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Multi-View Clustering via Joint Nonnegative Matrix Factorization
This paper proposes a novel NMFbased multi-view clustering algorithm by searching for a factorization that gives compatible clustering solutions across multiple views and designs a novel and effective normalization strategy inspired by the connection between NMF and PLSA.
Automated Phrase Mining from Massive Text Corpora
- Jingbo Shang, Jialu Liu, Meng Jiang, Xiang Ren, Clare R. Voss, Jiawei Han
- Computer ScienceIEEE Transactions on Knowledge and Data…
- 15 February 2017
This paper proposes a novel framework for automated phrase mining, which supports any language as long as a general knowledge base in that language is available, while benefiting from, but not requiring, a POS tagger.
Mining Quality Phrases from Massive Text Corpora
- Jialu Liu, Jingbo Shang, Chi Wang, Xiang Ren, Jiawei Han
- Computer ScienceSIGMOD Conference
- 27 May 2015
A new framework that extracts quality phrases from text corpora integrated with phrasal segmentation is proposed, which requires only limited training but the quality of phrases so generated is close to human judgment.
Large-Scale Embedding Learning in Heterogeneous Event Data
- Huan Gui, Jialu Liu, Fangbo Tao, Meng Jiang, Brandon Norick, Jiawei Han
- Computer ScienceIEEE 16th International Conference on Data Mining…
- 1 December 2016
The Hebe framework models the proximity among objects in an event by predicting a target object given the other participating objects in the event (hyperedge) and is robust to data sparseness.
Meta-Path Guided Embedding for Similarity Search in Large-Scale Heterogeneous Information Networks
- Jingbo Shang, Meng Qu, Jialu Liu, Lance M. Kaplan, Jiawei Han, Jian Peng
- Computer ScienceArXiv
- 31 October 2016
This paper re-examine similarity search in HINs and proposes a novel embedding-based framework, ESim, that accepts user-defined meta-paths as guidance to learn vertex vectors in a user-preferred embedding space to explore network structure-embedded similarity.
Gaussian Mixture Model with Local Consistency
- Jialu Liu, Deng Cai, Xiaofei He
- Computer ScienceAAAI Conference on Artificial Intelligence
- 3 July 2010
A novel method based on manifold structure for data clustering, called Locally Consistent Gaussian Mixture Model (LCGMM), is introduced, which construct a nearest neighbor graph and adopt Kullback-Leibler Divergence as the distance measurement to regularize the objective function of GMM.
ClusCite: effective citation recommendation by information network-based clustering
A novel cluster-based citation recommendation framework, called ClusCite, which explores the principle that citations tend to be softly clustered into interest groups based on multiple types of relationships in the network, and learns group memberships for objects and the significance of relevance features for each interest group by solving a joint optimization problem.
Representing Documents via Latent Keyphrase Inference
- Jialu Liu, Xiang Ren, Jingbo Shang, Taylor Cassidy, Clare R. Voss, Jiawei Han
- Computer ScienceWWW
- 11 April 2016
This paper proposes a data-driven model named Latent Keyphrase Inference LAKI that represents documents with a vector of closely related domain keyphrases instead of single words or existing concepts in the knowledge base, and shows that given a corpus of in-domain documents, topical content units can be learned for each domain keyphrase.
Large-Scale Spectral Clustering on Graphs
- Jialu Liu, Chi Wang, Marina Danilevsky, Jiawei Han
- Computer ScienceInternational Joint Conference on Artificial…
- 3 August 2013
The key idea is to repeatedly generate a small number of "supernodes" connected to the regular nodes, in order to compress the original graph into a sparse bipartite graph.