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Application and Evaluation of a Conditioned Hidden Markov Model for Estimating Interaction Quality of Spoken Dialogue Systems
[chapter]
2013
Natural Interaction with Robots, Knowbots and Smartphones
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account
• Our approach:
-Models which take into account temporal dependencies and previous
values inherently
• Hidden Markov Model
• Conditioned Hidden Markov Model
• Often: one class per HMM ...
• Observation sequence probability
Start
Hidden Markov Model (HMM)
Motivation | IQ | CHMM | Experiment | Conclusion
S1
S2
Conditioned Hidden Markov Model (CHMM) (Glodek et al., Interspeech 2011 ...
doi:10.1007/978-1-4614-8280-2_27
fatcat:chgotrfxojgjvm5lzy4oqxdkx4
Marimba: A Tool for Verifying Properties of Hidden Markov Models
[chapter]
2015
Lecture Notes in Computer Science
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The formal verification of properties of Hidden Markov Models (HMMs) is highly desirable for gaining confidence in the correctness of the model and the corresponding system. ...
A significant step towards HMM verification was the development by Zhang et al. of a family of logics for verifying HMMs, called POCTL*, and its model checking algorithm. ...
Introduction A Hidden Markov Model (HMM) is an extension of a Discrete Time Markov Chain (DTMC) where the states of the model are hidden but the observations are visible. ...
doi:10.1007/978-3-319-24953-7_14
fatcat:uziot5sabbgvjg7asgp7prh4py
Modeling search processes using hidden states in collaborative exploratory web search
2014
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing - CSCW '14
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Author Keywords Collaborative information behavior; exploratory search; Hidden Markov Model; information seeking process. ...
Our results showed that the identified hidden patterns of search process through HMM are compatible with previous well-known models. ...
The Markov model is built on four pre-defined Areas of Interests (AOIs). The Hidden Markov Model (HMM) is a well-established model with mature techniques for parameter estimation. ...
doi:10.1145/2531602.2531658
dblp:conf/cscw/YueHH14
fatcat:m6lodxa7rvewjiwmkw4qw4aq4a
Analysis of Temporal Features for Interaction Quality Estimation
[article]
2016
arXiv
pre-print
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Furthermore, for the feature sub-group modeling the temporal effects with a window, we modify the window size increasing the overall performance significantly by +15.69%. ...
We extend the set of temporal features to contain the system and the user view. ...
[3] uses Hidden Markov Models (HMMs) to model the SDS as a process evolving over time. User Satisfaction was predicted at any point within the dialogue on a 5 point scale. ...
arXiv:1604.01985v1
fatcat:63ayuemcxbdr3gawsjdblwvoqi
Recurrent Neural Network Interaction Quality Estimation
[chapter]
2016
Lecture Notes in Electrical Engineering
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Getting a good estimation of the Interaction Quality (IQ) of a spoken dialogue helps to increase the user satisfaction as the dialogue strategy may be adapted accordingly. ...
[8] put an emphasis on the sequential character of the IQ measure by applying Hidden Markov Models (HMMs) and Conditioned Hidden Markov Models (CHMMs). ...
[16] presented an approach using Hidden Markov Models (HMMs) to model the SDS as a process evolving over time. ...
doi:10.1007/978-981-10-2585-3_31
fatcat:2y3t4i72cvg5ho5kepemkaxani
A QoS-Satisfied Prediction Model for Cloud-Service Composition Based on a Hidden Markov Model
2013
Mathematical Problems in Engineering
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In this paper, we focus on QoS-satisfied predictions about the composition of cloud-service components and present a QoS-satisfied prediction model based on a hidden Markov model. ...
We discuss the proposed model in detail and prove some aspects of the model. Simulation results show that our model can achieve high prediction accuracies. ...
The Markov model (MM), particularly the hidden Markov model (HMM), has been shown to be a good technique for solving prediction problems. ...
doi:10.1155/2013/387083
fatcat:n67iqjylzfe2fcosnk43iafm7u
A Time-Aware Recommender System Based on Dependency Network of Items
2014
Computer journal
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There is indeed a hidden network structure among the items and each user tracks a sequence of items in this network. ...
The proposed model also results in personalized and diverse recommendations. Experimental evaluations show that the model can be trained based on the ratings of a limited number of users. ...
Markov-based recommender Methods based on Markov chain model the recommendation task as a Markov process [10] . ...
doi:10.1093/comjnl/bxu115
fatcat:q7yzp65t5ze25mgxgdsxdihr4a
Temporal Analytics for Software Usage Models
[chapter]
2018
Lecture Notes in Computer Science
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We address the problem of analysing how users actually interact with software. ...
We define new probabilistic models whose parameters are inferred from logged time series data of user-software interactions. ...
(mobile app) used by tens of thousands of users, working in close collaboration with the app developers. 2 Technical background
Markov models We assume familiarity with Markov models, probabilistic logics ...
doi:10.1007/978-3-319-74781-1_1
fatcat:bqmdln4drvdodaadsw4v42migy
Interaction Quality Estimation in Spoken Dialogue Systems Using Hybrid-HMMs
2014
Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)
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In this work, we investigate an approach for determining Interaction Quality for human-machine dialogue based on methods modeling the sequential characteristics using HMM modeling. ...
Ultes et al. (2012a) put an emphasis on the sequential character of the IQ measure by applying a Hidden Markov Models (HMMs) and a Conditioned Hidden Markov Models (CHMMs). ...
presented an approach using Hidden Markov Models (HMMs) to model the SDS as a process evolving over time. ...
doi:10.3115/v1/w14-4328
dblp:conf/sigdial/UltesM14
fatcat:4wxit6fuvvc3vesspzov45bjjy
Assisted living technologies for older adults
2012
Proceedings of the 2nd ACM SIGHIT symposium on International health informatics - IHI '12
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Hidden Semi-Markov Model
y 1
y 2
y 3
y 4
x 1
x 2
x 3
x 4
Arbitrary Duration
Distribution
51
Markov
Network
First
Order
Logic
Markov
Logic
Network
Markov logic networks ...
−1
=1
48
Coupled Hidden Markov Model (CHMM) [Wang 2010]
O = observations
A, B = activities
Multiple Residents? ...
doi:10.1145/2110363.2110478
dblp:conf/ihi/Rashidi12
fatcat:vavobpvbqzfslm4343duxh7yfe
Managing travel demand: Location recommendation for system efficiency based on mobile phone data
[article]
2016
arXiv
pre-print
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Under 60% compliance rate, 41% travel delay is saved with a 17% reduction in satisfaction. ...
Specifically, the results show that under full compliance rate, travel delay fell by 52% at a cost of 31% less satisfaction. ...
Mathew [29] predicts next-location using a Hidden Markov Model with contextual information, such as activities and purposes. ...
arXiv:1610.06825v1
fatcat:t33vmnawzradffdwhq4xkjhb74
A Comparison of Structural Equation Modeling Approaches with DeLone & McLean's Model: A Case Study of Radio-Frequency Identification User Satisfaction in Malaysian University Libraries
2018
Sustainability
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Two approaches are applied to estimate user satisfaction, such as the Bayesian and maximum likelihood estimation approaches. ...
The results reveal that Bayesian estimation provides good fit to the data, unlike the model with the maximum likelihood estimator. ...
The current study suggests that the Bayesian approach is deemed a suitable structural equation model for analyzing user satisfaction with library RFID. ...
doi:10.3390/su10072532
doaj:800e6047f7f34c3f9a9d7c1e4811fcc4
fatcat:o4gijvl22faqvdq6r3u5znpktu
Introducing Busy Customer Portfolio Using Hidden Markov Model
2011
Iranian Journal of Management Studies
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Forty four articles were selected and categorized on two major subclasses: articles which had used Markov chain models (MCM) in CRM and those which had applied hidden Markov models (HMM) in CRM. ...
One hundred articles were identified and reviewed to find direct relevance for applying Markov models in CRM. ...
Markov chain models (MCM) that includes all Markov models except hidden ones. 2. Hidden Markov models (HMM). ...
doaj:b7bdc5b6edb94be2ba1cc33d5c39794b
fatcat:r5yllq237rfhbc76ahw4qdtkze
Estimation of spectrum valuation for 5G dynamic frequency allocation and auctions
2021
2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)
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In this paper, we propose a model for estimating that valuation. The model is based on Markov chain modeling of user behavior, to compute the MNO satisfaction as a function of the obtained spectrum. ...
With those assumptions, the pair (i, j) of numbers of connected users of each type is a Markov process [20] . ...
In [14] the authors propose a model based on user satisfaction in order to compute the economic valuation. ...
doi:10.1109/vtc2021-spring51267.2021.9448690
fatcat:7q5bc3vf3ngsdowzlu243sxzjy
Transition Discovery of Sequential Behaviors in Email Application Usage Using Hidden Markov Models
2013
2013 46th Hawaii International Conference on System Sciences
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Herein, we show how dynamically generated hidden Markov models (HMMs) characterize sequence patterns in a software's userinterface event-stream. ...
This is important for identifying usage transitions, which occur with user learning. ...
Monitor Design
Markov Modeling A hidden Markov model (HMM) is a stochastic signal model [41] . In our application, the signals are sequences of discrete typed events. ...
doi:10.1109/hicss.2013.574
dblp:conf/hicss/RobinsonAD13
fatcat:5inoq2n46rhmvplicabgd7oshi
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