptxL-26(Vector Space Classification)
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