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Modeling Information Retrieval with Probabilistic Argumentation Systems

Justin Picard, Rolf Haenni
1998 unpublished
Probabilistic Argumentation Systems (PAS) are a technique for representing uncertainty both symbolically and numerically.  ...  It is shown that this technique, which combines symbolic logic and probability, can be used as a general model of information retrieval.  ...  In a model of IR based on PAS, the Combining evidence and logical Modeling Information Retrieval with Probabilistic Argumentation Systems IRSG98 paradigms can be unified.  ... 
doi:10.14236/ewic/irsg1998.9 fatcat:clfkiuzfmbeovgcolapvr53v4a

The effect of accessing nonmatching documents on relevance feedback

Mark D. Dunlop
1997 ACM Transactions on Information Systems  
This paper shows that, in systems that allow access to non-matching documents (e.g. hybrid hypertext and information retrieval systems), the strength of the effect of giving relevance feedback varies between  ...  Traditional information retrieval (IR) systems only allow users access to documents that match their current query and, therefore, users can only give relevance feedback on matching documents (or those  ...  Figures 7 and 8 support the argument that, in general, the probabilistic model performs positive feedback in line with the intuitive argument.  ... 
doi:10.1145/248625.248650 fatcat:qy5kzxizl5a65gnb3rjdv4aq5e

A probabilistic relational algebra for the integration of information retrieval and database systems

Norbert Fuhr, Thomas Rölleke
1997 ACM Transactions on Information Systems  
With regard to databases, the approach allows for representing imprecise attribute values, whereas for information retrieval, probabilistic document indexing and probabilistic search term weighting can  ...  With these features, PRA implements uncertainty and vagueness in combination with the relational model.  ...  The Integration of Information Retrieval and Database Systems • The Integration of Information Retrieval and Database Systems • yields the equivalent result, i.e., if r The Integration of Information  ... 
doi:10.1145/239041.239045 fatcat:dmfa4ouxcvebzd3ceedmnrzxf4

Enhancing retrieval with hyperlinks: A general model based on propositional argumentation systems

Justin Picard, Jacques Savoy
2003 Journal of the American Society for Information Science and Technology  
This article proposes a general model for using hyperlinks based on Probabilistic Argumentation Systems, in which each of the above-mentioned techniques can be stated.  ...  Fast, effective, and adaptable techniques are needed to automatically organize and retrieve information on the ever-increasing World Wide Web.  ...  Probabilistic argumentation systems is a technique for dealing with uncertain knowledge, by integrating propositional logic with probability theory.  ... 
doi:10.1002/asi.10215 fatcat:lul3kl62nnd53m33duuprxa6e4

Modeling and combining evidence provided by document relationships using probabilistic argumentation systems

Justin Picard
1998 Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '98  
This model is based o n «Probabilistic Argumentation Systems », a technique which combines logic and probability to handle uncertainty.  ...  This paper introduces a new and sound model for representing and handling hypertext links in IR.  ...  Our proposed modeling is based on a technique called Probabilistic Argumentation Systems (PAS) [KH96] .  ... 
doi:10.1145/290941.290989 dblp:conf/sigir/Picard98 fatcat:wxvmmj3menbqpg2irz7vzlqdya

A probabilistic relational model for the integration of IR and databases

Norbert Fuhr
1993 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '93  
In this paper, a probabilistic relational model is presented which combines relational algebra with probabilistic retrieval.  ...  Furthermore, a special jom operator implementing probabilistic retrieval 1s proposed.  ...  In order to ease the following dis- Here we concentrate only on the differences to standard relational algebra (see a textbook on database systems, e.g [Date 90]).  ... 
doi:10.1145/160688.160754 dblp:conf/sigir/Fuhr93 fatcat:ltivbn5oabbflptj4n7x7jrtoe

Probability Based Clustering for Document and User Properties [article]

Thomas Mandl, Christa Womser-Hacker
2011 arXiv   pre-print
This article presents a model based on overlapping probabilistic or fuzzy clusters for such features. The model is applied within a fusion method which linearly combines several retrieval systems.  ...  Information Retrieval systems can be improved by exploiting context information such as user and document features.  ...  Unlike other user models in information retrieval, MIMOR introduces an adaption in the core of an information retrieval system and applies it to the calculation of the RSV.  ... 
arXiv:1102.3865v1 fatcat:63gil7lz5bdhpkjmhsivisveji

DOLORES

Norbert Fuhr, Norbert Gövert, Thomas Rölleke
1998 Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '98  
We describe the design and implementation of a system for logic-based multimedia retrieval.  ...  Based on a probabilistic four-valued logic, POOL uses an implicit open world assumption, allows for closed world assumptions and is able to deal with inconsistent knowledge.  ...  Most multimedia information systems are based on (object-oriented) database management systems.  ... 
doi:10.1145/290941.291005 dblp:conf/sigir/FuhrGR98 fatcat:geg4kpqmw5eaje3xf2am25535u

Collective Intelligence: It's All in the Numbers

K.S. Jones
2006 IEEE Intelligent Systems  
For example, the mechanisms underpinning current probabilistic information retrieval systems are designed to deliver texts that the user hopefully will like.  ...  Information retrieval systems are not currently seen as AI systems. But whatever they cannot do now, we would like them to be intelligent information systems.  ... 
doi:10.1109/mis.2006.43 fatcat:lecdc4avafhv3l5owgxhaggodi

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  
), 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  ...  This paper presents a probabilistic relational modelling (implementation) of the major probabilistic retrieval models.  ...  Retrieval Models Retrieval models form a crucial part of information retrieval. We mainly distinguish between two classes: non-probabilistic and probabilistic models.  ... 
doi:10.1007/s00778-007-0073-y fatcat:qiexpftcfvgs7eonakx3xocb7e

A Linguistically Motivated Probabilistic Model of Information Retrieval [chapter]

Djoerd Hiemstra
1998 Lecture Notes in Computer Science  
This paper presents a new probabilistic model of information retrieval. The most important modeling assumption made is that documents and queries are defined by an ordered sequence of single terms.  ...  This assumption is not made in well known existing models of information retrieval, but is essential in the field of statistical natural language processing.  ...  Wessel Kraaij of The Netherlands Organisation for Applied Scientific Research (TNO) for discussions on information retrieval.  ... 
doi:10.1007/3-540-49653-x_34 fatcat:nesghexv7fekjepzuludlxfvpi

Solving the Enterprise TREC Task with Probabilistic Data Models

Jan Frederik Forst, Anastasios Tombros, Thomas Rölleke
2006 Text Retrieval Conference  
Furthermore, our system highlights the integration of database technology with information retrieval (DB+IR).  ...  Expert identification has become an important information retrieval task. We present and investigate a number of approaches for identifying an expert.  ...  This report will highlight the integration of probabilistic information retrieval models with SQL and Datalog expressions commonly found in the DBMS realm.  ... 
dblp:conf/trec/ForstTR06 fatcat:uyia6nugdjcs5aymsk3hfqy5ey

Mean Field Approach to a Probabilistic Model in Information Retrieval

Bin Wu, K. Y. Michael Wong, David Bodoff
2002 Neural Information Processing Systems  
We study an explicit parametric model of documents, queries, and relevancy assessment for Information Retrieval (IR).  ...  The algorithm is further evaluated on several benchmark databases by comparing with standard algorithms in IR.  ...  In this respect, probabilistic models have become very useful in empowering information searches [1, 2] .  ... 
dblp:conf/nips/WuWB02 fatcat:5jspngucdrfunlfohgljtawhaq

A probabilistic justification for using tf�idf term weighting in information retrieval

Djoerd Hiemstra
2000 International Journal on Digital Libraries  
This paper presents a new probabilistic model of information retrieval. The most important modeling assumption made is that documents and queries are defined by an ordered sequence of single terms.  ...  This assumption is not made in well-known existing models of information retrieval, but is essential in the field of statistical natural language processing.  ...  The term discrimination model has been criticised because it does not exhibit well substantiated theoretical properties. This in contrast with the probabilistic model of information retrieval . . .  ... 
doi:10.1007/s007999900025 fatcat:rdeytwkminc5rpykldvi75mcla

Perceptual consciousness and cognitive access from the perspective of capacity-unlimited working memory

Steven Gross
2018 Philosophical Transactions of the Royal Society of London. Biological Sciences  
Finally, it discusses the problem of relating seemingly non-probabilistic perceptual consciousness to the probabilistic representations posited by the models that challenge conceptions of cognitive access  ...  This paper argues that abandoning the assumption undermines post-cue -based 'overflow' arguments, according to which perceptual consciousness is rich and does not require cognitive access.  ...  the problem that some system needs to solve.  ... 
doi:10.1098/rstb.2017.0343 pmid:30061457 fatcat:4py5cx42b5burek3xopgqrgphe
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