Syllabus - Information Retrieval (AD 603 (C))

Introduction

History of IR- Components of IR - Issues - Open source Search engine. Frameworks - The Impact of the web on IR - The role of artificial intelligence (AI) in IR – IR Versus Web Search - Components of a search engine, characterizing the web.

Boolean and Vector space retrieval models

Term weighting - TF-IDF weighting- cosinesimilarity - Pre-processing - Inverted indices - efficient processing with sparse vectors LanguageModel based IR - Probabilistic IR -Latent Semantic indexing - Relevance feedback and queryexpansion.

Web search overview

web structure the user paid placement search engine optimization, Web Search Architectures - crawling - meta-crawlers, Focused Crawling - web indexes - Near duplicate detection - Index Compression - XML retrieval.

Link Analysis

hubs and authorities - Page Rank and HITS algorithms - Searching and Ranking Relevance Scoring and ranking for Web - Similarity - Hadoop & Map Reduce - Evaluation - Personalized search - Collaborative filtering and content-based recommendation of documents - handling And products QuestionAnswering, Cross-Lingual Retrieval. - Snippet generation, Summarization. invisible Web

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, expectation maximization (EM).