'Retrieval models' presentation slideshows

Analyzing Retrieval Models using Retrievability Measurement

Analyzing Retrieval Models using Retrievability Measurement. Shariq Bashir Supervisor: ao. Univ. Prof. Dr. Andreas Rauber Institute of Software Engineering and Interactive Systems Vienna University of Technology. bashir@ifs.tuwien.ac.at http://www.ifs.tuwien.ac.at/~bashir/. Outline.

794 views • 64 slides

Information Retrieval Models

Information Retrieval Models. School of Informatics Dept. of Library and Information Studies Dr. Miguel E. Ruiz. What is Information Retrieval. Information Retrieval deals with information items in terms of Representation Storage Organization Access

1.36k views • 48 slides

Lower-Bounding Term Frequency Normalization

Lower-Bounding Term Frequency Normalization. Yuanhua Lv and ChengXiang Zhai University of Illinois at Urbana-Champaign CIKM 2011 Best Student Award Paper Speaker: Tom Nov 8 th , 2011. It is very difficult to improve retrieval models. BM25 [Robertson et al. 1994]

501 views • 31 slides

Retrieval and Feedback Models for Blog Feed Search SIGIR 2008

Retrieval and Feedback Models for Blog Feed Search SIGIR 2008. Advisor ? Dr. Koh Jia-Ling Speaker ? Chou-Bin Fan Date ? 2009.10.05. Outline. Introduction Approach ? Retrieval Models : Large Document Model Small Document Models ? Query Expansion Models ?

400 views • 28 slides

Chapter 2 Modeling

Chapter 2 Modeling. ?? 4B 86075800 ???. Introduction. Traditional information retrieval systems usually adopt index terms to index and retrieve documents. An index term is a keyword (or group of related words) which has some meaning of its own (usually a noun).

334 views • 24 slides

Information Retrieval Models

Information Retrieval Models. Retrieval Models. A retrieval model specifies the details of: Document representation Query representation Retrieval function Determines a notion of relevance. Notion of relevance can be binary or continuous (i.e. ranked retrieval ).

1.86k views • 19 slides

Automatic Labeling of Multinomial Topic Models

Automatic Labeling of Multinomial Topic Models. Qiaozhu Mei, Xuehua Shen, ChengXiang Zhai University of Illinois at Urbana-Champaign. Outline. Background: statistical topic models Labeling a topic model Criteria and challenge Our approach: a probabilistic framework Experiments Summary.

338 views • 16 slides

CS598CXZ Course Summary

CS598CXZ Course Summary. ChengXiang Zhai Department of Computer Science University of Illinois, Urbana-Champaign. Course Goal. Advanced (graduate-level) introduction to the field of information retrieval (IR) Goal Provide an overview of IR research in the past several decades

91 views • 9 slides

A LANGUAGE MODELING APPROACH TO INFORMATION RETR I E VAL J AY M. Ponte & W. B RUCE Croft

92 views • 9 slides

ICAIL 2007 DESI Workshop Panel presentation Marie-Francine Moens

ICAIL 2007 DESI Workshop Panel presentation Marie-Francine Moens Centre for Law and ICT/ Department of Computer Science Katholieke Universiteit Leuven, Belgium. Some thoughts on search. Common information retrieval (cf. TREC):

52 views • 5 slides