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Integrating Structure in the Probabilistic Model for Information Retrieval

Mathias Gery, Christine Largeron, Franck Thollard
2008 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology  
We propose in this article to extend the classical IR probabilistic model in order to take into account the structure through the weighting of tags.  ...  In databases or in the World Wide Web, many documents are in a structured format (e.g. XML).  ...  Modelling document structure In information retrieval, the probabilistic model [17] aims at estimating the relevance of a document for a given query through two probabilities: the probability of finding  ... 
doi:10.1109/wiiat.2008.346 dblp:conf/webi/GeryLT08 fatcat:psdngrsv5jgevg3mc5zmczxgpy

Monolingual and Cross-Lingual Probabilistic Topic Models and Their Applications in Information Retrieval [chapter]

Marie-Francine Moens, Ivan Vulić
2013 Lecture Notes in Computer Science  
Their probabilistic framework allows for their easy integration into a language modeling framework for monolingual and crosslingual information retrieval.  ...  The tutorial also demonstrates how semantically similar words across languages are integrated as useful additional evidences in cross-lingual information retrieval models.  ...  -Come to know how to integrate the knowledge from probabilistic topic models into probabilistic models for information retrieval in both monolingual and cross-lingual settings.  ... 
doi:10.1007/978-3-642-36973-5_106 fatcat:bnk7t6l3zjfmval53l3lu5bbym

The HySpirit retrieval platform

Thomas Rölleke, Ralf Lübeck, Gabriella Kazai
2001 Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '01  
Between 1993Between -1999 , the foundations of the retrieval platform HySpirit (HYpermedia System with Probabilistic Inference for the Retrieval of InformaTion) were developed at the University of Dortmund  ...  structure of documents for retrieving best entry points into documents. • Support knowledge-oriented retrieval in semi-structured and heterogeneous data sources. • Integrate fact-oriented and content-oriented  ...  Between 1993-1999, the foundations of the retrieval platform HySpirit (HYpermedia System with Probabilistic Inference for the Retrieval of InformaTion) were developed at the University of Dortmund.  ... 
doi:10.1145/383952.384095 dblp:conf/sigir/RollekeLK01 fatcat:tcm3lndckzew7m5eypuy6uqlye

Information Extraction and Linking in a Retrieval Context [chapter]

Marie-Francine Moens, Djoerd Hiemstra
2009 Lecture Notes in Computer Science  
retrieval; -Be able to integrate the (probabilistic) content models into the ranking models; -Be able to choose a model for retrieval that is well-suited for a particular task and to integrate the necessary  ...  Another challenge is to integrate content recognition and content retrieval as much as possible, for instance by using the probabilistic output from the information extraction tools in the retrieval phase  ... 
doi:10.1007/978-3-642-00958-7_93 fatcat:r6g2o7rkfnc4jbckz46u43zqrq

Introduction to the special issue on database and information retrieval integration

W. Bruce Croft, Hans-J. Schek
2007 The VLDB journal  
A number of approaches have been suggested, both from the database and information retrieval (IR) perspective, but the motivation for finding a solution or solutions that work has grown tremendously since  ...  There are many possibilities for integration such as extending a database model to more effectively deal with probabilities, extending an IR model to handle more complex structures and multiple relations  ...  Probabilistic models for IR that used structure-based evidence were also developed (Croft and Turtle 1992 [7] ).  ... 
doi:10.1007/s00778-007-0074-x fatcat:ld66ny4vvrbuze7hwhhl7xu2ca

Information Retrieval System and challenges with Dataspace

Niranjan Lal, Samimul Qamar, Savita Shiwani
2016 International Journal of Computer Applications  
are used in data integration for the purpose of integrating information systems, at the same is not cost effective.  ...  Information Retrieval from heterogeneous information systems is required but challenging at the same as data is stored and represented in different data models in different information systems.  ...  We can choose one of the models for Information Retrieval models for Dataspace as discussed above.  ... 
doi:10.5120/ijca2016911128 fatcat:azjcen5w75gmxejhgc6kd6s7h4

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

Holger H. Hoos, Kai Renz, Marko Görg
2001 Zenodo  
Probabilistic Models The music information retrieval approach taken here is based on the general idea of characterising and summarising musical structure using probabilistic models.  ...  Generally, the key idea of information retrieval based on probabilistic models is the following: Given a piece and a probabilistic model !  ... 
doi:10.5281/zenodo.1417516 fatcat:jr6zhy6l3ngqfhpna4mkbswtny

Probabilistic information retrieval model for a dependency structured indexing system

Changki Lee, Gary Geunbae Lee
2005 Information Processing & Management  
However, independence assumption is obviously and openly understood to be wrong, so we present a new method of incorporating term dependence in probabilistic retrieval model by adapting a structural index  ...  Most previous information retrieval (IR) models assume that terms of queries and documents are statistically independent from each another.  ...  Using no relevance information In the probabilistic retrieval model, if the relevant information is not available, we can generally assume that R<<N.  ... 
doi:10.1016/j.ipm.2003.11.001 fatcat:akibwtrilnaxxidxg5kmzox7ji

Page 55 of Library & Information Science Abstracts Vol. , Issue 5 [page]

1990 Library & Information Science Abstracts  
Probability estimation is important for the application of probabilistic models as well as for any evaluation in information retrieval.  ...  Most currently used information retrieval models are unsuitable to describe and integrate many recent techniques, namely those for semantic-based retrieval.  ... 

Hierarchical Machine Learning – A Learning Methodology Inspired by Human Intelligence [chapter]

Ling Zhang, Bo Zhang
2006 Lecture Notes in Computer Science  
Specifically, we propose the Probabilistic Model Supported Rank Aggregation (PMSRA) method to accomplish this integration.  ...  One of the strategies for cross-modal learning is to integrate information from different sense modalities. The second problem is how to integrate the results from different modalities.  ...  In the video retrieval, this integration is a kind of classifier combination problem, which we propose a Probabilistic Model Supported Rank Aggregation (PMSRA) method to address.  ... 
doi:10.1007/11795131_3 fatcat:wo4qvdwa4fasfkejxhrjiw6ici

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 main findings are that the PSQL/PRA paradigm allows for the description of advanced retrieval models, is suitable for solving large-scale retrieval tasks, and outperforms traditional SQL in terms of  ...  This paper presents a probabilistic relational modelling (implementation) of the major probabilistic retrieval models.  ...  We thank Mounia Lalmas for her thorough editorial pass, and Ingo Frommholz for his technical improvements and tests.  ... 
doi:10.1007/s00778-007-0073-y fatcat:qiexpftcfvgs7eonakx3xocb7e

Modelling Vague Content and Structure Querying in XML Retrieval with a Probabilistic Object-Relational Framework [chapter]

Mounia Lalmas, Thomas Rölleke
2004 Lecture Notes in Computer Science  
In this paper, we use a probabilistic object-relational framework to model representation and retrieval strategies that take into account vagueness at both content and structure level.  ...  Many XML retrieval applications require relevance-oriented ranking of retrieved elements in order to capture the vagueness inherent to the information retrieval process.  ...  It is well known in information retrieval that users of retrieval systems often find it difficult to express their need for information in form of a query because they can be uncertain about the information  ... 
doi:10.1007/978-3-540-25957-2_34 fatcat:4etmybrt4jdlvht5nksvdixwji

On the Convergence of Structured Search, Information Retrieval and Trust Management in Distributed Systems [chapter]

Karl Aberer, Philippe Cudré-Mauroux, Zoran Despotovic
2005 Lecture Notes in Computer Science  
The database and information retrieval communities have long been recognized as being irreconcilable.  ...  from an information retrieval context.  ...  , the predominant model for modern text retrieval.  ... 
doi:10.1007/11550648_1 fatcat:nhplwe343jd2vfeeyx2hyjgksu

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.  ...  The fusion is based on weights for the different retrieval systems which are learned by exploiting relevance feedback information.  ...  For information retrieval tasks, this means the integration of different probabilities for the relevance of a document.  ... 
arXiv:1102.3865v1 fatcat:63gil7lz5bdhpkjmhsivisveji

Probabilistic drug connectivity mapping

Juuso A Parkkinen, Samuel Kaski
2014 BMC Bioinformatics  
We infer the relevance for retrieval by data-driven probabilistic modeling of the drug responses, resulting in probabilistic connectivity mapping, and further consider the available cell lines as different  ...  This can be viewed as an information retrieval task, with the goal of finding the most relevant profiles for a given query drug.  ...  Khan for his useful discussions and insights.  ... 
doi:10.1186/1471-2105-15-113 pmid:24742351 pmcid:PMC4011783 fatcat:mbxzgdvc6jgx3l6i47jufpcvqi
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