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An approach to probabilistic retrieval

C. T. Yu, K. Lam
1981 SIGIR Forum  
It is found that there is a correspondence between probabilistic retrieval schmes and fuzzy sets. A fuzzy set corresponding to a potentially optimal probabilistic retrieval scheme is obtained.  ...  The objective is to relate the effectiveness of retrieval, the fuzzy set concept and the processing of Boolean query. The use of a probabilistic retrieval scheme is motivated.  ...  Our aim is to find a probabilistic retrieval scheme, say PRSI, SL:cn that I) The performance of PRSI is always better than that of the random PRS (which assigns equal probabilities of retrieval to all  ... 
doi:10.1145/1013228.511761 fatcat:z476gfmbsjemdom7xqynwetdju

Book ReviewLanguage Modeling for Information Retrieval W. Bruce Croft and John Lafferty (editors) (University of Massachusetts, Amherst, and Carnegie Mellon University) Dordrecht: Kluwer Academic Publishers (Kluwer international series on information retrieval, edited by W. Bruce Croft), 2003, xiii+245 pp; hardbound, ISBN 1-4020-1216-0, $97.00, £62.00, €99.00

Paul Thompson
2004 Computational Linguistics  
Lafferty and Zhai claim to show an equivalence between the underlying probabilistic semantics 110 Book Reviews of the language-modeling approach and the standard probabilistic model of informa- tion retrieval  ...  Probabilistic Approach to Term Transla- tion for Cross-Lingual Retrieval,” Manmatha’s “Applications of Score Distributions in Information Retrieval,” and Zhang and Callan’s “An Unbiased Generative Model  ... 
doi:10.1162/coli.2004.30.1.110 fatcat:2ggkl2pbvnhyjklfxqrrkqndw4

Page 111 of Computational Linguistics Vol. 30, Issue 1 [page]

2004 Computational Linguistics  
Probabilistic Approach to Term Transla- tion for Cross-Lingual Retrieval,” Manmatha’s “Applications of Score Distributions in Information Retrieval,” and Zhang and Callan’s “An Unbiased Generative Model  ...  Statistical approaches have always played an important role in information retrieval.  ... 

Optimum polynomial retrieval functions

N. Fuhr
1989 Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '89  
Then we describe an approach for the development of optimum polynomial retrieval functions: request-document pairs (f" d",) are mapped onto description vectors Z(ft,&,), and a polynomial function of the  ...  On the other hand, this approach is not suited to loglinear probabilistic models, and it needs large samples of relevance feedback data for its application.  ...  This retrieval function yields results similar to those of the LSP approach.  ... 
doi:10.1145/75334.75343 dblp:conf/sigir/Fuhr89 fatcat:5amkkkzunfcdtacwmrvmbxwenm

Guido/Mir - An Experimental Musical Information Retrieval System Based On Guido Music Notation

Holger H. Hoos, Kai Renz, Marko Görg
2001 Zenodo  
to an intuitive approach to approximate matching.  ...  Here, we first consider exact retrieval, and later discuss briefly an extension of our approach to approximate retrieval.  ... 
doi:10.5281/zenodo.1417516 fatcat:jr6zhy6l3ngqfhpna4mkbswtny

Probabilistic document indexing from relevance feedback data

N. Fuhr, C. Buckley
1990 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '90  
Based on the binary independence indexing model, we apply three new concepts for probabilistic document indexing from relevance feedback data: (cl 1990 ACM o-89791-408-2 90 0009 45 $1.50  ...  Acknowledgement We thank Keith van Rijsbergen for his constructive comments on an earlier version of this paper.  ...  however, these models lack an explicit notion of an event to which the probabilistic weights relate. In this paper, we present a radically different approach to;probabilistic indexing.  ... 
doi:10.1145/96749.98008 dblp:conf/sigir/FuhrB90 fatcat:eqgdee67jnerzon3qouuenl2da

Looking back: On relevance, probabilistic indexing and information retrieval

Paul Thompson
2008 Information Processing & Management  
This was the first paper to present a probabilistic approach to information retrieval, and perhaps the first paper on ranked retrieval.  ...  Forty-eight years ago Maron and Kuhns published their paper, "On Relevance, Probabilistic Indexing and Information Retrieval" (1960).  ...  Solomonoff for their comments on the state of information retrieval research around 1960. The author also thanks the two anonymous reviewers whose comments helped improve the paper.  ... 
doi:10.1016/j.ipm.2007.10.002 fatcat:ijfndl2zhnbjvkmkwbz3uxic4e

Models for retrieval with probabilistic indexing

Norbert Fuhr
1989 Information Processing & Management  
Second is the retrieval-with-probabilistic-indexing (RPI) model, which is suited to different kinds of probabilistic indexing.  ...  The probabilistic indexing weights required for any of these models can be provided by an application of the Darmstadt indexing approach (DIA) for indexing with descriptors from a controlled vocabu-Iary  ...  While the first approach can be verified only indirectly by regarding its retrieval effectiveness, in the FOC approach every probabilistic weight has an explicit notion, and there are theoretical models  ... 
doi:10.1016/0306-4573(89)90091-5 fatcat:lkf75n35k5hkvl4uqxzrsfalgy

Probabilistic drug connectivity mapping

Juuso A Parkkinen, Samuel Kaski
2014 BMC Bioinformatics  
This can be viewed as an information retrieval task, with the goal of finding the most relevant profiles for a given query drug.  ...  We also demonstrate that an extension of the method is capable of retrieving combinations of drugs that match different relevant parts of the query drug response profile.  ...  Acknowledgements We'd like to thank Suleiman A. Khan for his useful discussions and insights.  ... 
doi:10.1186/1471-2105-15-113 pmid:24742351 pmcid:PMC4011783 fatcat:mbxzgdvc6jgx3l6i47jufpcvqi

Introduction to probabilistic models in IR

Victor P. Lavrenko
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
Most of today's state-of-the-art retrieval models, including BM25 and language modeling, are grounded in probabilistic principles.  ...  be applied to real world problems.  ...  This half-day tutorial will cover the fundamentals of two dominant probabilistic frameworks for Information Retrieval: the classical probabilistic model and the language modeling approach.  ... 
doi:10.1145/1835449.1835677 dblp:conf/sigir/Lavrenko10 fatcat:emrhptb75zdrnef5h62pqviqbq

The Probabilistic Relevance Framework: BM25 and Beyond

Stephen Robertson
2010 Foundations and Trends in Information Retrieval  
This is not primarily an experimental survey; throughout, assertions will be made about techniques which are said to work well.  ...  Introduction This monograph addresses the classical probabilistic model of information retrieval.  ... 
doi:10.1561/1500000019 fatcat:vma3ni3sffdyjhypjwf77xqdka

Modelling retrieval models in a probabilistic relational algebra with a new operator: the relational Bayes

Thomas Roelleke, Hengzhi Wu, Jun Wang, Hany Azzam
2007 The VLDB journal  
This paper presents a probabilistic relational modelling (implementation) of the major probabilistic retrieval models.  ...  ), the probabilistic relational modelling of retrieval models, a comparison of modelling retrieval with traditional SQL versus modelling retrieval with PSQL, and a comparison of the performance of probability  ...  Acknowledgements: We would like to acknowledge the excellent and deep reviews that helped improving the earlier version of this paper.  ... 
doi:10.1007/s00778-007-0073-y fatcat:qiexpftcfvgs7eonakx3xocb7e

Information Retrieval with Probabilistic Datalog [chapter]

Thomas Rölleke, Norbert Fuhr
1998 Information Retrieval: Uncertainty and Logics  
The probabilistic logical approach in Information Retrieval (IR) aims at describing the retrieval process as the computation of the probability .  ...  Datalog combines the logical approach to databases with IR applications.  ...  Datalog is a platform for investigating and implementing probabilistic logical approaches to IR and enables the evaluation of these approaches.  ... 
doi:10.1007/978-1-4615-5617-6_9 fatcat:5krw3l3n5rb3pfhgrmqdaoml5y

A Probabilistic, Text and Knowledge-Based Image Retrieval System [chapter]

Rubén Izquierdo-Beviá, David Tomás, Maximiliano Saiz-Noeda, José Luis Vicedo
2006 Lecture Notes in Computer Science  
This paper describes the development of an image retrieval system that combines probabilistic and ontological information 1 . The process is divided in two different stages: indexing and retrieval.  ...  Knowledge is added to the system by means of an ontology created automatically from the St. Andrews Corpus. The system has been evaluated at CLEF05 image retrieval task. 4  ...  Introduction An image retriever is an IR system that discovers relevant images. Mainly, there are two approaches to Image Retrieval [1] .  ... 
doi:10.1007/11878773_63 fatcat:72zaesgagbckbe4sjqmzy6rvdm

Ranking-based processing of SQL queries

Hany Azzam, Thomas Roelleke, Sirvan Yahyaei
2011 Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11  
To implement this ranking-based processing, we leverage PSQL, a probabilistic variant of SQL, to facilitate probability estimation and the generalisation of document retrieval models to be used for tuple  ...  The result is a general-purpose framework that can interpret any SQL query and then assign a probabilistic retrieval model to rank the results of that query.  ...  The SQL2PSQL translation algorithms were shown to generate PSQL programs that assign an IR-model-based, probabilistic ranking to the tuples retrieved for an SQL query.  ... 
doi:10.1145/2063576.2063614 dblp:conf/cikm/AzzamRY11 fatcat:kiwo2muys5h5jfcvqrw23s6gbm
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