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Probabilistic learning for selective dissemination of information

Gianni Amati, Fabio Crestani
1999 Information Processing & Management  
In this paper we describe and evaluate a learning model for information ®ltering which is an adaptation of the generalized probabilistic model of Information Retrieval.  ...  The proposed learning model is the core of a prototype information ®ltering system called ProFile. #  ...  Thanks also to Keith van Rijsbergen for the many and interesting discussions and suggestions on the probabilistic models of IR.  ... 
doi:10.1016/s0306-4573(99)00012-6 fatcat:ztf2bu4ykjhxraw7pso7nz5zn4

Using web helper agent profiles in query generation

Gabriel L. Somlo, Adele E. Howe
2003 Proceedings of the second international joint conference on Autonomous agents and multiagent systems - AAMAS '03  
Toward that end, we are building an information agent called SurfAgent; in previous studies, we have developed and tested methods for automatically learning a user profile [22] .  ...  Ideally, these components can be separated so that a single user profile can be leveraged for a variety of information services.  ...  The United States Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation herein.  ... 
doi:10.1145/860705.860706 fatcat:3k46w2oa4veazjtse3grcfru54

Document filtering with inference networks

Jamie Callan
1996 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '96  
The problems of document retrieval and document ltering are similar at an abstract level, but the architectures required, the optimizations that are possible, and the quality of the information available  ...  Although statistical retrieval models are now accepted widely, there has been little research o n h o w to adapt them to the demands of high speed document ltering.  ...  This research was partially supported by the NSF Center for Intelligent Information Retrieval at the University of Massachusetts, Amherst, by the National Science Foundation, Library of Congress, and Department  ... 
doi:10.1145/243199.243273 dblp:conf/sigir/Callan96 fatcat:sjqjv4objbc45nn62kkc4cyldq

Using web helper agent profiles in query generation

Gabriel L. Somlo, Adele E. Howe
2003 Proceedings of the second international joint conference on Autonomous agents and multiagent systems - AAMAS '03  
Toward that end, we are building an information agent called SurfAgent; in previous studies, we have developed and tested methods for automatically learning a user profile [22] .  ...  Ideally, these components can be separated so that a single user profile can be leveraged for a variety of information services.  ...  The United States Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation herein.  ... 
doi:10.1145/860575.860706 dblp:conf/atal/SomloH03 fatcat:sbvrgoounvd4pp2zvvdxugocyy

Dissimilarity Metric Based on Local Neighboring Information and Genetic Programming for Data Dissemination in Vehicular Ad Hoc Networks (VANETs)

Daniel Gutiérrez-Reina, Vishal Sharma, Ilsun You, Sergio Toral
2018 Sensors  
This paper presents a novel dissimilarity metric based on local neighboring information and a genetic programming approach for efficient data dissemination in Vehicular Ad Hoc Networks (VANETs).  ...  The primary aim of the dissimilarity metric is to replace the Euclidean distance in probabilistic data dissemination schemes, which use the relative Euclidean distance among vehicles to determine the retransmission  ...  Conclusions A new dissimilarity metric based on local neighboring information to be used in probabilistic data dissemination algorithms for VANET urban scenarios has been obtained thanks to a genetic programming  ... 
doi:10.3390/s18072320 pmid:30018267 pmcid:PMC6068898 fatcat:ihpnxltsefegrckb4c5oo6ba2u

Planning and learning algorithms for routing in Disruption-Tolerant Networks

Mark-Oliver Stehr, Carolyn Talcott
2008 MILCOM 2008 - 2008 IEEE Military Communications Conference  
We employ a disciplined two-level approach that clearly distinguishes the dissemination of application content from the dissemination of network-related knowledge, each of which can be supported by different  ...  learning algorithm that takes into account feedback about past performance.  ...  routing, and learning-based routing; Sebastian Guteirrez-Nolasco for improving the simulation component; and Mike Demmer for fixing bugs and implementing several of our suggestions.  ... 
doi:10.1109/milcom.2008.4753336 fatcat:5e4v7n5s6vbstjqqbbh73dns6m

Satisficing in split-second decision making is characterized by strategic cue discounting

Hanna Oh, Jeffrey M. Beck, Pingping Zhu, Marc A. Sommer, Silvia Ferrari, Tobias Egner
2016 Journal of Experimental Psychology. Learning, Memory and Cognition  
Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process.  ...  With increasingly demanding, subsecond time pressures, however, participants systematically discounted a subset of the cue information by dropping the least informative cue(s) from their decision making  ...  (E-F) To control for the effect of priors, Bayesian model selection analysis was repeated using informative priors based on the posterior distributions of the weights computed from the initial learning  ... 
doi:10.1037/xlm0000284 pmid:27253846 fatcat:7xvklusevfdojfiao7e4vm6hji

The development of categorization: Effects of classification and inference training on category representation

Wei (Sophia) Deng, Vladimir M. Sloutsky
2015 Developmental Psychology  
These results are discussed in relation to theories of categorization and the role of selective attention in the development of category learning.  ...  In contrast, regardless of the training condition, 4-year-olds relied on multiple probabilistic features.  ...  the personal use of the individual user and is not to be disseminated broadly. category information (i.e., the overall similarity).  ... 
doi:10.1037/a0038749 pmid:25602938 pmcid:PMC4339312 fatcat:r64g35cf5rhgfcyw34inyonvwm

Special Issue Editorial: Big Data for Mobile Services

Jason J. Jung
2018 Journal on spesial topics in mobile networks and applications  
As data and knowledge volume keep increasing while global means for information dissemination continue to diversify, new methods, modeling paradigms and structures are needed to efficiently mount scalability  ...  from the ever-growing size and complexity of information of all kinds.  ...  As data and knowledge volume keep increasing while global means for information dissemination continue to diversify, new methods, modeling paradigms and structures are needed to efficiently mount scalability  ... 
doi:10.1007/s11036-018-1070-7 fatcat:xmgmgg6w5bcjphrfwqczxpl4ai

Learning while filtering documents

Jamie Callan
1998 Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '98  
This paper examines the problems of learning queries and dissemination thresholds from relevance feedback in a dynamic information filtering environment.  ...  It also presents a new algorithm for learning dissemination thresholds automatically, from the same relevance feedback information used to learn queries.  ...  Acknowledgements I thank Daniella Malin for her assistance in the work described hcrc. This research was partially supported by the NSF Center for Intelligent  ... 
doi:10.1145/290941.290998 dblp:conf/sigir/Callan98 fatcat:jqdnw72whze5naecnoocvi4nbu

Probabilistic category learning in developmental dyslexia: Evidence from feedback and paired-associate weather prediction tasks

Yafit Gabay, Eli Vakil, Rachel Schiff, Lori L. Holt
2015 Neuropsychology  
If the ability to learn from feedback in this procedural learning task is selectively impaired in dyslexia, then we expect selective disruption of probabilistic category learning in the FB variant of the  ...  In all, these results indicate impairment in probabilistic category learning among participants with dyslexia that is not a result of a selective deficit of FB-based learning, since poorer learning relative  ... 
doi:10.1037/neu0000194 pmid:25730732 pmcid:PMC4558403 fatcat:t7oh6likfnfwpdtuzmgmkc5lgq

Mitigating flash crowd effect using connected vehicle technology

Agata Grzybek, Gregoire Danoy, Pascal Bouvry, Marcin Seredynski
2015 Vehicular Communications  
Real-time travel time information is crowd-sourced by TrafficEQ users.  ...  traveling on the link, which in the case of the loss of capacity is unreliable.  ...  which is learned over time.  ... 
doi:10.1016/j.vehcom.2015.10.002 fatcat:3w2mkl2b7rhqfeksytj7jpoo2e

Introduction to the special issue on statistical and probabilistic methods for user modeling

David Albrecht, Ingrid Zukerman
2007 User modeling and user-adapted interaction  
opportunities for information dissemination and information gathering.  ...  Statistical and probabilistic models are concerned with the use of observed sample results to make statements about unknown, dependent parameters.  ...  Their experimental framework also includes a meta-learning approach that selects the best model based on past performance and features of the data.  ... 
doi:10.1007/s11257-006-9025-2 fatcat:gyokztyecbgczf5bdtoswjcm6q

PROBCAST: A Web-Based Portal to Mesoscale Probabilistic Forecasts

Clifford Mass, Susan Joslyn, John Pyle, Patrick Tewson, Tilmann Gneiting, Adrian Raftery, Jeff Baars, J. M. Sloughter, David Jones, Chris Fraley
2009 Bulletin of The American Meteorological Society - (BAMS)  
Based on research by University of Washington psychologists and humaninterface specialists, a web site has been constructed that allows access to key elements of the probabilistic information.  ...  The design approach of the PROBCAST system is explained in this paper, as well as some of the challenges for future development.  ...  Acknowledgements This research has been supported by the Department of Defense MURI program, the National Science Foundation (Grant No.  ... 
doi:10.1175/2009bams2775.1 fatcat:rlgwgnpnxjaeppbsbq6xcvz4q4

Decoding the population dynamics underlying ocular following response using a probabilistic framework

Laurent U Perrinet, Guillaume S Masson
2009 BMC Neuroscience  
Using this velocity map, we progressively learn the dependence of local velocities in a second layer of the model.  ...  surrounded by an antagonistic modulation and (ii) a direction selective suppressive effect of the surround on the contrast gain control of the central stimuli [3] .  ...  can read your work free of charge"BioMed Central will be the most significant development for disseminating the results of biomedical researc h in our lifetime."  ... 
doi:10.1186/1471-2202-10-s1-p359 fatcat:rrjclaaplfccjgn4gjcmorivxu
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