Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Reexamining the cluster hypothesis: scatter/gather on retrieval results
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
The Journal of Machine Learning Research
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
ICML '06 Proceedings of the 23rd international conference on Machine learning
Pachinko allocation: DAG-structured mixture models of topic correlations
ICML '06 Proceedings of the 23rd international conference on Machine learning
Training linear SVMs in linear time
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning to link with wikipedia
Proceedings of the 17th ACM conference on Information and knowledge management
A survey of Web clustering engines
ACM Computing Surveys (CSUR)
AQTR '08 Proceedings of the 2008 IEEE International Conference on Automation, Quality and Testing, Robotics - Volume 03
Web Search Clustering and Labeling with Hidden Topics
ACM Transactions on Asian Language Information Processing (TALIP)
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Detecting topic evolution in scientific literature: how can citations help?
Proceedings of the 18th ACM conference on Information and knowledge management
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies
Journal of the ACM (JACM)
TAGME: on-the-fly annotation of short text fragments (by wikipedia entities)
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Topic-driven web search result organization by leveraging wikipedia semantic knowledge
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Topical clustering of search results
Proceedings of the fifth ACM international conference on Web search and data mining
An open-source toolkit for mining Wikipedia
Artificial Intelligence
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Searching for scientific publications on the Web is a tedious task, especially when exploring an unfamiliar domain. Typical scholarly search engines produce lengthy unstructured result lists that are difficult to comprehend, interpret and browse. We propose a novel method of organizing the search results into concise and informative topic hierarchies. The method consists of two steps: extracting interrelated topics from the result set, and summarizing the topic graph. In the first step we map the search results to articles and categories of Wikipedia, constructing a graph of relevant topics with hierarchical relations. In the second step we sequentially build nested summaries of the produced topic graph using a structured output prediction approach. Trained on a small number of examples, our method learns to construct informative summaries for unseen topic graphs, and outperforms unsupervised state-of-the-art Wikipedia-based clustering.