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Integration of probabilistic fact and text retrieval

Norbert Fuhr
1992 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '92  
In this paper, a model for combining text and fact retrieval is described. A query is a set of conditions, where a single condition is either a text or fact condition.  ...  These indexing weights are used in retrieval for a probabilistic ranking of objects basedon the retrieval-with-probabilistic-indexing (RPI) model, for which a new derivation is given here. 2  ...  command in order to show elements of the answer. 7 Conclusions and outlook In this paper, we have described a probabilistic approach for integrating text and fact retrieval.  ... 
doi:10.1145/133160.133202 dblp:conf/sigir/Fuhr92 fatcat:52vfw6znnrf4nlfpd4i7zlszru

Information Extraction and Linking in a Retrieval Context [chapter]

Marie-Francine Moens, Djoerd Hiemstra
2009 Lecture Notes in Computer Science  
text and multimedia data with semantics, the integration of the extraction technologies into ranking models for information retrieval, and of several illustrating retrieval applications.  ...  In 2008 she lectured the course Text Mining, Information and Fact Extraction at RuSSIR'2008: the 2nd Russian Summer School in Information Retrieval.  ... 
doi:10.1007/978-3-642-00958-7_93 fatcat:r6g2o7rkfnc4jbckz46u43zqrq

Probabilistic multimedia retrieval

Thijs Westerveld
2002 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '02  
We present a framework in which probabilistic models for textual and visual information retrieval can be integrated seamlessly.  ...  The underlying Language Models for text and Gaussian Mixture Models for images have proven successful in various retrieval tasks.  ...  CONCLUSION We presented a framework in which probabilistic models for textual and visual retrieval are integrated seamlessly.  ... 
doi:10.1145/564376.564482 dblp:conf/sigir/Westerveld02 fatcat:zjllgc3klnf67dmoqo2gq55plu

Probabilistic Modeling of Vague Conditions in Interactive Product Search

Alfred Sliwa
2019 BCS-IRSG Symposium on Future Directions in Information Access  
We argue that leveraging probabilistic modeling techniques and especially user-driven UI development can optimize the overall retrieval quality.  ...  However, many systems support retrieval of items fulfilling Boolean conditions so that only exact matching leads to the inclusion in the result list.  ...  In [3] probabilistic models are used to integrate text and fact retrieval where both text and fact conditions are treated similarly and vague but separately.  ... 
dblp:conf/fdia/Sliwa19 fatcat:h5hocg7ctrbmtm2s3ltwlm7gly

Scalable DB+IR Technology: Processing Probabilistic Datalog with HySpirit

Ingo Frommholz, Thomas Roelleke
2016 Datenbank-Spektrum  
Making PDatalog work in real-world applications requires more than probabilistic facts and rules, and the semantics associated with the evaluation of the programs.  ...  Probabilistic Datalog (PDatalog, proposed in 1995) is a probabilistic variant of Datalog and a nice conceptual idea to model Information Retrieval in a logical, rule-based programming paradigm.  ...  Full-text Search A potential application of the Bayes operator is a probabilistic variant of the famous TF-IDF ranking formula widely used in information retrieval.  ... 
doi:10.1007/s13222-015-0208-z pmid:29368760 pmcid:PMC5750817 fatcat:kdieshgrbfhypiqqfvu2s7nnhm

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  ...  Based on intensional semantics, the tuple weights of the result of a PRA expression always conform to the underlying probabilistic model.  ...  Rabitti and Savino [1990] describe an advanced system for retrieval of multimedia data (including facts). Their system uses probabilistic retrieval for text as well as for facts.  ... 
doi:10.1145/239041.239045 fatcat:dmfa4ouxcvebzd3ceedmnrzxf4

Probability Based Clustering for Document and User Properties [article]

Thomas Mandl, Christa Womser-Hacker
2011 arXiv   pre-print
The extension presented in this article allows overlapping, probabilistic clusters of features to further refine the process.  ...  Information Retrieval systems can be improved by exploiting context information such as user and document features.  ...  Domain and text type may also be useful. Research will discover more properties in the future. The extended MIMOR model leaves room for the integration of several other features.  ... 
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.  ...  As highlevel logic for retrieval of hypermedia documents, we have developed a probabilistic object-oriented logic (POOL) which supports aggregated objects, different kinds of propositions (terms, classifications  ...  On the other hand, both approaches deal with nested objects, and the retrieval strategy of the FMM is already integrated in POOL.  ... 
doi:10.1145/290941.291005 dblp:conf/sigir/FuhrGR98 fatcat:geg4kpqmw5eaje3xf2am25535u

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.  ...  We may consider each modality as a projection of the same object (video) and integrate information from the projections.  ...  In fact, if we look at (X 1 , F 1 , f 1 ) and (X 2 , F 2 , f 2 ) as probabilistic models for two rank lists from different modalities, F 1 and F 2 are the mixed distributions, and f 1 and f 2 are likelihood  ... 
doi:10.1007/11795131_3 fatcat:wo4qvdwa4fasfkejxhrjiw6ici

Information Retrieval in Life Sciences: The LAILAPS Search Engine

Matthias Lange, Jinbo Chen, Uwe Scholz
2012 Jahrestagung der Gesellschaft für Informatik  
Flemming and H. Miehe as administrator of the project website, Tomcat engine, and Maven developer pipeline.  ...  To consider the fact that data relevance is highly subjective to the user of an information retrieval system, we support specific neural networks.  ...  Another approach is probabilistic relevancy ranking [ILDF07] , whereby probabilistic values for the relevance of database fields and word combinations have to be predefined.  ... 
dblp:conf/gi/LangeCS12 fatcat:ylex65ivf5ffhnhpcusybjkw5a

Anchor text mining for translation of Web queries

Wen-Hsiang Lu, Lee-Feng Chien, Hsi-Jian Lee
2004 ACM Transactions on Information Systems  
through the mining of Web anchor texts and link structures.  ...  the cross-language retrieval performance, and is very useful when the considered language pairs lack a sufficient number of anchor texts.  ...  Mark Sanderson and the anonymous reviewers for their valuable comments and suggestions. Many thanks are given to Mr.  ... 
doi:10.1145/984321.984324 fatcat:75mnaq3qmza6vdduluhn3yhm5m

Models for Integrated Information Retrieval and Database Systems

Norbert Fuhr
1996 IEEE Data Engineering Bulletin  
Its scope includes the design, implementation, modelling, theory and application of database systems and their technology.  ...  The Bulletin of the Technical Committee on Data Engineering is published quarterly and is distributed to all TC members.  ...  Acknowledgments The author would like to thank Tore Bratvold, UBILAB, and Andreas Geppert from the University Zurich for many fruitful discussions on the design of FIRE and the integration of DBMSs and  ... 
dblp:journals/debu/Fuhr96 fatcat:hrztyc7oi5ddzdvxxdvs3r7nja

An approach to natural language for document retrieval

B. Croft
1987 Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '87  
Document retrieval systems have been restricted, by the nature of tile task, to techniques that can be used with large numbers of documents and broad domains.  ...  The proposed NLP techniques are used to develop a request model based on "conceptual case frames" and to compare this model with the texts of candidate documents.  ...  We would like to thank Wendy Lehnert and Daniel Suthers for their advice on the parser, and on REST, respectively.  ... 
doi:10.1145/42005.42009 dblp:conf/sigir/CroftL87 fatcat:yddpk576ljcmhbwbubk6n36cx4

Probabilistic optimized ranking for multimedia semantic concept detection via RVM

Yan-Tao Zheng, Shi-Yong Neo, Tat-Seng Chua, Qi Tian
2008 Proceedings of the 2008 international conference on Content-based image and video retrieval - CIVR '08  
Most existing concept detection systems utilize Support Vector Machines (SVM) to perform the detection and ranking of retrieved video shots.  ...  The probability output of RVM on individual uni-modal features also facilitates probabilistic fusion of multi-modal evidences to minimize Bayes risk.  ...  of CM, WT, BoW, text and feature fusion respectively.  ... 
doi:10.1145/1386352.1386378 dblp:conf/civr/ZhengNCT08 fatcat:66as6qbcqzdpfahxlqkcy2k6vm

LANGUAGE MODEL FOR DIGITAL RECOURSE OBJECTS RETRIEVAL

ABDULLAH HJ TALIB WAFA ZAAL ALMAAITAH
2019 Zenodo  
Language model has been approved outperforms of other retrieval model such as vector space model and probabilistic model.  ...  This paper presents a performance comparison among information retrieval models (Vector Space Model and Probabilistic Model) using a Digital Resource Objects (CHiC2013 collection).  ...  ACKNOWLEDGMENT The authors would like to acknowledge the support of Universiti Sains Malaysia for this research under the Research University Grant entitled "A Two-Stage Expansion Method for Retrieval  ... 
doi:10.5281/zenodo.3256408 fatcat:oaqlyseu6rf7pjzxmacqkedusa
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