Filters








8,314 Hits in 6.6 sec

The geography of Twitter topics in London

Guy Lansley, Paul A. Longley
2016 Computers, Environment and Urban Systems  
Topics and attitudes expressed through Tweets are found to vary substantially across Inner London, and by time of day.  ...  Our classification identifies 20 distinctive and interpretive topic groupings, which represent key types of Tweets, from describing activities or informal conversations between users, to the use of check-in  ...  Acknowledgements This work is funded by the UK ESRC Consumer Data Research Centre (CDRC) grant reference ES/L011840/1 and 'The analysis of names from the 2011 Census of Population' (ES/L013800/1).  ... 
doi:10.1016/j.compenvurbsys.2016.04.002 fatcat:pyvu354b7vd7vp2e2agimctl24

Scalable topic-specific influence analysis on microblogs

Bin Bi, Yuanyuan Tian, Yannis Sismanis, Andrey Balmin, Junghoo Cho
2014 Proceedings of the 7th ACM international conference on Web search and data mining - WSDM '14  
While most previous influence analysis schemes rely only on the links between users to find key influencers, they omit the important text content created by the users.  ...  Social influence analysis on microblogs, such as Twitter, has been playing a crucial role in online advertising and brand management.  ...  As we will show later in this paper, these methods perform inferior to those approaches in the second camp that integrate text topic discovery and social influence analysis in the same model.  ... 
doi:10.1145/2556195.2556229 dblp:conf/wsdm/BiTSBC14 fatcat:z2n3wzvqvnahdayh7eqhdpdzym

Recommending Flickr groups with social topic model

Jingdong Wang, Zhe Zhao, Jiazhen Zhou, Hao Wang, Bin Cui, Guojun Qi
2012 Information retrieval (Boston)  
Particularly, Flickr groups, self-organized communities with declared, common interests, are able to help users to conveniently participate in social media network.  ...  In this paper, we address the problem of automatically recommending groups to users. We propose to simultaneously exploit media contents and link structures between users and groups. To this end,  ...  Acknowledgements Bin Cui is supported by the grant of Natural Science Foundation of China (No. 61073019 and 60933004).  ... 
doi:10.1007/s10791-012-9193-0 fatcat:xvt7m56qajhcbe53g5pcmsy2ea

Building a semantic recommendation engine for news feeds based on emerging topics from tweets

Mihai Tabara, Mihai Dascalu, Stefan Trausan-Matu
2016 2016 15th RoEduNet Conference: Networking in Education and Research  
The rise of social networks powered by the emergence of Web 2.0 unleashed a massive amount of generated user content.  ...  In this paper, we approach the problem of topic extraction from Twitter in the context of designing a recommendation engine to best matching user profiles to news feed articles.  ...  Acknowledgment The work presented in this paper was partially funded by the EC H2020 project RAGE (Realising and Applied Gaming Eco-System) http://www.rageproject.eu/ Grant agreement No 644187.  ... 
doi:10.1109/roedunet.2016.7753209 fatcat:fywcfbdd3bdkznzhsvdiyxih3y

Document-topic hierarchies from document graphs

Tim Weninger, Yonatan Bisk, Jiawei Han
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
Topic taxonomies allow users to quickly drill down into their topic of interest to find documents.  ...  We show that hierarchies of documents, where documents live at the inner nodes of the hierarchy-tree can also be inferred by combining document text with inter-document links.  ...  ACKNOWLEDGMENTS We thank Qirong Ho for his helpful discussion, the developers of the Mallet toolkit, as well as Rob Rutenbar and Abner Guzmán Rivera for their initial guidance.  ... 
doi:10.1145/2396761.2396843 dblp:conf/cikm/WeningerBH12 fatcat:rpgg24sr6rg7xl66adf5adikb4

Spam, Opinions, and Other Relationships: Towards a Comprehensive View of the Web Knowledge Discovery [chapter]

Bettina Berendt
2011 Advanced Topics in Information Retrieval  
We illustrate the usefulness of this model in an introduction to Web content/text mining, using the model to structure the activities in this form of Knowledge Discovery.  ...  Web mining" or "Web Knowledge Discovery" is the analysis of Web resources with data-mining techniques such as classification, clustering, association-rule or graph-structure methods.  ...  Acknowledgements I thank my students and colleagues from various Web Mining classes for many valuable discussions and ideas. In particular, I thank the members of the  ... 
doi:10.1007/978-3-642-20946-8_3 fatcat:dzzvsoiizbb3terfovfzojtqbi

Topicality Reconsidered: A Multidisciplinary Inquiry into Topical Relevance Relationships

Xiaoli Huang
2009 Zenodo  
The findings from the analysis contribute to the foundation work of information organization, intellectual access / information retrieval, and knowledge discovery.  ...  , and induces a cohesive topic-oriented information architecture that is meaningful across topics and domains.  ...  In addition to structuring a single topic space, the topical relationships can also be used to link different topics and connect them into a knowledge network.  ... 
doi:10.5281/zenodo.3475965 fatcat:ajmdssk34jbmtkeswj53w6mf6y

Literature Survey on Interplay of Topics, Information Diffusion and Connections on Social Networks [article]

Kuntal Dey, Saroj Kaushik, L. Venkata Subramaniam
2017 arXiv   pre-print
Researchers have attempted to model information diffusion and topic trends and lifecycle on online social networks.  ...  The current article presents a survey of representative models that perform topic analysis, capture information diffusion, and explore the properties of social connections in the context of online social  ...  This also holds for communities formed on social network graphs, over links inferred from user-generated topical text content. Table II .  ... 
arXiv:1706.00921v1 fatcat:doqorr3v2zhq5oiemm5zhlmc3u

Topic level expertise search over heterogeneous networks

Jie Tang, Jing Zhang, Ruoming Jin, Zi Yang, Keke Cai, Li Zhang, Zhong Su
2010 Machine Learning  
For example in a heterogeneous academic network, there are different objects such as authors, conferences, and papers; in a product review system, there are objects like products, users, and reviews.  ...  The emerging complex networking data poses many fundamental challenges for search and mining of them.  ...  Philip Yu for his valuable suggestions.  ... 
doi:10.1007/s10994-010-5212-9 fatcat:k2awpzjuwvafxhhsvf5bbng33u

Identifying Changes in the Cybersecurity Threat Landscape Using the LDA-Web Topic Modelling Data Search Engine [chapter]

Noura Al Moubayed, David Wall, A. Stephen McGough
2017 Lecture Notes in Computer Science  
The tool is based on the probabilistic topic modelling technique which goes further than the lexical analysis of documents to model the subtle relationships between words, documents, and abstract topics  ...  This results in large volumes of unstructured text data that is difficult to manage or investigate manually.  ...  Acknowledgment This work is part of the CRITiCal project (Combatting cRiminals In The Cloud -EP/M020576/1) funded by the Engineering and Physical Sciences Research Council (EPSRC).  ... 
doi:10.1007/978-3-319-58460-7_19 fatcat:lw6r23oznbajxfzj4lfyrpoxqu

Bayesian Nonparametric Relational Topic Model through Dependent Gamma Processes

Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo
2017 IEEE Transactions on Knowledge and Data Engineering  
Index Terms-Text mining, network analysis, topic model, Bayesian nonparametric ! • J. Xuan is with  ...  Many theoretical and practical tasks, such as dimensional reduction, document clustering, and link prediction, could benefit from this revealed knowledge.  ...  ACKNOWLEDGMENTS Research work reported in this paper was partly supported by the Australian Research Council (ARC) under discovery grant DP140101366 and the China Scholarship Council.  ... 
doi:10.1109/tkde.2016.2636182 fatcat:omdokoyn4je2tncprynvasivs4

Sparse Relational Topic Models for Document Networks [chapter]

Aonan Zhang, Jun Zhu, Bo Zhang
2013 Lecture Notes in Computer Science  
Our model can also handle imbalance issues in real networks via introducing various cost parameters for positive and negative links.  ...  Previous work on relational topic models (RTM) has shown promise on learning latent topical representations for describing relational document networks and predicting pairwise links.  ...  Link prediction is a fundamental task in network analysis [1] , and building link prediction models can provide solutions like suggesting friends for social network users or recommending products.  ... 
doi:10.1007/978-3-642-40988-2_43 fatcat:h3xnk5l7abb3vi22lfbhylv7z4

Topics in semantic representation

Thomas L. Griffiths, Mark Steyvers, Joshua B. Tenenbaum
2007 Psychological review  
The topic model performs well in predicting word association and the effects of semantic association and ambiguity on a variety of language-processing and memory tasks.  ...  It also provides a foundation for developing more richly structured statistical models of language, as the generative process assumed in the topic model can easily be extended to incorporate other kinds  ...  For example, if we lived in a world where people only wrote about finance, the English countryside, and oil mining, then we could model all documents with the three topics shown in Figure 1c .  ... 
doi:10.1037/0033-295x.114.2.211 pmid:17500626 fatcat:b7kxhjo4kvfsbmlslhhuslt5xa

III Advanced Topics [chapter]

2016 Soft Computing Applications in Sensor Networks  
Acknowledgments This work has been supported in part by AGAUR Project under Grant  ...  Because of its proven strength in treating imprecise information and discovering novel solutions 21 22 Soft Computing Applications in Sensor Networks to hard problems, SC is a topic of interest amongst  ...  Modeling and analysis of fault detection and fault tolerance in wireless sensor networks.  ... 
doi:10.1201/9781315372020-13 fatcat:ze5voikcfbfi5lubz5t5oismua

Dimensionality Reduction and Topic Modeling: From Latent Semantic Indexing to Latent Dirichlet Allocation and Beyond [chapter]

Steven P. Crain, Ke Zhou, Shuang-Hong Yang, Hongyuan Zha
2012 Mining Text Data  
The bag-of-words representation commonly used in text analysis can be analyzed very efficiently and retains a great deal of useful information, but it is also troublesome because the same thought can be  ...  We also discuss recent advances that have made it possible to apply these techniques to very large and evolving text collections and to incorporate network structure or other contextual information.  ...  For very large datasets, this is many times faster than other algorithms and yet yields very excellent results. Networked Data Networks play an important role in many text mining problems.  ... 
doi:10.1007/978-1-4614-3223-4_5 fatcat:773znlkzwffznnm7wm5rk24luu
« Previous Showing results 1 — 15 out of 8,314 results