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Semi-Supervised Variational User Identity Linkage via Noise-Aware Self-Learning [article]

Chaozhuo Li, Senzhang Wang, Zheng Liu, Xing Xie, Lei Chen, Philip S. Yu
2021 arXiv   pre-print
To address the mentioned limitations, in this paper we propose a novel Noise-aware Semi-supervised Variational User Identity Linkage (NSVUIL) model.  ...  Existing approaches usually first embed the identities as deterministic vectors in a shared latent space, and then learn a classifier based on the available annotations.  ...  based variational be easily clustered into the same group.  ... 
arXiv:2112.07373v1 fatcat:e6zcnwrxifasbdmffrvqzmejiq

A survey on different dimensions for graphical keyword extraction techniques: Issues and Challenges

Muskan Garg
2021 Artificial Intelligence Review  
To elucidate these different dimensions, a comprehensive survey of GKET is carried in different domains to make some inferences out of the existing literature.  ...  approaches are identified for different dimensions, namely, GoW representation: 'Line Graphs' and 'Bigram Words Graphs'; Feature extraction and selection using eigenvalues: 'Random Walk' and 'Spectral Clustering  ...  is a data reduction method that employs the correlation matrix of the features.  ... 
doi:10.1007/s10462-021-10010-6 pmid:33907346 pmcid:PMC8062621 fatcat:a4boojb4vrebtkoqwn3l66zo7e

A Survey on Multi-Task Learning [article]

Yu Zhang, Qiang Yang
2018 arXiv   pre-print
In order to improve the performance of learning tasks further, MTL can be combined with other learning paradigms including semi-supervised learning, active learning, unsupervised learning, reinforcement  ...  In this paper, we give a survey for MTL.  ...  Hence semi-supervised learning and active learning can be combined with MTL, leading to three new learning paradigms including semi-supervised multitask learning [117] , [118] , [119] , multi-task active  ... 
arXiv:1707.08114v2 fatcat:6lrpe4nk45djbjyfjco7t4yfme

Second order probabilistic models for within-document novelty detection in academic articles

Laurence A.F. Park, Simeon Simoff
2014 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14  
The Correlation between Cluster Hypothesis Tests and the Effectiveness of Cluster-Based Retrieval Fiana Raiber, Oren Kurland 84.  ...  Callan  Gaussian Process Factorization Machines for Context-Aware Recommendations Trung Nguyen, Alexandros Karatzoglou, Linas Baltrunas  Addressing Cold Start in Recommender Systems: A Semi-Supervised  ... 
doi:10.1145/2600428.2609520 dblp:conf/sigir/ParkS14 fatcat:ye2rtri2xjbyrjvkkzgt7srcfu

The Emerging Trends of Multi-Label Learning [article]

Weiwei Liu, Xiaobo Shen, Haobo Wang, Ivor W. Tsang
2020 arXiv   pre-print
data with limited supervision to build a multi-label classification model becomes valuable for practical applications, etc.  ...  For example, extreme multi-label classification is an active and rapidly growing research area that deals with classification tasks with an extremely large number of classes or labels; utilizing massive  ...  within a cluster  ... 
arXiv:2011.11197v2 fatcat:hu6w4vgnwbcqrinrdfytmmjbjm

Using Hashtag Graph-Based Topic Model to Connect Semantically-Related Words Without Co-Occurrence in Microblogs

Yuan Wang, Jie Liu, Yalou Huang, Xia Feng
2016 IEEE Transactions on Knowledge and Data Engineering  
In this paper, treating tweets as semi-structured texts, we propose a novel topic model, denoted as Hashtag Graph-based Topic Model (HGTM) to discover topics of tweets.  ...  In this paper, we introduce a new topic model to understand the chaotic microblogging environment by using hashtag graphs.  ...  [22] achieved focused topics and focused terms for short texts in the way of adding a dual-sparse constraint on topic mixtures of documents and words by applying a "Spike and Slab" prior.  ... 
doi:10.1109/tkde.2016.2531661 fatcat:h4mtgomevbewfnr4c3kyfbblsq

IEEE Access Special Section Editorial: AI-Driven Big Data Processing: Theory, Methodology, and Applications

Zhanyu Ma, Sunwoo Kim, Pascual Martinez-Gomez, Jalil Taghia, Yi-Zhe Song, Huiji Gao
2020 IEEE Access  
In this regard, the article, ''SSLSS: Semi-supervised learning-based steganalysis scheme for instant voice communication network,'' by Tu et al., initially introduces a novel semi-supervised hybrid learning  ...  Graph-based semi-supervised learning (GSSL) has attracted great attention over the past decade.  ...  Based on the long short-term memory neural network (LSTM NN), they develop a data-driven trajectory model to generate human-like driving trajectories.  ... 
doi:10.1109/access.2020.3035461 fatcat:rt7ejtponrfexigie4cfpt7gd4

Message from the general chair

Benjamin C. Lee
2015 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)  
We propose a joint learning model which combines pairwise classification and mention clustering with Markov logic.  ...  Compared with the best system from CoNLL-2011, which employs a rule-based method, our system shows competitive performance.  ...  The second step involves supervised property synonym discovery using a maximum entropy based clustering algorithm.  ... 
doi:10.1109/ispass.2015.7095776 dblp:conf/ispass/Lee15 fatcat:ehbed6nl6barfgs6pzwcvwxria

Open challenges for data stream mining research

Georg Krempl, Myra Spiliopoulou, Jerzy Stefanowski, Indre Žliobaite, Dariusz Brzeziński, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi
2014 SIGKDD Explorations  
ABSTRACT With the inception of the Twitter microblogging platform in 2006, a myriad of research efforts have emerged studying different aspects of the Twittersphere.  ...  ABSTRACT With the inception of the Twitter microblogging platform in 2006, a myriad of research efforts have emerged studying different aspects of the Twittersphere.  ...  It has been studied extensively in the static setting as semi-supervised learning (SSL, see [11] ).  ... 
doi:10.1145/2674026.2674028 fatcat:y3bozzeohveibgxb5wmiwfcogm

A survey on next location prediction techniques, applications, and challenges

Ayele Gobezie Chekol, Marta Sintayehu Fufa
2022 EURASIP Journal on Wireless Communications and Networking  
In next location prediction, trajectory is represented by a sequence of timestamped geographical locations.  ...  Using this big location-based trajectory data, researchers tend to predict human next location.  ...  Although trajectory segmentation has been the object of several approaches in the last decade, a proposal based on a semi-supervised remains inexistent.  ... 
doi:10.1186/s13638-022-02114-6 fatcat:s2ixs3ftibaobighbik6ikgfce

HYDRA

Siyuan Liu, Shuhui Wang, Feida Zhu, Jinbo Zhang, Ramayya Krishnan
2014 Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14  
This paper proposes HYDRA, a solution framework which consists of three key steps: (I) modeling heterogeneous behavior by long-term behavior distribution analysis and multi-resolution temporal information  ...  measure the high-order structure consistency on users' core social structures across different platforms; and (III) learning the mapping function by multi-objective optimization composed of both the supervised  ...  The proposed long-term user topic model captures the behavior similarity from pair-wise topic correlation at a series of coarse-tofine resolutions.  ... 
doi:10.1145/2588555.2588559 dblp:conf/sigmod/LiuWZZK14 fatcat:osatik6fcfhbxcjugwvtvzvslq

A Review on Text-Based Emotion Detection – Techniques, Applications, Datasets, and Future Directions [article]

Sheetal Kusal, Shruti Patil, Jyoti Choudrie, Ketan Kotecha, Deepali Vora, Ilias Pappas
2022 arXiv   pre-print
The field of text-based emotion detection (TBED) is advancing to provide automated solutions to various applications, such as businesses, and finances, to name a few.  ...  TBED has gained a lot of attention in recent times. The paper presents a systematic literature review of the existing literature published between 2005 to 2021 in TBED.  ...  GPT uses transformer decoders to model language using a semi-supervised learning technique.  ... 
arXiv:2205.03235v1 fatcat:b3m25fg6xfc3leeym22eqysq5a

Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs

Cristian Rotaru, Octav Brudaru
2012 2012 IEEE Congress on Evolutionary Computation  
A similarity based communication protocol between clusters of individuals from parallel grids is defined. The exchange of genetic material proves to considerably boost the quality of the solution.  ...  The population evolves on a bidimensional grid and is implicitly organized in geographical clusters that present a form of structural similarity between individuals.  ...  Alzate and Johan Suykens, A Semi-Supervised Formulation to Binary Kernel Spectral Clustering Wednesday, IEEE CEC, Poster WeC, 15:40-17:10, Poster session IEEE CEC, Bob (R.I) McKay 4, Yasin Volkan Pehlivanoglu  ... 
doi:10.1109/cec.2012.6256590 dblp:conf/cec/RotaruB12 fatcat:4ly3nrktw5habc6lf5err7d5py

Image Steganography Using HBC and RDH Technique

Hemalatha M, Prasanna A, Dinesh Kumar R, Vinothkumar D
2014 International Journal of Computer Applications Technology and Research  
With these methods the performance of the stegnographic technique is improved in terms of PSNR value.  ...  Reverse Data Hiding (RDH) is used to get the original image and it proceeds once when all the corners are unlocked with proper secret keys.  ...  Tian et al. have presented a method based on machine learning method, and used human ideas and comments and semi-supervised algorithm to detect web spam [19] .Becchetti et al. considered link based features  ... 
doi:10.7753/ijcatr0303.1001 fatcat:4i6tujs4oje2tnxf5c25eh26x4

Welcome message from the General Chairs

Giovanni Giambene, Boon Sain Yeo
2009 2009 International Workshop on Satellite and Space Communications  
This year we received a total of 153 high-quality papers from more than 20 countries. Many papers demonstrated notable systems with good analytical and/or empirical analyses.  ...  Based on these rigorous reviews, IES 2014 accepted 106 papers for inclusion in the conference program, which represents an acceptance rate of 69%.  ...  Semi-supervised ranking is a relatively new and important learning problem inspired by many applications.  ... 
doi:10.1109/iwssc.2009.5286448 fatcat:wcu4uzasizhzjmdkzyekynnqwi
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