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Subject Syllabus

AL503 (A) - Information Retrieval

AIML · Semester 5

Course Modules

Learn topic-wise with Hyper AI and revise using mapped PYQs.

History of information retrieval Components of information retrieval Issues Open source search engine frameworks The impact of the web on information retrieval The role of artificial intelligence in information retrieval Information retrieval versus web search Components of a search engine Characterizing the web

Boolean and vector space retrieval models Term weighting TF-IDF weighting Cosine similarity Preprocessing Inverted indices Efficient processing with sparse vectors Language model based information retrieval Probabilistic information retrieval Latent semantic indexing Relevance feedback and query expansion

Web search overview Web structure, the user, paid placement, and search engine optimization Web search architectures Crawling and meta-crawlers Focused crawling Web indexes Near-duplicate detection Index compression XML retrieval

Link analysis Hubs and authorities PageRank and HITS algorithms Searching and ranking Relevance scoring and ranking for the web Similarity Hadoop and MapReduce Evaluation Personalized search Collaborative filtering and content-based recommendation of documents and products Handling the invisible web Snippet generation and summarization Question answering Cross-lingual retrieval

Information filtering: organization and relevance feedback Text mining Text classification and clustering Categorization algorithms: naive Bayes, decision trees, and nearest neighbor Clustering algorithms: agglomerative clustering, k-means, and expectation maximization (EM)