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CS6007 Information Retrieval Syllabus Notes 2 Marks with Answers Question Bank with answers

Anna University CS6007 Information Retrieval Notes Syllabus 2 marks with answers Part A Question Bank with answers

Anna University CS6007 Information Retrieval Syllabus Notes 2 marks with answer is provided below. CS6007 Notes Syllabus all 5 units notes are uploaded here. here CS6007 IR Syllabus notes download link is provided and students can download the CS6007 Syllabus and Lecture Notes and can make use of it.

Anna University Regulation 2013 Notes Syllabus Question Papers Question Banks - Rejinpaul

Click below link to download CS6007 Information Retrieval Study Materials .

CS6007 Information Retrieval THEORY SYLLABUS REGULATION 2013

UNIT I   INTRODUCTION                                                                               
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.

UNIT II  INFORMATION RETRIEVAL                       
Boolean and vector-space retrieval models- Term weighting - TF-IDF weighting- cosine similarity – Preprocessing - Inverted indices - efficient processing with sparse vectors – Language Model based IR - Probabilistic IR –Latent Semantic Indexing - Relevance feedback and query expansion.

UNIT III  WEB SEARCH ENGINE – INTRODUCTION AND CRAWLING                                 
Web search overview, web structure, the user, paid placement, search engine optimization/ spam. Web size measurement - search engine optimization/spam – Web Search Architectures - crawling - meta-crawlers- Focused Crawling - web indexes –- Near-duplicate detection - Index Compression - XML retrieval.

UNIT IV  WEB SEARCH – LINK ANALYSIS AND SPECIALIZED SEARCH                 
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 and products – handling “invisible” Web - Snippet generation, Summarization, Question Answering, CrossLingual Retrieval.

UNIT V  DOCUMENT TEXT MINING                                 
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)

Click below link to download the Notes and 2 marks with answers Question Bank Question Papers

CS6007 Notes - Click here (NOTES 1)
CS6007 NOTES - CLICKHERE(NOTES 2)

CS6007 Question Bank - Click here



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