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Using Data Mining to Investigate the Behavior of Video Rental Customers
[chapter]
2009
Data Mining and Knowledge Discovery in Real Life Applications
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LTD (2006) showed that 27.8% of people in Taiwan watch TV videos to relax, the most popular activity, followed by travel, physical activities, dining out, shopping, playing on-line games, and enjoying ...
Obviously video entertainment is the most common and most basic form of consumer entertainment. Scholars have formulated different definitions of consumer behavior. ...
In this study Apriori algorithm was used to analyze favorite leisure activities and video category. ...
doi:10.5772/6452
fatcat:lmqw5v4nhfhpfnysimxsspsfdm
What's going on? Discovering spatio-temporal dependencies in dynamic scenes
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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In contrast to previous work, we build on state-of-the-art topic models that allow to automatically infer all parameters such as the optimal number of HMMs necessary to explain the rules governing a scene ...
They allow to discover temporal rules, such as the right of way between different lanes or typical traffic light sequences. To extract them, sequences of activities need to be learned. ...
Introduction In this work, we address scene understanding and automatic behaviour mining in video footage from one static camera. ...
doi:10.1109/cvpr.2010.5539869
dblp:conf/cvpr/KuttelBGF10
fatcat:p3qhtxoyereyfj3i7s3fsqzpkq
Is that scene dangerous?
2012
Proceedings of the 5th Ph.D. workshop on Information and knowledge - PIKM '12
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Activity mining in traffic scenes aims to automatically explain the complex interactions among moving objects recorded with a surveillance camera. ...
A concrete example of this first stage consists of a simple (but efficient) algorithm to incrementally generate association rules to explain current traffic scenes as co-occurrence relationships between ...
These issues violate fundamental assumptions of topic modeling for mining crowd activities in video data. ...
doi:10.1145/2389686.2389694
dblp:conf/cikm/FlorezD12
fatcat:xauhdpcqsjbxngok6eb2qdfrgu
A Framework to Counteract Suboptimal User-Behaviors in Exploratory Learning Environments: an Application to MOOCs
[article]
2021
arXiv
pre-print
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In particular, there is little a priori knowledge of which student's behaviors can be detrimental to learning in such environments. ...
To address this problem, we focus on a data-driven user-modeling framework that uses logged interaction data to learn which behavioral or activity patterns should trigger help during interaction with a ...
This indicates that the clusters are based on the level of engagement and activity of the students during video watching, which in turns can explain the differences in performance of students among clusters ...
arXiv:2106.07555v1
fatcat:46t6n7qahvc7hacgu67mdo4mk4
Finding out Reasons for Low Completion in MOOC Environment: An Explicable Approach Using Hybrid Data Mining Methods
2017
DEStech Transactions on Social Science Education and Human Science
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The extracted rules are used to find out and explain the reasons for low completion in MOOC environment. ...
Their study behaviors and interactions with website are analyzed with association rules mining in order to explore potential patterns and rules. ...
Rules could be explained as Y will likely happen due to the existence of X. ...
doi:10.12783/dtssehs/meit2017/12893
fatcat:wlycivcicfdwli2n3h4f6gv2se
A study on video data mining
2012
International Journal of Multimedia Information Retrieval
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Compared to the mining of other types of data, video data mining is still in its infancy. There are many challenging research problems existing with video mining. ...
The objective of video data mining is to discover and describe interesting patterns from the huge amount of video data as it is one of the core problem areas of the data-mining research community. ...
to identify elements in the video and finds rules to qualitatively select important elements to be included in the summary. ...
doi:10.1007/s13735-012-0016-2
fatcat:xuuf3w3b2rfcxlyevzndz6v62e
Predicting Student Performance in Higher Educational Institutions Using Video Learning Analytics and Data Mining Techniques
2020
Applied Sciences
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Additionally, the CN2 Rule Inducer and multivariate projection can be used to assist faculty in interpreting the rules to gain insights into student interactions. ...
The study aimed to predict student's overall performance at the end of the semester using video learning analytics and data mining techniques. ...
The authors are thankful to the Head of Computing Department, Mounir Dhibi (MEC), for his support and encouragement to carry out this study. ...
doi:10.3390/app10113894
fatcat:ucgkxpj5lbeabjc6ob5ivflkqm
A Data-Driven Student Model to Provide Adaptive Support During Video Watching Across MOOCs
[chapter]
2020
Lecture Notes in Computer Science
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In this paper, we show how FUMA, a data-driven framework for student modeling and adaptation, can help understand how to provide personalized support to MOOCs students, specifically targeting video watching ...
We discuss how these behaviors can be used to define personalized support to effective MOOC video usage regardless of the target course. ...
Next, association rule mining is used to identify the distinctive behaviors in each cluster. ...
doi:10.1007/978-3-030-52237-7_23
fatcat:4qf3cbnz3faerj4v6tfnpc7nwa
A Survey on Web Multimedia Mining
2011
The International Journal of Multimedia & Its Applications
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However, the state of the art techniques to process, mining and manage those rich media are still in their infancy. ...
The purpose of this paper is to provide a systematic overview of multimedia mining. ...
Images include maps, geological structures, and biological structures and even in the educational field, explained in [12] . ...
doi:10.5121/ijma.2011.3307
fatcat:dgvdft6tdra2lbdn6xkvr3ipsm
Exploring Smartphone Users' Social Information Behavior
2019
Contemporary Management Research
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This study used a site-centric approach, wherein user data was examined by using association rules and the Jaccard Index to explore the relationship between SNS and other online activities. ...
Second, site-centric approach will conduct correspondence analysis and association rules by using users' session to gather all categories in the graph and explore the relationship between the SNSs and ...
At least by two or more participants to participate in the information sharing activities, so all the information sharing activities are occurring in the network. ...
doi:10.7903/cmr.18461
fatcat:zyzt6vvur5bufdyczbrokocqzi
Data Mining for Action Recognition
[chapter]
2015
Lecture Notes in Computer Science
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This paper improves the performance of action recognition through two data mining techniques, APriori association rule mining and Contrast Set Mining. ...
called rules. ...
In order to classify test videos, the rules for each class need to be mined through the two data mining techniques we propose. ...
doi:10.1007/978-3-319-16814-2_19
fatcat:fhxlpeku35glzaxshd5ffq6mzi
Predicting Student Academic Performance by Means of Associative Classification
2021
Applied Sciences
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Although several machine learning and data mining solutions have been proposed to learn accurate predictors from past data, the interpretability and explainability of the best performing models is often ...
Early predictions allow teachers to put in place targeted actions, e.g., supporting at-risk students to avoid exam failures or course dropouts. ...
This is valid for the use of MA video-lectures (rules 18, 20 and 22), but also for the use other course video-lectures (rules 19, 21 and 23), because this activity likely identifies active and motivated ...
doi:10.3390/app11041420
fatcat:e552dq4hzjh33l4k3quonosa6y
Theoretical and Empirical Analysis of Crime Data
2021
Journal of Web Engineering
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This paper shows, how data mining techniques can be used to detect and predict crime using association mining rule, k-means clustering, decision tree, artificial neural networks and deep learning methods ...
are also explained. ...
Nieto
et al. (2018)
[1]
CERTH/ITI
Project
works on
real time
online as
well as
offline video
analysis
Working
process need
to be
explained in
more detail,
graphs are
less. ...
doi:10.13052/jwe1540-9589.2016
fatcat:nqoxbqz5fvc3rlxpti6rkdnxfy
Personalising Mobile Advertising Based on Users' Installed Apps
2014
2014 IEEE International Conference on Data Mining Workshop
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In addition association rule mining was performed to find whether the time of the day that the advert is served and the number of apps a user has installed makes certain profiles more likely to interact ...
In this paper we investigate whether the application of unsupervised learning and association rule mining could be used to enable personalised targeting of mobile adverts with the aim of increasing the ...
We mined 70 rules for finance ads where the consequence was play video, watch 50% of video or watch The lift value of a rule is similar to the index value, so a rule with a lift of 2 means that users with ...
doi:10.1109/icdmw.2014.90
dblp:conf/icdm/RepsAGD14
fatcat:pwhea63zynbqrpjm7yzntr6mbe
Mining Layered Grammar Rules for Action Recognition
2010
International Journal of Computer Vision
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Using the learned rules, the parse tree of an action video is constructed by combining a bottom-up rule detection step and a top-down ambiguous rule pruning step. ...
At each layer above, we iteratively mine grammar rules and "super rules" that account for the high-order compositional feature structures. ...
Emerging Pattern (EP) Mining In this section, we briefly introduce the Emerging Pattern mining method (Dong and Li 2004) , and present how to apply it in our framework to mine production rules. ...
doi:10.1007/s11263-010-0393-z
fatcat:djpm6qeyujgbxj7fddiidtdriy
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