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Attribute extraction and scoring: A probabilistic approach

Taesung Lee, Zhongyuan Wang, Haixun Wang, Seung-won Hwang
2013 2013 IEEE 29th International Conference on Data Engineering (ICDE)  
To the best of our knowledge, ours is the first approach to integrate concept-and instance-based patterns into probabilistic typicality scores that scale to broad concept space.  ...  Knowledge bases, which consist of concepts, entities, attributes and relations, are increasingly important in a wide range of applications.  ...  CONCLUSION In this paper, we proposed a framework for extracting attributes from multiple data sources and computing probabilistic scores.  ... 
doi:10.1109/icde.2013.6544825 dblp:conf/icde/LeeWWH13 fatcat:cynig2u2cbgz3d27zqtdf6d5pu

A Unified Approach to Ranking in Probabilistic Databases [article]

Jian Li, Barna Saha, Amol Deshpande
2010 arXiv   pre-print
In this paper, we present a unified approach to ranking and top-k query processing in probabilistic databases by viewing it as a multi-criteria optimization problem, and by deriving a set of features that  ...  We contend that a single, specific ranking function may not suffice for probabilistic databases, and we instead propose two parameterized ranking functions, called PRF-w and PRF-e, that generalize or can  ...  Attribute Uncertainty or Uncertain Scores We briefly sketch how we can do ranking over tuples with discrete attribute uncertainty where the uncertain attributes are part of the tuple scoring function (  ... 
arXiv:0904.1366v4 fatcat:stibxrhwtrcabbgqhvsibmqcua

Cyclist Intention Detection: A Probabilistic Approach [article]

Stefan Zernetsch, Hannes Reichert, Viktor Kress, Konrad Doll, Bernhard Sick
2021 arXiv   pre-print
This article presents a holistic approach for probabilistic cyclist intention detection.  ...  We compare our method to a single model approach which produces forecasts in the form of Gaussian distributions and show that our method is able to produce more reliable and sharper outputs while retaining  ...  CONCLUSIONS AND FUTURE WORK In this article, we presented a new approach to perform probabilistic cyclist intention detection.  ... 
arXiv:2104.09176v1 fatcat:5ifvjnvnwnf6tlqaiwrmtuukrq

Facial feature extraction using a probabilistic approach

Mustafa Berkay Yilmaz, Hakan Erdogan, Mustafa Unel
2012 Signal processing. Image communication  
In this work, we propose a probabilistic framework and several methods which can extract critical points on a face using both location and texture information.  ...  We perform extensive experiments to show that the new methods outperform the conventional approaches in facial feature extraction accuracy.  ...  Acknowledgments This work has been supported by TUBITAK (Scientific and Technical Research Council of Turkey); research support program (program code 1001), project number 107E015.  ... 
doi:10.1016/j.image.2012.03.003 fatcat:vr6jvd4dxrfhrbqqu3u3vvshz4

A Probabilistic Approach for Integrating Heterogeneous Knowledge Sources [chapter]

Arnab Dutta, Christian Meilicke, Simone Paolo Ponzetto
2014 Lecture Notes in Computer Science  
Our approach is unsupervised in nature and relies on two key components. First, we automatically acquire probabilistic type information for Nell terms given a set of matching hypotheses.  ...  Experimental results on gold-standard data indicate that our approach outperforms a strong baseline, and is able to produce everimproving mappings consistently across iterations.  ...  Acknowledgments We thank Mathias Niepert for his contributions and valuable feedback on this work.  ... 
doi:10.1007/978-3-319-07443-6_20 fatcat:3inw5oghifehxfyb2skv764aem

A Probabilistic Approach to Uncovering Attributed Graph Anomalies [chapter]

Nan Li, Huan Sun, Kyle Chipman, Jemin George, Xifeng Yan
2014 Proceedings of the 2014 SIAM International Conference on Data Mining  
In this paper, we introduce a probabilistic model to identify anomalous subgraphs containing a significantly different percentage of a certain vertex attribute, such as a specific disease or an intrusion  ...  Our framework, gAnomaly, models generative processes of vertex attributes and divides the graph into regions that are governed by background and anomaly processes.  ...  The views and conclusions contained herein are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or  ... 
doi:10.1137/1.9781611973440.10 dblp:conf/sdm/LiSCGY14 fatcat:svkjuzia5bdathdxnxkokiafsy

Top-K Deep Video Analytics: A Probabilistic Approach [article]

Ziliang Lai, Chenxia Han, Chris Liu, Pengfei Zhang, Eric Lo, Ben Kao
2021 arXiv   pre-print
Everest ranks and identifies the most interesting frames/moments from videos with probabilistic guarantees.  ...  Everest is a system built with a careful synthesis of deep computer vision models, uncertain data management, and Top-K query processing.  ...  Since model inference results are intrinsically probabilistic, Everest treats inference score distribution as a first-class citizen so that it can offer probabilistic guarantees (e.g., guaranteeing a Top-K  ... 
arXiv:2003.00773v3 fatcat:kq77zqrdbralnnngivh4cyks2a

A unified approach to ranking in probabilistic databases

Jian Li, Barna Saha, Amol Deshpande
2011 The VLDB journal  
In this paper, we present a unified approach to ranking and top-k query processing in probabilistic databases by viewing it as a multi-criteria optimization problem, and by deriving a set of features that  ...  We contend that a single, specific ranking function may not suffice for probabilistic databases, and we instead propose two parameterized ranking functions, called P RF ω and P RF e , that generalize or  ...  Acknowledgements: This work was supported in part by NSF under Grants CCF-0728839 and IIS-0546136.  ... 
doi:10.1007/s00778-011-0220-3 fatcat:i3i7xifynfcaro2j3jxc5sw3vy

A unified approach to ranking in probabilistic databases

Jian Li, Barna Saha, Amol Deshpande
2009 Proceedings of the VLDB Endowment  
In this paper, we present a unified approach to ranking and top-k query processing in probabilistic databases by viewing it as a multi-criteria optimization problem, and by deriving a set of features that  ...  We contend that a single, specific ranking function may not suffice for probabilistic databases, and we instead propose two parameterized ranking functions, called P RF ω and P RF e , that generalize or  ...  Acknowledgements: This work was supported in part by NSF under Grants CCF-0728839 and IIS-0546136.  ... 
doi:10.14778/1687627.1687685 fatcat:ru7m3c35bnbvnfj3fbhkimdtaa

A Probabilistic Fusion Approach to human age prediction

Guodong Guo, Yun Fu, Charles R. Dyer, Thomas S. Huang
2008 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops  
In this paper we propose a Probabilistic Fusion Approach (PFA) that produces a high performance estimator for human age prediction. The PFA framework fuses a regressor and a classifier.  ...  Experiments on the large UIUC-IFP-Y aging database and the FG-NET aging database show the merit of the proposed approach to human age prediction.  ...  Facial attributes play a crucial role in applications including multimedia communication and Human-Computer Interaction (HCI).  ... 
doi:10.1109/cvprw.2008.4563041 dblp:conf/cvpr/GuoFDH08 fatcat:nj7o7p7vnvd5doz6sw2jo2ewie

A Probabilistic Approach for Image Retrieval Using Descriptive Textual Queries

Yashaswi Verma, C.V. Jawahar
2015 Proceedings of the 23rd ACM international conference on Multimedia - MM '15  
., "a brown cat sleeping on a sofa"), or even long descriptions with multiple sentences. We present a probabilistic approach that seamlessly integrates visual and textual information for the task.  ...  It relies on linguistically and syntactically motivated mid-level textual patterns (or phrases) that are automatically extracted from available descriptions.  ...  Rather than considering objects, attributes, verb, preposition, etc. from a sentence in a piece-wise manner, we extract relation tuples or phrases 1 .  ... 
doi:10.1145/2733373.2806289 dblp:conf/mm/VermaJ15 fatcat:pgrdsvtaqzb77b7fxuoiqxtlda

Referring Expressions with Rational Speech Act Framework: A Probabilistic Approach [article]

Hieu Le, Taufiq Daryanto, Fabian Zhafransyah, Derry Wijaya, Elizabeth Coppock, Sang Chin
2022 arXiv   pre-print
This paper applies a combination of the probabilistic RSA framework and deep learning approaches to larger datasets involving complex visual scenes in a multi-step process with the aim of generating better-explained  ...  We carry out experiments on the RefCOCO and RefCOCO+ datasets and compare our approach with other end-to-end deep learning approaches as well as a variation of RSA to highlight our key contribution.  ...  Since Detectron2 and Graph-RCNN output likelihood values for attributes and types for each object as shown in Figure 2 , the last step in the textual extraction process is using a cutoff threshold to  ... 
arXiv:2205.07795v1 fatcat:rlm2fslu75e6ncwyejsogjpfje

PARI: A Probabilistic Approach to AS Relationships Inference [article]

Guoyao Feng, Srinivasan Seshan, Peter Steenkiste
2019 arXiv   pre-print
In this paper, we analyze the factors contributing to this uncertainty and introduce a new paradigm to explicitly model the uncertainty and reflect it in the inference result.  ...  While the recent works have achieved increasingly higher accuracy, there has not been a systematic study on the uncertainty of AS relationship inference.  ...  Moreover, PARI's probabilistic inference outperforms a naïve approach to expressing uncertainty.  ... 
arXiv:1905.02386v1 fatcat:7otqz7y3vrczxjhhutpwwl4t44

A Probabilistic Approach to Lexical Semantic Knowledge Acquisition and S tructural Disambiguation [article]

Hang LI
1998 arXiv   pre-print
The approach I adopt has the following characteristics: (1) dividing the problem into three subproblems: case slot generalization, case dependency learning, and word clustering (thesaurus construction)  ...  of a high-performance disambiguation method.  ...  Briscoe and Carroll (1997) extracted case frames by using a probabilistic LR parser.  ... 
arXiv:cs/9812001v3 fatcat:mtjvcuk3jff3jeiakclq5uclw4

A Probabilistic Latent Factor approach to service ranking

Gilbert Cassar, Payam Barnaghi, Klaus Moessner
2011 2011 IEEE 7th International Conference on Intelligent Computer Communication and Processing  
In this paper we investigate the use of probabilistic machine-learning techniques to extract latent factors from semantically enriched service descriptions.  ...  This approach is scalable to large service repositories and provides an efficient mechanism for publishing and new services after the system is deployed.  ...  Wei Wang from the University of Nottingham Malaysia Campus for his comments and suggestions.  ... 
doi:10.1109/iccp.2011.6047850 dblp:conf/iccp2/CassarBM11 fatcat:cgrfjix7e5fmzh5ld3ij3e6dfq
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