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Displaying 1-50 out of 71 total
Behavior Informatics: A New Perspective
Found in: IEEE Intelligent Systems
By Longbing Cao,Thorsten Joachims,Can Wang,Eric Gaussier,Jinjiu Li,Yuming Ou,Dan Luo,Reza Zafarani,Huan Liu,Guandong Xu,Zhiang Wu,Gabriella Pasi,Ya Zhang,Xiaokang Yang,Hongyuan Zha,Edoardo Serra,V.S. Subrahmanian
Issue Date:July 2014
pp. 62-80
This installment of Trends & Controversies provides an array of perspectives on the latest research in behavior informatics. Longbing Cao introduces the work in "Behavior Informatics: A New Perspective." Then, in "Behavior Computing,...
 
Manifold Based Dynamic Texture Synthesis from Extremely Few Samples
Found in: 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
By Hongteng Xu,Hongyuan Zha,Mark A. Davenport
Issue Date:June 2014
pp. 3019-3026
In this paper, we present a novel method to synthesize dynamic texture sequences from extremely few samples, e.g., merely two possibly disparate frames, leveraging both Markov Random Fields (MRFs) and manifold learning. Decomposing a textural image as a se...
 
Learning the Gain Values and Discount Factors of Discounted Cumulative Gains
Found in: IEEE Transactions on Knowledge and Data Engineering
By Ke Zhou,Hongyuan Zha,Yi Chang,Gui-Rong Xue
Issue Date:February 2014
pp. 391-404
Evaluation metric is an essential and integral part of a ranking system. In the past, several evaluation metrics have been proposed in information retrieval and web search, among them Discounted Cumulative Gain (DCG) has emerged as one that is widely adopt...
 
Manifold Based Face Synthesis from Sparse Samples
Found in: 2013 IEEE International Conference on Computer Vision (ICCV)
By Hongteng Xu,Hongyuan Zha
Issue Date:December 2013
pp. 2208-2215
Data sparsity has been a thorny issue for manifold-based image synthesis, and in this paper we address this critical problem by leveraging ideas from transfer learning. Specifically, we propose methods based on generating auxiliary data in the form of synt...
 
Joint Optimization for Consistent Multiple Graph Matching
Found in: 2013 IEEE International Conference on Computer Vision (ICCV)
By Junchi Yan,Yu Tian,Hongyuan Zha,Xiaokang Yang,Ya Zhang,Stephen M. Chu
Issue Date:December 2013
pp. 1649-1656
The problem of graph matching in general is NP-hard and approaches have been proposed for its sub optimal solution, most focusing on finding the one-to-one node mapping between two graphs. A more general and challenging problem arises when one aims to find...
 
A New Algorithm for Inferring User Search Goals with Feedback Sessions
Found in: IEEE Transactions on Knowledge and Data Engineering
By Zheng Lu,Hongyuan Zha,Xiaokang Yang,Weiyao Lin,Zhaohui Zheng
Issue Date:March 2013
pp. 502-513
For a broad-topic and ambiguous query, different users may have different search goals when they submit it to a search engine. The inference and analysis of user search goals can be very useful in improving search engine relevance and user experience. In t...
 
Adaptive Manifold Learning
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Zhenyue Zhang, Jing Wang, Hongyuan Zha
Issue Date:February 2012
pp. 253-265
Manifold learning algorithms seek to find a low-dimensional parameterization of high-dimensional data. They heavily rely on the notion of what can be considered as local, how accurately the manifold can be approximated locally, and, last but not least, how...
 
Estimate-Piloted Regularization and Fast ALS Algorithm for Collaborative Filtering
Found in: International Conference on Future Computer Science and Education
By Zhenyue Zhang,Keke Zhao,Hongyuan Zha,Guirong Xue
Issue Date:August 2011
pp. 567-570
Regularized Low-rank approximation with missing data is an effective approach for Collaborative Filtering since it generates high quality rating predictions for recommender systems. Alternative LS (ALS) method is one of the commonly used algorithms for the...
 
Spectral methods for semi-supervised manifold learning
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Zhenyue Zhang, Hongyuan Zha, Min Zhang
Issue Date:June 2008
pp. 1-6
Given a finite number of data points sampled from a low-dimensional manifold embedded in a high dimensional space together with the parameter vectors for a subset of the data points, we need to determine the parameter vectors for the rest of the data point...
 
Adapting ranking functions to user preference
Found in: Data Engineering Workshops, 22nd International Conference on
By Keke Chen, Ya Zhang, Zhaohui Zheng, Hongyuan Zha, Gordon Sun
Issue Date:April 2008
pp. 580-587
Learning to rank has become a popular method for web search ranking. Traditionally, expert-judged examples are the major training resource for machine learned web ranking, which is expensive to get for training a satisfactory ranking function. The demands ...
 
A Comparison of Unsupervised Dimension Reduction Algorithms for Classification
Found in: Bioinformatics and Biomedicine, IEEE International Conference on
By Jaegul Choo, Hyunsoo Kim, Haesun Park, Hongyuan Zha
Issue Date:November 2007
pp. 71-77
Distance preserving dimension reduction (DPDR) using the singular value decomposition has recently been intro- duced. In this paper, for disease diagnosis using gene or protein expression data, we present empirical comparison results between DPDR and other...
 
Co-ranking Authors and Documents in a Heterogeneous Network
Found in: Data Mining, IEEE International Conference on
By Ding Zhou, Sergey A. Orshanskiy, Hongyuan Zha, C. Lee Giles
Issue Date:October 2007
pp. 739-744
Recent graph-theoretic approaches have demonstrated remarkable successes for ranking networked entities, but most of their applications are limited to homogeneous networks such as the network of citations between publications. This paper proposes a novel m...
 
Discovering Temporal Communities from Social Network Documents
Found in: Data Mining, IEEE International Conference on
By Ding Zhou, Isaac Councill, Hongyuan Zha, C. Lee Giles
Issue Date:October 2007
pp. 745-750
This paper studies the discovery of communities from social network documents produced over time, addressing the discovery of temporal trends in community memberships. We first formulate static community discovery at a single time period as a tripartite gr...
 
Boosting the Feature Space: Text Classification for Unstructured Data on the Web
Found in: Data Mining, IEEE International Conference on
By Yang Song, Ding Zhou, Jian Huang, Isaac G. Councill, Hongyuan Zha, C. Lee Giles
Issue Date:December 2006
pp. 1064-1069
The issue of seeking efficient and effective methods for classifying unstructured text in large document corpora has received much attention in recent years. Traditional document representation like bag-of-words encodes documents as feature vectors, which ...
 
Towards Discovering Organizational Structure from Email Corpus
Found in: Machine Learning and Applications, Fourth International Conference on
By Ding Zhou, Yang Song, Hongyuan Zha, Ya Zhang
Issue Date:December 2005
pp. 279-284
Email logs people's communication history which provides valuable information regarding the infrastructure of an organization. In this paper, a two-phase framework is introduced to attack the problem of leadership discovery in an organization based on emai...
 
Efficient Block Noise Removal Based on Nonlinear Manifolds
Found in: Computer Vision, IEEE International Conference on
By Haoying Fu, Hongyuan Zha, Jesse Barlow
Issue Date:October 2005
pp. 549-556
The problem of block noise removal is considered. It is assumed that the original image is on or close to a sub-space of admissible images in the form of a low dimensional nonlinear manifold. We propose to use a close variant of the total variation regular...
 
Name disambiguation in author citations using a K-way spectral clustering method
Found in: Digital Libraries, Joint Conference on
By C. Lee Giles, Hongyuan Zha, Hui Han
Issue Date:June 2005
pp. 334-343
An author may have multiple names and multiple authors may share the same name simply due to name abbreviations, identical names, or name misspellings in publications or bibliographies 1. This can produce name ambiguity which can affect the performance of ...
 
Protein Interaction Inference as a MAX-SAT Problem
Found in: Computer Vision and Pattern Recognition Workshop
By Ya Zhang, Hongyuan Zha, Chao-Hisen Chu, Xiang Ji
Issue Date:June 2005
pp. 146
<p>Discovering interacting proteins is essential for understanding protein functions. However, high throughput interaction data are inherently noisy and only cover a small portion of the whole interactome. Domains, the building block of proteins, are...
 
A Time-Series Biclustering Algorithm for Revealing Co-Regulated Genes
Found in: Information Technology: Coding and Computing, International Conference on
By Ya Zhang, Hongyuan Zha, Chao-Hisen Chu
Issue Date:April 2005
pp. 32-37
Although existing bicluster algorithms claimed to be able to discover co-regulated genes under a subset of given experiment conditions, they ignore the inherent sequential relationship between crucial time points and thus are not applicable to analyze time...
 
Support Vector Clustering Combined with Spectral Graph Partitioning
Found in: Pattern Recognition, International Conference on
By JinHyeong Park, Xiang Ji, Hongyuan Zha, Rangachar Kasturi
Issue Date:August 2004
pp. 581-584
In this paper, we propose a new support vector clustering (SVC) strategy by combining (SVC) with spectral graph partitioning (SGP). SVC has two main steps: support vector computation and cluster labeling using adjacency matrix. Spectral graph partitioning ...
 
Local Smoothing for Manifold Learning
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By JinHyeong Park, Zhenyue Zhang, Hongyuan Zha, Rangachar Kasturi
Issue Date:July 2004
pp. 452-459
We propose methods for outlier handling and noise reduction using weighted local linear smoothing for a set of noisy points sampled from a nonlinear manifold. Weighted PCA is used as a building block for our methods and we suggest an iterative weight selec...
 
Two Supervised Learning Approaches for Name Disambiguation in Author Citations
Found in: Digital Libraries, Joint Conference on
By Hui Han, Lee Giles, Hongyuan Zha, Cheng Li, Kostas Tsioutsiouliklis
Issue Date:June 2004
pp. 296-305
Due to name abbreviations, identical names, name misspellings, and pseudonyms in publications or bibliographies (citations), an author may have multiple names and multiple authors may share the same name. Such name ambiguity affects the performance of docu...
 
Automatic Document Metadata Extraction Using Support Vector Machines
Found in: Digital Libraries, Joint Conference on
By Hui Han, C. Lee Giles, Eren Manavoglu, Hongyuan Zha, Zhenyue Zhang, Edward A. Fox
Issue Date:May 2003
pp. 37
Automatic metadata generation provides scalability and usability for digital libraries and their collections. Machine learning methods offer robust and adaptable automatic metadata extraction. We describe a Support Vector Machine classification-based metho...
 
Correlating Summarization of A Pair of Multilingual Documents
Found in: Research Issues in Data Engineering, International Workshop on
By Xiang Ji, Hongyuan Zha
Issue Date:March 2003
pp. 39
With the emergence of enormous amount of documents in multiple languages, it is desirable to construct text mining methods that can compare and highlight similarities of them. In this paper, we explore the research issue of comparative summarization for a ...
 
Adaptive dimension reduction for clustering high dimensional data
Found in: Data Mining, IEEE International Conference on
By Chris Ding, Xiaofeng He, Hongyuan Zha, Horst D. Simon
Issue Date:December 2002
pp. 147
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K -means are often trapped in local minimum. Many initialization methods were proposed to tackle this problem, but with only limited success. In this paper w...
 
Indexing management for distributed linear hash files
Found in: Database and Expert Systems Applications, International Workshop on
By Shang-Sheng Tung, Hongyuan Zha, T. Keefe
Issue Date:September 1996
pp. 106
LH* is a scalable distributed data structure that extends linear hashing to support file manipulations in a distributed environment. The purpose of the paper is to investigate the behavior of concurrent transactions in the context of LH*. We present an alg...
 
Simultaneous Classification and Feature Clustering Using Discriminant Vector Quantization with Applications to Microarray Data Analysis
Found in: Computational Systems Bioinformatics Conference, International IEEE Computer Society
By Jia Li, Hongyuan Zha
Issue Date:August 2002
pp. 246
In many applications of supervised learning, automatic feature clustering is often desirable for a better understanding of the interaction among the various features as well as the interplay between the features and the class labels. In addition, for high ...
 
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering
Found in: Data Mining, IEEE International Conference on
By Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Ming Gu, Horst D. Simon
Issue Date:December 2001
pp. 107
An important application of graph partitioning is data clustering using a graph model - the pairwise similarities between all data objects form a weighted graph adjacency matrix that contains all necessary information for clustering. Here we propose a new ...
 
Dyadic event attribution in social networks with mixtures of hawkes processes
Found in: Proceedings of the 22nd ACM international conference on Conference on information & knowledge management (CIKM '13)
By Hongyuan Zha, Liangda Li
Issue Date:October 2013
pp. 1667-1672
In many applications in social network analysis, it is important to model the interactions and infer the influence between pairs of actors, leading to the problem of dyadic event modeling which has attracted increasing interests recently. In this paper we ...
     
Improving recency ranking using twitter data
Found in: ACM Transactions on Intelligent Systems and Technology (TIST)
By Anlei Dong, Fernanodo Diaz, Hongyuan Zha, Pranam Kolari, Ruiqiang Zhang, Yan Liu, Yi Chang, Yoshiyuki Inagaki
Issue Date:January 2013
pp. 1-24
In Web search and vertical search, recency ranking refers to retrieving and ranking documents by both relevance and freshness. As impoverished in-links and click information is the the biggest challenge for recency ranking, we advocate the use of Twitter d...
     
Collaborative ranking: improving the relevance for tail queries
Found in: Proceedings of the 21st ACM international conference on Information and knowledge management (CIKM '12)
By Hongyuan Zha, Ke Zhou, Xin Li
Issue Date:October 2012
pp. 1900-1904
It is well known that tail queries contribute to a substantial fraction of distinct queries submitted to search engines and thus become a major battle field for search engines. Unfortunately, compared with popular queries, it is much more difficult to obta...
     
Friend or frenemy?: predicting signed ties in social networks
Found in: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval (SIGIR '12)
By Alexander J. Smola, Bo Long, Hongyuan Zha, Shuang-Hong Yang, Yi Chang
Issue Date:August 2012
pp. 555-564
We study the problem of labeling the edges of a social network graph (e.g., acquaintance connections in Facebook) as either positive (i.e., trust, true friendship) or negative (i.e., distrust, possible frenemy) relations. Such signed relations provide much...
     
Learning binary codes for collaborative filtering
Found in: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '12)
By Hongyuan Zha, Ke Zhou
Issue Date:August 2012
pp. 498-506
This paper tackles the efficiency problem of making recommendations in the context of large user and item spaces. In particular, we address the problem of learning binary codes for collaborative filtering, which enables us to efficiently make recommendatio...
     
Leveraging Auxiliary Data for Learning to Rank
Found in: ACM Transactions on Intelligent Systems and Technology (TIST)
By Ke Zhou, Gui-Rong Xue, Hongyuan Zha, Jing Bai
Issue Date:February 2012
pp. 1-21
In learning to rank, both the quality and quantity of the training data have significant impacts on the performance of the learned ranking functions. However, in many applications, there are usually not sufficient labeled training data for the construction...
     
Advertising Keywords Recommendation for Short-Text Web Pages Using Wikipedia
Found in: ACM Transactions on Intelligent Systems and Technology (TIST)
By Hongyuan Zha, Dingquan Wang, Gui-Rong Xue, Weinan Zhang
Issue Date:February 2012
pp. 1-25
Advertising keywords recommendation is an indispensable component for online advertising with the keywords selected from the target Web pages used for contextual advertising or sponsored search. Several ranking-based algorithms have been proposed for recom...
     
Functional matrix factorizations for cold-start recommendation
Found in: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information (SIGIR '11)
By Hongyuan Zha, Ke Zhou, Shuang-Hong Yang
Issue Date:July 2011
pp. 315-324
A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressively querying user responses through an initial interview process has been propose...
     
Collaborative competitive filtering: learning recommender using context of user choice
Found in: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information (SIGIR '11)
By Alexander J. Smola, Bo Long, Hongyuan Zha, Shuang-Hong Yang, Zhaohui Zheng
Issue Date:July 2011
pp. 295-304
While a user's preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learning recommender models. In particular, existing collaborative filtering (CF) appr...
     
Like like alike: joint friendship and interest propagation in social networks
Found in: Proceedings of the 20th international conference on World wide web (WWW '11)
By Alex Smola, Bo Long, Hongyuan Zha, Narayanan Sadagopan, Shuang-Hong Yang, Zhaohui Zheng
Issue Date:March 2011
pp. 537-546
Targeting interest to match a user with services (e.g. news, products, games, advertisements) and predicting friendship to build connections among users are two fundamental tasks for social network systems. In this paper, we show that the information conta...
     
Video summarization via transferrable structured learning
Found in: Proceedings of the 20th international conference on World wide web (WWW '11)
By Gui-Rong Xue, Hongyuan Zha, Ke Zhou, Liangda Li, Yong Yu
Issue Date:March 2011
pp. 287-296
It is well-known that textual information such as video transcripts and video reviews can significantly enhance the performance of video summarization algorithms. Unfortunately, many videos on the Web such as those from the popular video sharing site YouTu...
     
Learning to blend rankings: a monotonic transformation to blend rankings from heterogeneous domains
Found in: Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM '10)
By Hongyuan Zha, Yi Chang, Zhaohui Zheng, Zhenzhen Kou
Issue Date:October 2010
pp. 1921-1924
There have been great needs to develop effective methods for combining multiple rankings from heterogeneous domains into one single rank list arising from many recent web search applications, such as integrating web search results from multiple engines, fa...
     
Language pyramid and multi-scale text analysis
Found in: Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM '10)
By Hongyuan Zha, Shuang-Hong Yang
Issue Date:October 2010
pp. 639-648
The classical Bag-of-Word (BOW) model represents a document as a histogram of word occurrence, losing the spatial information that is invaluable for many text analysis tasks. In this paper, we present the Language Pyramid (LaP) model, which casts a documen...
     
Ranking with query-dependent loss for web search
Found in: Proceedings of the third ACM international conference on Web search and data mining (WSDM '10)
By Hongyuan Zha, Jiang Bian, Tao Qin, Tie-Yan Liu
Issue Date:February 2010
pp. 141-150
Queries describe the users' search intent and therefore they play an essential role in the context of ranking for information retrieval and Web search. However, most of existing approaches for ranking do not explicitly take into consideration the fact that...
     
Smoothing DCG for learning to rank: a novel approach using smoothed hinge functions
Found in: Proceeding of the 18th ACM conference on Information and knowledge management (CIKM '09)
By Hongyuan Zha, Mingrui Wu, Yi Chang, Zhaohui Zheng
Issue Date:November 2009
pp. 1923-1926
Discounted cumulative gain (DCG) is widely used for evaluating ranking functions. It is therefore natural to learn a ranking function that directly optimizes DCG. However, DCG is non-smooth, rendering gradient-based optimization algorithms inapplicable. To...
     
Multi-task learning for learning to rank in web search
Found in: Proceeding of the 18th ACM conference on Information and knowledge management (CIKM '09)
By Belle Tseng, Gordon Sun, Guirong Xue, Hongyuan Zha, Jing Bai, Ke Zhou, Yi Chang, Zhaohui Zheng
Issue Date:November 2009
pp. 1549-1552
Both the quality and quantity of training data have significant impact on the performance of ranking functions in the context of learning to rank for web search. Due to resource constraints, training data for smaller search engine markets are scarce and we...
     
Learning distance metric for regression by semidefinite programming with application to human age estimation
Found in: Proceedings of the seventeen ACM international conference on Multimedia (MM '09)
By Bo Xiao, Hongyuan Zha, Xiaokang Yang, Yi Xu
Issue Date:October 2009
pp. 451-460
A good distance metric for the input data is crucial in many pattern recognition and machine learning applications. Past studies have demonstrated that learning a metric from labeled samples can significantly improve the performance of classification and c...
     
Global ranking by exploiting user clicks
Found in: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval (SIGIR '09)
By Ciya Liao, Gordon Sun, Gui-Rong Xue, Hongyuan Zha, Ke Zhou, Olivier Chapelle, Shihao Ji, Zhaohui Zheng
Issue Date:July 2009
pp. 435-435
It is now widely recognized that user interactions with search results can provide substantial relevance information on the documents displayed in the search results. In this paper, we focus on extracting relevance information from one source of user inter...
     
Web-scale classification with naive bayes
Found in: Proceedings of the 18th international conference on World wide web (WWW '09)
By Congle Zhang, Gui-Rong Xue, Hongyuan Zha, Yong Yu
Issue Date:April 2009
pp. 66-66
Traditional Naive Bayes Classifier performs miserably on web-scale taxonomies. In this paper, we investigate the reasons behind such bad performance. We discover that the low performance are not completely caused by the intrinsic limitations of Naive Bayes...
     
Enhancing diversity, coverage and balance for summarization through structure learning
Found in: Proceedings of the 18th international conference on World wide web (WWW '09)
By Gui-Rong Xue, Hongyuan Zha, Ke Zhou, Liangda Li, Yong Yu
Issue Date:April 2009
pp. 66-66
Document summarization plays an increasingly important role with the exponential growth of documents on the Web. Many supervised and unsupervised approaches have been proposed to generate summaries from documents. However, these approaches seldom simultane...
     
Learning to recognize reliable users and content in social media with coupled mutual reinforcement
Found in: Proceedings of the 18th international conference on World wide web (WWW '09)
By Ding Zhou, Eugene Agichtein, Hongyuan Zha, Jiang Bian, Yandong Liu
Issue Date:April 2009
pp. 66-66
Community Question Answering (CQA) has emerged as a popular forum for users to pose questions for other users to answer. Over the last few years, CQA portals such as Naver and Yahoo! Answers have exploded in popularity, and now provide a viable alternative...
     
A scalable assistant librarian: hierarchical subject classification of books
Found in: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '08)
By Hongyuan Zha, Jian Huang, Steven P. Crain
Issue Date:July 2008
pp. 2-2
In this paper, we discuss our work in progress towards a scalable hierarchical classification system for books using the Library of Congress subject hierarchy. We examine the characteristics of this domain which make the problem very challenging, and we lo...
     
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