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Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains
2005
Data mining and knowledge discovery
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The algorithm is based on a straightforward generalization of latent Dirichlet allocation to time-invariant Markov chains of arbitrary order. ...
To provide a parsimonious generative representation of the sequential activity of a number of individuals within a population there is a necessary tradeoff between the definition of individual specific ...
The consistent generative semantics of the recently introduced latent Dirichlet allocation (LDA) [3] will be adopted and by analogy with [16] the resulting model will be referred to as a simplicial ...
doi:10.1007/s10618-005-0362-2
fatcat:cd7bcqnh55fy3pnhqu4axzhpnq
RaptGen: A variational autoencoder with profile hidden Markov model for generative aptamer discovery
[article]
2021
bioRxiv
pre-print
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RaptGen exploits a profile hidden Markov model decoder to represent motif sequences effectively. ...
We demonstrated that RaptGen could be applied to activity-guided aptamer generation according to Bayesian optimization. ...
p(x) can be written by using the Markov chain rule: 86 p (x) = π p (x, π) = p(x 0:L+1 , π last = M m+1 ),
3050 - 3050 AV), respectively. ...
doi:10.1101/2021.02.17.431338
fatcat:hukpewsdc5bn5nob622myx76ve
Exploring the Sensory Profiles of Children on the Autism Spectrum Using the Short Sensory Profile-2 (SSP-2)
2019
Journal of Autism and Developmental Disorders
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The aim of this study was to identify sensory subtypes in children on the autism spectrum using the Short Sensory Profile-2 (SSP-2). ...
Analysis using Dirichlet process mixture model identified a two-cluster model which provided the best solution to subtype sensory responses. ...
Essentially, the DPMM has an infinite number of components, and the algorithm implemented with Monte Carlo Markov Chain (MCMC) techniques adapts the number of "active" components based on the previous ...
doi:10.1007/s10803-019-03889-2
fatcat:lh5uzcmhm5bjrjk7g37zmmnvxy
Sequential latent Dirichlet allocation
2011
Knowledge and Information Systems
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In this article, we address this problem by presenting a novel variant of latent Dirichlet allocation (LDA): Sequential LDA (SeqLDA). ...
Such progressive sequential dependency is captured by using the hierarchical two-parameter Poisson-Dirichlet process (HPDP). ...
NICTA is funded by the Australian Government as represented by the Department of Broadband, Communications and the Digital Economy and the Australian Research Council through the ICT Centre of Excellence ...
doi:10.1007/s10115-011-0425-1
fatcat:avtzeaozsvb25eudm372mdfjim
Human Activity Clustering for Online Anomaly Detection
2011
Journal of Computers
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This paper aims to address the problem of profiling human activities captured in surveillance videos for the applications of online normal human activity recognition and anomaly detection. ...
The framework consists of the following key components: 1) A compact and effective activity representation method is developed based on a stochastic sequence of spatiotemporal actions. 2) The natural grouping ...
on discovering the natural grouping of activity using Hidden Markov Model with Latent Dirichlet Allocation (HMM-LDA). ...
doi:10.4304/jcp.6.6.1071-1079
fatcat:m7jtw33qezdchfx56z5xv2teay
A Survey on Journey of Topic Modeling Techniques from SVD to Deep Learning
2017
International Journal of Modern Education and Computer Science
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Here we present a survey on journey of topic modeling techniques comprising Latent Dirichlet Allocation (LDA) and non-LDA based techniques and the reason for classify the techniques into LDA and non-LDA ...
These techniques reveal the hidden thematic structure in a collection of documents and facilitate to build up new ways to browse, search and summarize large archive of texts. ...
LDA based sequence of words topic models with unsupervised learning a. Sequential Latent Dirichlet Allocation (seqLDA)
Fig. 13 . 13 seqLDA Graphical Model D. ...
doi:10.5815/ijmecs.2017.07.06
fatcat:nadnmsoj4zdi7onlxivrne6gqm
Combining eye movements and collaborative filtering for proactive information retrieval
2005
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '05
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Collaborative filtering is carried out using the User Rating Profile model, a state-of-the-art probabilistic latent variable model, computed using Markov Chain Monte Carlo techniques. ...
The best prediction accuracy still leaves room for improvement but shows that proactive information retrieval and combination of many sources of relevance feedback is feasible. ...
This work was supported by the Academy of Finland, decision no. 79017, and by the IST Programme of the European Community, under the PASCAL Network of Excellence, IST-2002-506778. ...
doi:10.1145/1076034.1076062
dblp:conf/sigir/PuolamakiSSSK05
fatcat:cqfmykb3b5bxrjr2gigpt3uek4
WWW 2011 invited tutorial overview
2011
Proceedings of the 20th international conference companion on World wide web - WWW '11
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Secondly, the problems arising on the internet do not always fit well into the known categories for latent variable inference such as Latent Dirichlet Allocation or clustering. ...
Firstly, we present a variety of applications ranging from general purpose document analysis, ideology detection, clustering of sequential data, and dynamic user profiling to recommender systems and data ...
Latent Dirichlet Allocation (LDA) is a suitable tool for uncovering such dependencies. It proved successful on smaller scale datasets for extraction of topics in documents. ...
doi:10.1145/1963192.1963311
dblp:conf/www/AhmedS11
fatcat:t6ua5wckjjgtpaeubhhsh2ivra
Topic Modeling for Sequences of Temporal Activities
2009
2009 Ninth IEEE International Conference on Data Mining
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This paper presents an LDA-style topic model for sequences of temporal activities that captures three features of such sequences: 1) the counts of unique activities, 2) the Markov transition dependence ...
This paper presents an LDAstyle topic model for sequences of temporal activities that captures three features of such sequences: 1) the counts of unique activities, 2) the Markov transition dependence ...
[7] successfully employ Latent Dirichlet Allocation (LDA) [3] to discovery patterns in the sequences of daily human activities, in which LDA only models the counts of unique words (Feature 1) in a ...
doi:10.1109/icdm.2009.83
dblp:conf/icdm/ShenLXSS09
fatcat:yqmrmlwvprailnroil4xulykcq
Classification and Clustering Methods for Multiple Environmental Factors in Gene–Environment Interaction
2016
Epidemiology
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., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. ...
These tools not only allow researchers to consider several environmental exposures in G×E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead ...
The funder was not involved in the preparation of the manuscript or in the final decision to publish. ...
doi:10.1097/ede.0000000000000548
pmid:27479650
pmcid:PMC5039086
fatcat:k4nynx24wrfujcvbr64tishx7i
Non-Employment Activity Type Imputation from Points of Interest and Mobility Data at an Individual Level: How Accurate Can We Get?
2019
ISPRS International Journal of Geo-Information
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This research proposes a methodological framework for urban activity type inference using a Dirichlet multinomial dynamic Bayesian network with an empirical Bayes prior that can be applied to mobility ...
The results provide evidence of the limits of activity detection accuracy using such data as determined by the Area Under Receiving Operating Curve (AUROC), log-loss, and accuracy metrics. ...
The accuracy of the proposed method was also benchmarked against two popular activity type models, Hidden Markov Model (HMM) and Latent Dirichlet Allocation (LDA). ...
doi:10.3390/ijgi8120560
fatcat:nuasif3mpzb47nekics267yn5u
Toward Personalized Context Recognition for Mobile Users
2014
ACM Transactions on Knowledge Discovery from Data
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Specifically, we first exploit the Bayesian Hidden Markov Model (B-HMM) for modeling context in the form of probabilistic distributions and transitions of raw context data. ...
Also, we propose a sequential model by extending B-HMM with the prior knowledge of contextual features to model context more accurately. ...
The proposed approach is based on the Latent Dirichlet Allocation topic model and is scalable for multiple contextual features. ...
doi:10.1145/2629504
fatcat:x3nrhg24mjdmrktosub3dx6axi
Bayesian non-parametric hidden Markov models with applications in genomics
2010
Journal of The Royal Statistical Society Series B-statistical Methodology
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The algorithm involves analytic marginalizations of latent variables to improve the mixing, facilitated by exchangeability properties of the Dirichlet process that we uncover in the paper. ...
analysis of parametric hidden Markov models. ...
It is interesting to investigate whether our approach of integrating out the global allocation variables when updating the hidden Markov chain, which is based on proposition 1, can be extended in this ...
doi:10.1111/j.1467-9868.2010.00756.x
pmid:21687778
pmcid:PMC3116623
fatcat:5xdtn4m2ifdbpn35wt3ey7dhlm
Spatiotemporal Sequential Influence Modeling for Location Recommendations
2015
ACM Transactions on Intelligent Systems and Technology
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a user visiting a new location through the developed additive Markov chain that considers the effect of all visited locations in the check-in history of the user on the new location. ...
However, human movement also exhibits spatiotemporal sequential patterns, but only few current studies consider spatiotemporal sequential influence of locations on users' check-in behaviors. ...
This method ] exploits the well-known topic model, i.e., latent Dirichlet allocation, to infer personal interest and local preference (i.e., local specialty). ...
doi:10.1145/2786761
fatcat:ssogeviapjhtfirs6yksmhagom
TraLFM: Latent Factor Modeling of Traffic Trajectory Data
2019
IEEE transactions on intelligent transportation systems (Print)
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2020 pre-print arXiv:2003.07780v1 fatcat:q2wqsca2tjbydjnag3ixzkdcja
Thus, TraLFM models the joint action of sequential, personal and temporal factors in a unified way, and brings a new perspective to many applications such as latent factor analysis and next location prediction ...
The widespread use of positioning devices (e.g., GPS) has given rise to a vast body of human movement data, often in the form of trajectories. ...
Both probabilistic latent semantic analysis(PLSA) [18] and latent dirichlet allocation (LDA) [7] have been popular methods for exploratory analysis of text. ...
doi:10.1109/tits.2019.2912075
fatcat:2hn7fq5bojgs7jb5qpxjulluja
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