A phrase mining framework for recursive construction of a topical hierarchy

Chi Wang, Marina Danilevsky, Nihit Desai, Yinan Zhang, Phuong Nguyen, Thrivikrama Taula, Jiawei Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A high quality hierarchical organization of the concepts in a dataset at different levels of granularity has many valuable applications such as search, summarization, and content browsing. In this paper we propose an algorithm for recursively constructing a hierarchy of topics from a collection of content-representative documents. We characterize each topic in the hierarchy by an integrated ranked list of mixed-length phrases. Our mining framework is based on a phrase-centric view for clustering, extracting, and ranking topical phrases. Experiments with datasets from different domains illustrate our ability to generate hierarchies of high quality topics represented by meaningful phrases.

Original languageEnglish (US)
Title of host publicationKDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
EditorsRajesh Parekh, Jingrui He, Dhillon S. Inderjit, Paul Bradley, Yehuda Koren, Rayid Ghani, Ted E. Senator, Robert L. Grossman, Ramasamy Uthurusamy
PublisherAssociation for Computing Machinery
Pages437-445
Number of pages9
ISBN (Electronic)9781450321747
DOIs
StatePublished - Aug 11 2013
Event19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013 - Chicago, United States
Duration: Aug 11 2013Aug 14 2013

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
VolumePart F128815

Other

Other19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013
CountryUnited States
CityChicago
Period8/11/138/14/13

Keywords

  • Keyphrase extraction
  • Keyphrase ranking
  • Network analysis
  • Ontology learning
  • Topic modeling

ASJC Scopus subject areas

  • Software
  • Information Systems

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  • Cite this

    Wang, C., Danilevsky, M., Desai, N., Zhang, Y., Nguyen, P., Taula, T., & Han, J. (2013). A phrase mining framework for recursive construction of a topical hierarchy. In R. Parekh, J. He, D. S. Inderjit, P. Bradley, Y. Koren, R. Ghani, T. E. Senator, R. L. Grossman, & R. Uthurusamy (Eds.), KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 437-445). [2487631] (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. Part F128815). Association for Computing Machinery. https://doi.org/10.1145/2487575.2487631