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Follower Behavior Analysis via Influential Transmitters on Social Issues in Twitter
2016
Journal of Computacion y Sistemas
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The thread tweets are clustered based on Latent Dirichlet Allocation for social issues. Then, sentiment analysis is conducted for the clusters of a follower. ...
To detect a follower's specific opinion, social issues are extracted based on tweets of influential transmitters. ...
Acknowledgements
Follower Behavior Analysis via Influential Transmitters on Social Issues in Twitter 423 Center) support program (IITP-2016-R0992-15-1023) supervised by the IITP (Institute for Information ...
doi:10.13053/cys-20-3-2452
fatcat:hlmyrtmxkrharhroabxzqq2wb4
Knowledge Discovery from Dynamically Evolving User Profiles
2014
International Journal of Computer Applications
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In this paper it analyzes computer user behavior based on the commands that they execute as part of their job profile. ...
For this reason the user behavior profiles are continually updated on order to ensure that they reflect the true knowledge of the behavior of users with respect to their job roles. ...
The user behavior can be used to take necessary steps based on the result of analysis. ...
doi:10.5120/14805-3013
fatcat:tvfzgu7kdfdmlnzdlpr5dk67ou
An anomaly-based approach to the analysis of the social behavior of VoIP users
2013
Computer Networks
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The objective of such study was twofold: (i) first of all, we wanted to be able to tell well-behaving users apart from potential malicious ones; (ii) once done with the first, coarse-grained, classification ...
The paper shows how we can reliably identify behavioral patterns associated with the most common anomalous behaviors of VoIP users. ...
clustering algorithm, capable to provide a first visual representation of the classification made by the clustering algorithm; (iii) chart of the time distribution of the calls issued by a suspect user ...
doi:10.1016/j.comnet.2013.02.009
fatcat:dysjgzkssbh2na6forpxwecxme
Context-aware prediction of user's first click
2012
Proceedings of the 1st International Workshop on Context Discovery and Data Mining - ContextDD '12
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Location-based services has attracted attentions from both industry and academia. ...
Our proposed approach models the problem as a multi-label classification. We introduce three sets of features including location feature, time feature and behavioral feature. ...
Item-based CF algorithms quantify a product's characteristics based on the group of users who purchased it. A challenging issue of CF-based models is how to conquer the cold start problem. ...
doi:10.1145/2346604.2346613
fatcat:wmeeftkbbjayjjktg3do2yb4me
Railway Infrastructure and Traveller usage Prediction and Rendering Solutions
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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Thus our proposed system involves data collection of the users based on id, username, gender, age, the timing of travel, station source and destination to monitor the user travel behavior. ...
For this work, In R programming, we use K-means algorithm for clustering and use Naive Bayes algorithm for machine learning and solution defining. ...
We have created an user interface in this module where user can input his choice for clustering and classification . ...
doi:10.35940/ijitee.j9296.1081219
fatcat:c3t7ijjh6ffcbl6fbvvesfxxbu
On Modeling Community Behaviors and Sentiments in Microblogging
[chapter]
2014
Proceedings of the 2014 SIAM International Conference on Data Mining
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In this paper, we propose the CBS topic model, a probabilistic graphical model, to derive the user communities in microblogging networks based on the sentiments they express on their generated content ...
Our experiments on two Twitter datasets show that the CBS model can effectively mine the representative behaviors and emotional topics for each community. ...
80 for the user classification task. ...
doi:10.1137/1.9781611973440.55
dblp:conf/sdm/HoangCL14
fatcat:hitjgzrrmzcihpj6itvor2zjai
Recommendations of Personal Web Pages Based on User Navigational Patterns
2014
International Journal of Machine Learning and Computing
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These navigational patterns are then used to generate recommendation web pages by matching the navigation behavior of a user personal knowledge base. ...
The experimental results show that the web pages recommended by our system are of better quality and acceptable for humans from various domains, based on human evaluators ranking as well as quality-value-based ...
Query Classification Typically, the queries issued by users consist of a few words. ...
doi:10.7763/ijmlc.2014.v4.429
fatcat:hwo74szi3basbncn6lychcw2r4
Web personalization based on static information and dynamic user behavior
2004
Proceedings of the 6th annual ACM international workshop on Web information and data management - WIDM '04
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This strategy takes into account both static information, by means of classical clustering algorithms, and dynamic behavior of a user, proposing a novel and effective re-classification algorithm. ...
In this paper, a web personalization strategy based on pattern recognition techniques is presented. ...
Re-classification is used to overcome the inaccuracy of the registration information, based on the users' navigational behavior. ...
doi:10.1145/1031453.1031469
dblp:conf/widm/AlbanesePSS04
fatcat:c332liwzrvh2nksmwh4ktnskae
Special Issue on Device-Free Sensing for Human Behavior Recognition II (Addcorr from the editor)
2021
Personal and Ubiquitous Computing
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Meanwhile, an automatic classification technique is proposed to identify location types based on collected data. ...
Based on the cluster characteristic, nearfield human presence can be recognized with online sensing. ...
doi:10.1007/s00779-020-01493-1
fatcat:leh6s4w7ynawpdgyj3uw6znyoy
Data-Driven Requirements Elicitation: A Systematic Literature Review
2021
SN Computer Science
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This article highlights the need for developing methods to leverage process-mediated and machine-generated data for requirements elicitation and addressing the issues related to variety, velocity, and ...
for data processing. ...
For clustering, topic modeling (16%) was the most commonly used approach, followed by more traditional clustering techniques (13%) and unsupervised rule-based clustering (2%). ...
doi:10.1007/s42979-020-00416-4
fatcat:g4g7nb4mwbhuhgmmfxi5vir5ly
Design of an Ensemble Learning Behavior Anomaly Detection Framework
2019
Zenodo
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This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. ...
In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. ...
These methods are based on clustering and outliers detection. The goal is to group users who showcase the same practices as one entity (i.e. clusters). ...
doi:10.5281/zenodo.3566298
fatcat:man7qwdaynhsdnfc2rvzqrdkbi
Effective personalized recommendation based on time-framed navigation clustering and association mining
2004
Expert systems with applications
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Historical navigation sessions for each user are divided into frames of sessions based on a specific time interval. ...
This research proposes a new clustering method, called HBM (Hierarchical Bisecting Medoids Algorithm) to cluster users based on the time-framed navigation sessions. ...
On the other hand, to investigate the issue of whether it is better to consider the previous sessions ðS 1 ; S 2 ; …; S n21 Þ when doing user classification, another avenue of user classification based ...
doi:10.1016/j.eswa.2004.05.005
fatcat:km4s6ncf3vda7lruduw7wqxymy
SOME OBSERVATION OF ALGORITHMS DEVELOPED FOR ANOMALY DETECTION
2020
Indian Journal of Computer Science and Engineering
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The generated data are publicly available which may become the prime target for the malicious users, who try to attack and harm the innocent users. ...
This paper mainly focuses on the graph mining techniques used for anomaly detection in social networks. ...
At the final step, users and messages are co-clustered based on co-clustering algorithm non negative matrix trifactorization. ...
doi:10.21817/indjcse/2020/v11i1/201101005
fatcat:ynz45figozbu7fuznqo2u3j55y
Building MultiView Analyst Profile From Multidimensional Query Logs: From Consensual to Conflicting Preferences
[article]
2012
arXiv
pre-print
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In fact, the analyst preferences are clustered into three main pools : (i) consensual or non conflicting preferences referring to same preferences for all analysts; (ii) semi-conflicting preferences corresponding ...
In this paper, we introduce a new approach for user profile construction from OLAP query logs. The key idea is to learn the user's preferences by drawing the evidence from OLAP logs. ...
Via Clustering which is a simple metaclassifier that uses a cluster for classification. ...
arXiv:1203.3589v1
fatcat:wtbbqywoonfy5hm4n42vvexjli
Spiteful, One-Off, and Kind: Predicting Customer Feedback Behavior on Twitter
[chapter]
2016
Lecture Notes in Computer Science
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Identifying different types of customers based on their feedback behavior can help companies to maintain their customers. ...
In this paper, we use a machine learning approach to predict a customer's feedback behavior based on her first feedback tweet. ...
Next, based on this representation, we cluster the users together. To cluster the users, we use Expectation-Maximization (E-M) algorithm. ...
doi:10.1007/978-3-319-47874-6_26
fatcat:jtlz7xvrivfv7hzotl3wshwkwm
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