CS6007 Information Retrieval Syllabus Notes Question Papers 2 Marks with Answers Question Bank with answers Anna University
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 the answer is provided below. CS6007 Notes Syllabus all 5 units notes are uploaded here. here CS6007 Information Retrieval 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
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CS6007 INFORMATION RETRIEVAL 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, Cross- Lingual 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).

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CS6007 Information Retrieval Notes Syllabus Question Papers Question Bank
Anna University CS6007 Notes Syllabus Question Papers Question Bank 2 marks with answers
CS6007 Information Retrieval Lecture Notes Subject Notes Anna University
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