• Publications
  • Influence
Towards social user profiling: unified and discriminative influence model for inferring home locations
TLDR
We propose a unified discriminative influence model, named as UDI, that captures how likely a user connects to a signal with respect to distance between the user and the signal, and the influence scope of the signal. Expand
  • 306
  • 22
  • PDF
Probabilistic topic models with biased propagation on heterogeneous information networks
TLDR
We propose a novel topic model with biased propagation (TMBP) algorithm to directly incorporate heterogeneous information network with topic modeling in a unified way. Expand
  • 116
  • 15
  • PDF
SHRINK: a structural clustering algorithm for detecting hierarchical communities in networks
TLDR
In this paper, we propose a parameter-free hierarchical network clustering algorithm SHRINK by combining the advantages of density-based clustering and modularity optimization methods. Expand
  • 125
  • 14
  • PDF
Formal Models for Expert Finding on DBLP Bibliography Data
TLDR
We present three models for expert finding based on the large-scale DBLP bibliography and Google scholar for data supplementation. Expand
  • 152
  • 11
  • PDF
A generalized Co-HITS algorithm and its application to bipartite graphs
TLDR
We propose a novel and general Co-HITS algorithm to incorporate the bipartite graph with the content information from both sides as well as the constraints of relevance. Expand
  • 139
  • 11
  • PDF
Entropy-biased models for query representation on the click graph
TLDR
In this paper, we investigate and develop a novel entropy-biased framework for modeling click graphs and introduce a new concept, namely the inverse query frequency (IQF), to weigh the importance (discriminative ability) of a click on a certain URL. Expand
  • 65
  • 5
  • PDF
gSkeletonClu: Density-Based Network Clustering via Structure-Connected Tree Division or Agglomeration
TLDR
We propose a novel density-based network clustering algorithm, called gSkeletonClu (graph-skeleton based clustering). Expand
  • 62
  • 5
  • PDF
Modeling and exploiting heterogeneous bibliographic networks for expertise ranking
TLDR
In this paper, we propose a joint regularization framework to enhance expertise retrieval by modeling heterogeneous networks as regularization constraints on top of document-centric model. Expand
  • 54
  • 5
  • PDF
Enhanced Models for Expertise Retrieval Using Community-Aware Strategies
TLDR
We investigate and develop two community-aware strategies to enhance expertise retrieval, including a new smoothing method based on community context and a community-sensitive AuthorRank based on coauthorship networks. Expand
  • 30
  • 5
A two-dimensional click model for query auto-completion
TLDR
Query auto-completion (QAC) facilitates faster user query input by predicting users' intended queries. Expand
  • 48
  • 4
  • PDF