Information Retrieval
24CSE6144 · S6 · 4 credits
Official KTU 2024 syllabus subject — study with practice, PYQs and AI tools.
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Why:Foundation module
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Why:Core module
Why:Applied concepts
Why:Standard exam coverage
Module 01Dictionaries and Tolerant Retrieval (7 hrs)expand
Boolean Retrieval-An example information retrieval problem, Inverted index, Processing Boolean queries, The extended Boolean model versus ranked retrieval, Search structures for dictionaries, Wildcard queries-General wildcard queries, k-gram indexes for wildcard queries, Spelling correction-Implementing spelling correction, Forms of spelling correction, Edit distance, k-gram indexes for spelling correction, Context sensitive spelling correction
Module 02Index Compression and Dictionary Compression (7 hrs)expand
Index construction-Hardware basics, Blocked sort-based indexing, Single-pass in- memory indexing, Distributed indexing, Dynamic indexing, Index Compression-Heaps’ law, Statistical properties of terms- Zipf’s law, Dictionary compression- Dictionary as a string, Blocked storage,
Module 03Scoring, Term Weighting, and Vector Space Models (7 hrs)expand
Parametric and zone indexes -Weighted zone scoring, Learning weights, optimal weight g, Term frequency, and weighting- Inverse document frequency Tf-idf weighting, Vector space model for scoring-Dot products, Queries as vectors, Computing vector scores. Variant tf-idf functions-Sublinear tf scaling, Maximum tf normalization, Document and query weighting schemes, Pivoted normalized document length.
Module 04Evaluation and Language Models (7 hrs)expand
Information retrieval system evaluation, Standard test collections, Evaluation of unranked retrieval sets, Evaluation of ranked retrieval results, Assessing relevance. Language models- Finite automata and language models, Types of language models, Multinomial distributions over words
Module 05Web Search and Link Analysis (8 hrs)expand
Web characteristics-Web graph, Spam, Crawling-Features of a Crawler, Crawler architecture, DNS resolution, URL frontier, Link Analysis-Web Graph, PageRank – Markov chains, Page Rank computation, Topic-specific Page Rank.
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