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 Xiaoming Zhang

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Average citations per article1.12
Citation Count29
Publication count26
Publication years2007-2017
Available for download5
Average downloads per article103.40
Downloads (cumulative)517
Downloads (12 Months)186
Downloads (6 Weeks)29
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26 results found Export Results: bibtexendnoteacmrefcsv

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1 published by ACM
October 2017 Thematic Workshops '17: Proceedings of the on Thematic Workshops of ACM Multimedia 2017
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 10,   Downloads (12 Months): 41,   Downloads (Overall): 41

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Learning social media data embedding by deep models has attracted extensive research interest as well as boomed a lot of applications, such as link prediction, classification, and cross-modal search. However, for social images which contain both link information and multimodal contents (e.g., text description, and visual content), simply employing the ...
Keywords: deep learning, siamese-triplet, social embedding, attention model

2 published by ACM
May 2016 ACM Transactions on Intelligent Systems and Technology (TIST) - Special Issue on Crowd in Intelligent Systems, Research Note/Short Paper and Regular Papers: Volume 7 Issue 4, July 2016
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 6,   Downloads (12 Months): 71,   Downloads (Overall): 151

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Scientific literature ranking is essential to help researchers find valuable publications from a large literature collection. Recently, with the prevalence of webpage ranking algorithms such as PageRank and HITS, graph-based algorithms have been widely used to iteratively rank papers and researchers through the networks formed by citation and coauthor relationships. ...
Keywords: Influence mining, literature ranking, mutual reinforcement

3
March 2016 Multimedia Tools and Applications: Volume 75 Issue 6, March 2016
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 0

With the rapidly increasing popularity of social media sites, a large amount of user-generated data has been injected into the web. The data include a wide variety of real-world events. As a consequence, especially for social multimedia objects, it has become increasingly difficult to allow the browsing and organization of ...
Keywords: Feature correlation, Image tag, Event identification, Topic detection

4
July 2015 IJCAI'15: Proceedings of the 24th International Conference on Artificial Intelligence
Publisher: AAAI Press
Bibliometrics:
Citation Count: 0

Image location prediction is to estimate the geolocation where an image is taken. Social image contains heterogeneous contents, which makes image location prediction nontrivial. Moreover, it is observed that image content patterns and location preferences correlate hierarchically. Traditional image location prediction methods mainly adopt a single-level architecture, which is not ...

5 published by ACM
June 2015 ICMR '15: Proceedings of the 5th ACM on International Conference on Multimedia Retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 5,   Downloads (12 Months): 21,   Downloads (Overall): 80

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The vast amount of geo-tagged social images has attracted great attention in research of predicting location using the plentiful content of images, such as visual content and textual description. Most of the existing researches use the text-based or vision-based method to predict location. There still exists a problem: how to ...
Keywords: image topic, location prediction, topic model, geographical topic

6
May 2015 World Wide Web: Volume 18 Issue 3, May 2015
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 0

Influential spreaders identification in social networks contributes to optimize the use of available resources and ensure the more efficient spread of information. In contrast to common belief that highly connected or core located users are most crucial spreaders, this paper shows that both user's local and global structural properties matter ...
Keywords: Social circle, Influential identification, Information propagation

7
March 2015 Neurocomputing: Volume 152 Issue C, March 2015
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 5

There is an abundance of information found on microblog services due to their popularity. However the potential of this trove of information is limited by the lack of effective means for users to browse and interpret the numerous messages found on these services. We tackle this problem using a two-step ...
Keywords: Summarization, Microblog, Probabilistic graphical model, Topic classification, Pagerank, Semi-supervised

8 published by ACM
November 2014 CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 8,   Downloads (12 Months): 49,   Downloads (Overall): 210

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Previous work studied one-class collaborative filtering (OCCF) problems including pointwise methods, pairwise methods, and content-based methods. The fundamental assumptions made on these approaches are roughly the same. They regard all missing values as negative. However, this is unreasonable since the missing values actually are the mixture of negative and positive ...
Keywords: one-class collaborative filtering, latent dirichlet allocation, topic model

9
September 2014 Applied Intelligence: Volume 41 Issue 2, September 2014
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 1

Traditional Support Vector Machine (SVM) solution suffers from O ( n 2 ) time complexity, which makes it impractical to very large datasets. To reduce its high computational complexity, several data reduction methods are proposed in previous studies. However, such methods are not effective to extract informative patterns. In this ...
Keywords: Data cleaning, Entropy maximization, Bootstrap, Pattern extraction

10 published by ACM
July 2014 ICIMCS '14: Proceedings of International Conference on Internet Multimedia Computing and Service
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 0,   Downloads (12 Months): 4,   Downloads (Overall): 35

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One of the key problems of image retrieval and classification is how to measure the distance between any two social images. However, unlike traditional images, social images usually contain multi-types of features (e.g., visual content, textual description, users' social relation information, etc.). In this paper, we propose to integrate textual ...
Keywords: Distance Metric Learning, Social Image Retrieving, Social Image Tagging

11
August 2013 International Workshop on Behavior and Social Informatics on Behavior and Social Computing - Volume 8178
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

Relationships in Microblogging services are lack of explicit meaningful labels, such as "colleagues", "family members", etc. The state-of-the-arts mainly work on mining only one particular relationship type such as advisor-advisee relationship for specific social networks. Moreover, few work focuses on relationship identification in Microblog based on link analysis. In Microblog, ...
Keywords: Relationship type identification, community discovery, generative models, interactive tweets

12
July 2013 AAAI'13: Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence
Publisher: AAAI Press
Bibliometrics:
Citation Count: 6

Recent years have witnessed the tremendous development of social media, which attracts a vast number of Internet users. The high-dimension content generated by these users provides an unique opportunity to understand their behavior deeply. As one of the most fundamental topics, location estimation attracts more and more research efforts. Different ...

13
June 2013 WAIM'13: Proceedings of the 14th international conference on Web-Age Information Management
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

Nowadays, products are increasingly abundant and diverse, which makes user more fastidious. In fact, user has demands on a product in many aspects. A user is satisfied with a product usually because he or she likes all aspects of the product. Even only few of his or her demands or ...
Keywords: latent demands, stochastic gradient descent, collaborative filtering, rating psychology

14
June 2013 WAIM'13: Proceedings of the 14th international conference on Web-Age Information Management
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

In this paper, the psychometrics model, i.e. the rating scale model, is extended from one dimension to multiple dimension. Then, based on this, a novel collaborative filtering algorithm is proposed. In this algorithm, user's interest and item's quality are represented by vectors. User's rating for an item is a weighted ...
Keywords: latent interests, rating scale model, stochastic gradient descent, psychometrics, collaborative filtering

15
February 2013 Multimedia Tools and Applications: Volume 62 Issue 3, February 2013
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 4

Automatic image tagging automatically assigns image with semantic keywords called tags, which significantly facilitates image search and organization. Most of present image tagging approaches are constrained by the training model learned from the training dataset, and moreover they have no exploitation on other type of web resource (e.g., web text ...
Keywords: Search based tagging, Tag expansion, Image tagging, Image retrieval

16
August 2012 Journal of Intelligent Information Systems: Volume 39 Issue 1, August 2012
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 1

Image tagging is a task that automatically assigns the query image with semantic keywords called tags, which significantly facilitates image search and organization. Since tags and image visual content are represented in different feature space, how to merge the multiple features by their correlation to tag the query image is ...
Keywords: Feature fusion, Image tagging, Feature correlation, Image retrieval

17
May 2012 World Wide Web: Volume 15 Issue 3, May 2012
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 7

Automatic tagging can automatically label images and videos with semantic tags to significantly facilitate multimedia search and organization. However, most of existing tagging algorithms often don't differentiate between tags used to describe visual content, and neglect the semantic correlation of the assigned tag set. In this paper, we propose a ...
Keywords: automatic tagging, set correlation, information capability

18
October 2011 ICADL'11: Proceedings of the 13th international conference on Asia-pacific digital libraries: for cultural heritage, knowledge dissemination, and future creation
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

Image tagging is a task that automatically assigns the query image with semantic keywords called tags. Since tags and image visual content are represented in different feature space, how to merge the multiple features by their correlation to tag the query image is an important problem. However, most of existing ...
Keywords: feature correlation, image retrieval, image tagging

19
September 2011 WAIM'11: Proceedings of the 12th international conference on Web-age information management
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

Automatic image tagging automatically label images with semantic tags, which significantly facilitate image search and organization. Existing tagging methods often derive the probabilistic or co-occurring tags from the visually similar images, which based on the image level similarity between images. It may result in many noisy tags due to the ...
Keywords: feature correlation, image retrieval, image tagging

20
April 2011 DASFAA'11: Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

Automatic image tagging automatically assigns image with semantic keywords called tags, which significantly facilitates image search and organization. Most of present image tagging approaches assign the query image with the tags derived from the visually similar images in the training dataset only. However, their scalabilities and performances are constrained by ...
Keywords: tag expansion, image tagging, search based tagging



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