Information Retrieval 3170718 Syllabus Download With Weightage
Information Retrieval 3170718 Syllabus Download With Weightage is presented in the 7th semester of the Computer department.
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| 1 | Introduction to Information Retrieval: The nature of unstructured and semi-structured text. Inverted index and Boolean queries. |
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| 2 | Text Indexing, Storage and Compression: Text encoding: tokenization, stemming, stop words, phrases, index optimization. Index compression: lexicon compression and postings lists compression. Gap encoding, gamma codes, Zipf’s Law. Index construction. Postings size estimation, merge sort, dynamic indexing, positional indexes, n-gram indexes, realworld issues. |
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| 3 | Retrieval Models: Boolean, vector space, TFIDF, Okapi, probabilistic, language modeling, latent semantic indexing. Vector space scoring. The cosine measure. Efficiency considerations. Document length normalization. Relevance feedback and query expansion. Rocchio. |
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| 4 | Performance Evaluation: Evaluating search engines. User happiness, precision, recall, Fmeasure. Creating test collections: kappa measure, interjudge agreement. | 6 |
| 5 | Text Categorization and Filtering: Introduction to text classification. Naive Bayes models. Spam filtering. Vector space classification using hyperplanes; centroids; k Nearest Neighbors. Support vector machine classifiers. Kernel functions. Boosting |
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| 6 | Text Clustering: Clustering versus classification. Partitioning methods. k-means clustering. Mixture of Gaussians model. Hierarchical agglomerative clustering. Clustering terms using documents |
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| 7 | Advanced Topics: Summarization, Topic detection and tracking, Personalization, Question answering, Cross language information retrieval |
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| 8 | Web Information Retrieval: Hypertext, web crawling, search engines, ranking, link analysis, PageRank, HITS. |
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| 9 | Retrieving Structured Documents: XML retrieval, semantic web | 5 |
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