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Distance metric learning from uncertain side information for automated photo tagging

Lei Wu, Steven C.H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu
2011 ACM Transactions on Intelligent Systems and Technology  
In this work, we aim to address the challenge of large-scale automated photo tagging by exploring the social images. We present a retrieval based approach for automated photo tagging.  ...  Unlike traditional web images, social images often contain tags and other user-generated content, which offer a new opportunity to resolve some long-standing challenges in multimedia.  ...  Acknowledgments The work was supported in part by Singapore MOE Academic Tier-1 Grant (RG67/07) and NRF IDM Grant (IDM-004-018), National Science Foundation (  ... 
doi:10.1145/1899412.1899417 fatcat:krly2vmz65cvtkpuobw73frv4a

Distance metric learning from uncertain side information with application to automated photo tagging

Lei Wu, Steven C.H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu
2009 Proceedings of the seventeen ACM international conference on Multimedia - MM '09  
In this work, we aim to address the challenge of large-scale automated photo tagging by exploring the social images. We present a retrieval based approach for automated photo tagging.  ...  Unlike traditional web images, social images often contain tags and other user-generated content, which offer a new opportunity to resolve some long-standing challenges in multimedia.  ...  Acknowledgments The work was supported in part by Singapore MOE Academic Tier-1 Grant (RG67/07) and NRF IDM Grant (IDM-004-018), National Science Foundation (  ... 
doi:10.1145/1631272.1631293 dblp:conf/mm/WuHJZY09 fatcat:jfiaje3m7vfvjnayfy7bbi3se4

Structural Regularities in Text-based Entity Vector Spaces

Christophe Van Gysel, Maarten de Rijke, Evangelos Kanoulas
2017 Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval - ICTIR '17  
Such vector spaces are constructed in an unsupervised manner without explicit information about structural aspects.  ...  We compare latent, continuous representations created using methods based on distributional semantics (LSI), topic models (LDA) and neural networks (word2vec, doc2vec, SERT).  ...  All content represents the opinion of the authors, which is not necessarily shared or endorsed by their respective employers and/or sponsors.  ... 
doi:10.1145/3121050.3121066 dblp:conf/ictir/GyselRK17 fatcat:5nq2kg5fk5bjpiohr6nh6oisz4

Using latent topics to enhance search and recommendation in Enterprise Social Software

Konstantinos Christidis, Gregoris Mentzas, Dimitris Apostolou
2012 Expert systems with applications  
We employ Latent Dirichlet Allocation in order to elicit hidden topics and use the latter to assess similarities in resource and tag recommendation as well as for the expansion of query results.  ...  A challenge in Enterprise Social Software is to discover and maintain over time the knowledge structure of topics found relevant to the organization.  ...  Acknowledgement Acknowledgments Research reported in this paper has been partially financed by the European Commission in the OrganiK project (FP7: Research for the Benefit of SMEs, 222225).  ... 
doi:10.1016/j.eswa.2012.02.073 fatcat:iojnwwniczgsdduxrylhfnibrm

Are words enough?

Susana Zoghbi, Ivan Vulić, Marie-Francine Moens
2013 Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing - UnstructureNLP '13  
In this work we evaluate different textual representations and retrieval models that aim to make sense of social media data for retail applications.  ...  Our results show that document representations that combine latent concepts with single words yield the best performance.  ...  Acknowledgments This project is part of the SBO Program of the IWT (IWT-SBO-Nr. 110067).  ... 
doi:10.1145/2513549.2513557 dblp:conf/cikm/ZoghbiVM13a fatcat:n5hd46kkojbarl4mqywjuc5tqm

Temporal Latent Space Modeling for Community Prediction [chapter]

Hossein Fani, Ebrahim Bagheri, Weichang Du
2020 Lecture Notes in Computer Science  
Our model assumes that each user lies within an unobserved latent space, and similar users in the latent space representation are more likely to be members of the same user community.  ...  We propose a temporal latent space model for user community prediction in social networks, whose goal is to predict future emerging user communities based on past history of users' topics of interest.  ...  We propose a temporal latent space model for user community prediction in social networks that (i ) allows users to change their latent representations as their topics of interest evolve over time, and  ... 
doi:10.1007/978-3-030-45439-5_49 fatcat:5nwwmjuprbgdxh6fu22dzbt3pe

Searching in the Context of a Task: A Review of Methods and Tools

Ana Maguitman
2018 CLEI Electronic Journal  
In particular, topical context can be exploited to identify the subject of the information needs, contributing to reduce the information overload problem.  ...  It discusses major difficulties encountered in the research area of context-based information retrieval and presents an overview of tools proposed since the mid-nineties to deal with the problem of context-based  ...  Acknowledgment This work was supported by CONICET (PIP 11220120100487), MinCyT (PICT 2014-0624) and Universidad Nacional del Sur (PGI-UNS 24/N039).  ... 
doi:10.19153/cleiej.21.1.1 fatcat:eteqn6owzbbexmvo6sqfkcqywu

Multi-modal Mutual Topic Reinforce Modeling for Cross-media Retrieval

Yanfei Wang, Fei Wu, Jun Song, Xi Li, Yueting Zhuang
2014 Proceedings of the ACM International Conference on Multimedia - MM '14  
To further enhance the discriminative power of the learned latent topic representations, M 3 R incorporates the auxiliary information (i.e., categories or labels) into the process of Bayesian modeling,  ...  In principle, M 3 R is capable of simultaneously accomplishing the following two learning tasks: 1) modality-specific (e.g., image-specific or text-specific ) latent topic learning; and 2) cross-modal  ...  M 3 R gains interpretable latent representations for multi-modal retrieval and is effective for cross-modal retrieval in terms of MAP, Percentage and MRR.  ... 
doi:10.1145/2647868.2654901 dblp:conf/mm/WangWSLZ14 fatcat:rb65bjlp4zbjnh2qxc64x5w3da

Neural Vector Spaces for Unsupervised Information Retrieval

Christophe Van Gysel, Maarten de Rijke, Evangelos Kanoulas
2018 ACM Transactions on Information Systems  
We propose the Neural Vector Space Model (NVSM), a method that learns representations of documents in an unsupervised manner for news article retrieval.  ...  The addition of NVSM to a mixture of lexical language models and a state-of-the-art baseline vector space model yields a statistically significant increase in retrieval effectiveness.  ...  ACKNOWLEDGMENTS We thank Adith Swaminathan, Alexey Borisov, Tom Kenter, Hosein Azarbonyad, Mostafa Dehghani and Nikos Voskarides and the anonymous reviewers for their helpful comments.  ... 
doi:10.1145/3196826 fatcat:46qldllsnfd4xfyrrvw7xrtjhq

Topic modelling of clickthrough data in image search

Donn Morrison, Theodora Tsikrika, Vera Hollink, Arjen P. de Vries, Éric Bruno, Stéphane Marchand-Maillet
2012 Multimedia tools and applications  
We posit that clickthrough data contains hidden topics and can be used to infer a lower dimensional latent space that can be subsequently employed to improve various aspects of the retrieval system.  ...  In this paper we explore the benefits of latent variable modelling of clickthrough data in the domain of image retrieval.  ...  Acknowledgements This research was funded by the Swiss National Science Foundataion (SNF) through IM 2 (Interactive Multimedia Information Management) and by EU-FP7-ICT.1.5 NoE PetaMedia.  ... 
doi:10.1007/s11042-012-1038-8 fatcat:oaehqvunuzgkbozxfvfrkywiqi

Remedies against the Vocabulary Gap in Information Retrieval [article]

Christophe Van Gysel
2017 arXiv   pre-print
More specifically, we propose (1) methods to formulate an effective query from complex textual structures and (2) latent vector space models that circumvent the vocabulary gap in information retrieval.  ...  It is the alleviation of the effect brought forward by this vocabulary gap that is the topic of this dissertation.  ...  Secondly, the incorporation of entity-entity similarity in the construction of latent entity representations. Latent vector spaces for information retrieval.  ... 
arXiv:1711.06004v1 fatcat:6vkhvfby3zbzrepgopunm7gie4

Adaptive Model for Dynamic and Temporal Topic Modeling from Big Data using Deep Learning Architecture

Ajeet Ram Pathak, Manjusha Pandey, Siddharth Rautaray
2019 International Journal of Intelligent Systems and Applications  
and trends of topics over time.  It supports extraction of implicit and explicit topics from sentences also.  ...  The framework works in an adaptive manner in the sense that model is extracts incrementally according to streaming data and retrieves dynamic topics.  ...  the matrices U and V  Retrieve the term topic matrix U Input Query Processing  Analyze the query  Retrieve terms explicitly mentioned in the query  Perform explicit topic detection with the help of  ... 
doi:10.5815/ijisa.2019.06.02 fatcat:3gbhpyml2fgc7nh2rgvso4hnke

EXPLORING INFORMATION RETRIEVAL BY LATENT SEMANTIC INDEXING AND LATENT DIRICHLET ALLOCATION TECHNIQUES

Radha Guha
2020 International Research Journal of Computer Science  
This paper explores information retrieval models and experiments Semantic Indexing (LSI) first and then with the more efficient topic modeling algorithm of Latent Dirichlet Allocation (LDA).  ...  Comparisons between the two models are described clearly and concisely in their ef topic modeling. Various applications of topic modeling are also reviewed in this paper from the literature.  ...  Retrieving the relevant information from the internet in the Big Data era is same as finding a needle in the haystack. with the basic topic modeling concept of Latent Semantic Indexing (LSI) first and  ... 
doi:10.26562/irjcs.2020.v0705.001 fatcat:3mmmcy5kuve5hetxfh456bxwoy

Extracting, Mining and Predicting Users' Interests from Social Media

Fattane Zarrinkalam, Stefano Faralli, Guangyuan Piao, Ebrahim Bagheri
2020 Foundations and Trends in Information Retrieval  
Editorial Scope Topics Foundations and Trends R in Information Retrieval publishes survey and tutorial articles in the following topics: • Applications of IR Information for Librarians Foundations and  ...  Learning user topical profiles with implicit and explicit footprints". In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. SIGIR '17.  ... 
doi:10.1561/1500000078 fatcat:yarpz425bjbfjfihzs6y2mnere

Toward community answer selection by jointly static and dynamic user expertise modeling

Yuchao Liu, Meng Liu, Jianhua Yin
2021 APSIPA Transactions on Signal and Information Processing  
Besides, we introduce the explicit topic interest of users and capture the context-based personal interest by weighing the activation of each topic.  ...  In this paper, we propose an answer selection model based on the user expertise modeling, which simultaneously considers the social influence and the personal interest that affect the user expertise from  ...  dual LSTM architecture, in The International ACM SIGIR Conf. on Research and Development in Information Retrieval, 2017, 695-704. 6 Tan, M.; Dos Santos, C.; Xiang, B.; Zhou, B.: Improved representation  ... 
doi:10.1017/atsip.2020.28 fatcat:vb4tgretnbgmvmmwqhx5hqpiou
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