'Retrieved documents' presentation slideshows

INFSCI 2140 Information Storage and Retrieval Lecture 5: Retrieval Evaluation

574 views • 54 slides

Indexing and Representation: The Vector Space Model

546 views • 40 slides

Computing Relevance, Similarity: The Vector Space Model

439 views • 37 slides

Assessing The Retrieval

Assessing The Retrieval. A.I Lab 2007.01.20 ???. Contents. 4.1 Personal Assessment of Relevance 4.2 Extending the Dialog with RelFbk 4.3 Aggregated Assessment : Search Engine Performance 4.4 RAVE : A Relevance Assessment Vehicle 4.5 Summary. 4.1 Personal Assessment of Relevance.

453 views • 34 slides

Computing Relevance, Similarity: The Vector Space Model

403 views • 34 slides

Computing Relevance, Similarity: The Vector Space Model

355 views • 34 slides

Information Retrieval and Web Search

Vasile Rus, PhD vrus@memphis.edu www.cs.memphis.edu/~vrus/teaching/ir-websearch/. Information Retrieval and Web Search. Indexing and Searching. Outline. Sequential online text searching Raw text Appropriate for small texts or fast-changing texts Use index structures for fast access

418 views • 28 slides

Clustering-based Collaborative filtering for web page recommendation

Clustering-based Collaborative filtering for web page recommendation. CSCE 561 project Proposal Mohammad Amir Sharif mas4108@louisiana.edu. Presentation Outline. Introduction to Recommendation Systems Clustering based recommendation algorithm

538 views • 24 slides

Learning to Rank at Query-Time using Association Rules

346 views • 23 slides

Probabilistic Latent Semantic Analysis

390 views • 22 slides

Precision and Recall

Precision and Recall. Reminder: Precision : % of # of retrieved documents that are relevant Recall : % of all relevant documents that are retrieved. Not Relevant. Relevant. Not Rel Not Ret. Rel but Not Ret A. Ret but Not Rel C. Rel and Ret B. Not Retrieved.

167 views • 10 slides

Retrieval Evaluation

Retrieval Evaluation. Introduction. Evaluation of implementations in computer science often is in terms of time and space complexity. With large document sets, or large content types, such performance evaluations are valid.

125 views • 10 slides

Document Clustering for Natural Language Dialogue-based IR (Google for the Blind)

Document Clustering for Natural Language Dialogue-based IR (Google for the Blind). Antoine Raux IR Seminar and Lab 11-743 Fall 2003 Initial Presentation. Background. Current search engines: user browses through an ordered list of retrieved documents

93 views • 9 slides

Kappa Statistic (See Carletta 96 to start)

Kappa Statistic (See Carletta 96 to start). retrieved & irrelevant. Not retrieved & irrelevant. Entire document collection. irrelevant. Relevant documents. Retrieved documents. retrieved & relevant. not retrieved but relevant. relevant. retrieved. not retrieved. Precision and Recall.

200 views • 6 slides