• Publications
  • Influence
Multi-document summarization using cluster-based link analysis
Experimental results on the DUC2001 and DUC2002 datasets demonstrate the good effectiveness of the proposed summarization models and demonstrate that the ClusterCMRW model is more robust than the ClusterHITS model, with respect to different cluster numbers. Expand
Manifold-Ranking Based Topic-Focused Multi-Document Summarization
A novel extractive approach based on manifold-ranking of sentences to this summarization task can significantly outperform existing approaches of the top performing systems in DUC tasks and baseline approaches. Expand
Towards an Iterative Reinforcement Approach for Simultaneous Document Summarization and Keyword Extraction
A novel iterative reinforcement approach to simultaneously extractingsummary and keywords from single document under the assumption that the summary and keywords of a document can be mutually boosted. Expand
Towards a unified approach to document similarity search using manifold-ranking of blocks
A novel retrieval approach based on manifold-ranking of document blocks to re-rank a small set of documents initially retrieved by some existing retrieval function by propagating the ranking scores between the blocks on a weighted graph. Expand
Exploiting real-time information retrieval in the microblogosphere
This paper introduces a two-stage pseudo-relevance feedback query expansion to overcome the severe vocabulary-mismatch problem of short message retrieval in microblog, and suggests several methods to evaluate the temporal aspects of documents. Expand
XML Document Classification Using Extended VSM
The experimental results on the challenge's data set show that the classification approach for XML documents based on SLVM and Support Vector Machine outperforms any other approach on XML document classification task at the challenge. Expand
CollabSum: exploiting multiple document clustering for collaborative single document summarizations
This paper proposes a novel framework called CollabSum for collaborative single document summarizations by making use of mutual influences of multiple documents within a cluster context by first employing the clustering algorithm to obtain appropriate document clusters and then exploiting the graph-ranking based algorithm for collaborative document summarization within each cluster. Expand
Exploiting ranking factorization machines for microblog retrieval
A Ranking Factorization Machine (Ranking FM) model is proposed, which applies Factorization machine model to microblog ranking on basis of pairwise classification, and demonstrates its superiority over several baseline systems on a real Twitter dataset in terms of P@30 and MAP metrics. Expand
Improving Microblog Retrieval with Feedback Entity Model
A feedback entity model is proposed and integrated into an adaptive language modeling framework in order to improve the retrieval performance of tweets and demonstrates the significant superiority of this approach over the state-of-the-art baselines. Expand
Improved Affinity Graph Based Multi-Document Summarization
This paper describes an affinity graph based approach to multi-document summarization. We incorporate a diffusion process to acquire semantic relationships between sentences, and then computeExpand