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Subject

Information Retrieval

This course familiarizes students with different concepts of information retrieval techniques mainly focused on clustering, classification, search engine, ranking and query operations techniques.

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Introduction to IR and Web Search

Introduction, Data vs Information Retrieval, Logical view of the documents, Architecture of IR System, Web search system, History of IR, Related areas

Introduction, Data vs Information Retrieval, Logical view of the documents, Architecture of IR System, Web search system, History of IR, Related areas

128+ Students

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Text properties, operations and preprocessing

Tokenization, Text Normalization, Stop-word removal, Morphological Analysis, Word Stemming (Porter Algorithm), Case folding, Lemmatization, Word statistics (Zipf's law, Heaps. . .

Tokenization, Text Normalization, Stop-word removal, Morphological Analysis, Word Stemming (Porter Algorithm), Case folding, Lemmatization, Word statistics (Zipf's law, Heaps’Law), Index term selection, Inverted indices, Positional Inverted index, Natural Language Processing in Information Retrieval, Basic NLP tasks – POS tagging; shallow parsing

84+ Students

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Basic IR Models

Classes of Retrieval Model, Boolean model, Term weighting mechanism – TF, IDF, TF-IDF weighting, Cosine Similarity, Vector space model , Probabilistic models (the binary inde. . .

Classes of Retrieval Model, Boolean model, Term weighting mechanism – TF, IDF, TF-IDF weighting, Cosine Similarity, Vector space model , Probabilistic models (the binary independence model ,Language models; · KL-divergence; · Smoothing), Non-Overlapping Lists, Proximal Nodes Mode

92+ Students

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Evaluation of IR

Precision, Recall, F-Measure, MAP (Mean Average Precision), (DCG) Discounted Cumulative Gain, Known-item Search Evaluation

Precision, Recall, F-Measure, MAP (Mean Average Precision), (DCG) Discounted Cumulative Gain, Known-item Search Evaluation

78+ Students

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Query Operations and Languages

Relevance feedback and pseudo relevance feedback, Query expansion (with a thesaurus or WordNet and correlation matrix), Spelling correction (Edit distance, K – Gram indexes, . . .

Relevance feedback and pseudo relevance feedback, Query expansion (with a thesaurus or WordNet and correlation matrix), Spelling correction (Edit distance, K – Gram indexes, Context sensitive spelling correction), Query languages (Single-Word Queries, Context Queries, Boolean Queries, Structural Query, Natural Language)

74+ Students

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Web Search

Search engines (working principle), Spidering (Structure of a spider, Simple spidering algorithm, multithreaded spidering, Bot), Directed spidering (Topic directed, Link dire. . .

Search engines (working principle), Spidering (Structure of a spider, Simple spidering algorithm, multithreaded spidering, Bot), Directed spidering (Topic directed, Link directed), Crawlers (Basic crawler architecture), Link analysis (HITS, Page ranking), Query log analysis, Handling “invisible” Web – Snippet generation, CLIR (Cross Language Information Retrieval)

94+ Students

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Text Categorization

Categorization, Learning for Categorization, General learning issues, Learning algorithms : Bayesian (naïve), Decision tree, KNN, Rocchio)

Categorization, Learning for Categorization, General learning issues, Learning algorithms : Bayesian (naïve), Decision tree, KNN, Rocchio)

74+ Students

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Text Clustering

Clustering, Clustering algorithms (Hierarchical clustering, k-means, k-medoid, Expectation maximization (EM), Text shingling)

Clustering, Clustering algorithms (Hierarchical clustering, k-means, k-medoid, Expectation maximization (EM), Text shingling)

71+ Students

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Recommender System

Personalization, Collaborative filtering recommendation, Content-based recommendation

Personalization, Collaborative filtering recommendation, Content-based recommendation

60+ Students

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Question Answering

Information bottleneck, Information Extraction, Ambiguities in IE, Architecture of QA system, Question processing, Paragraph retrieval, Answer processing

Information bottleneck, Information Extraction, Ambiguities in IE, Architecture of QA system, Question processing, Paragraph retrieval, Answer processing

75+ Students

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Advanced IR Models

Latent Semantic Indexing (LSI), Singular value decomposition, Latent Dirichlet Allocation, Efficient string searching, Knuth – Morris – Pratt, Boyer – Moore Family, Pattern m. . .

Latent Semantic Indexing (LSI), Singular value decomposition, Latent Dirichlet Allocation, Efficient string searching, Knuth – Morris – Pratt, Boyer – Moore Family, Pattern matching

71+ Students

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7th sem exam offer
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