2026-09-20T09:04:16Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/49348 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Han, Jiawei Lei, Kin Hou 2014-05-30T16:39:26Z 2014-05-30T16:39:26Z 2014-05 2014-05-30T16:39:26Z 2014-05 Multi-dimensional data is one of the most abundant and publicly available data sources for people to access today. It forms hierarchy naturally(e.g., people publish posts about different topics or share information from various countries. Given a topic such as technology, it many form sub-topics like mobile devices and web news. Similarly, given a country, it naturally forms hierarchy such as states, counties, cities, and towns). Multi-dimensional data may also interlink together with URLs, images, videos and people to form a rich heterogeneous information network. In this study, we propose ONet to search, explore and visualize hierarchical summarization on multi-dimensional data. In particular, we take Twitter data as an example to show the power of integration of data warehouse and OLAP technologies with information network. Based on Twitter data, ONet summarized important events at different granularities. With the interlinked events and other entities consisted in the network, we investigated some state-of-the-art ranking algorithms, and developed a ranking model in a learning-to-rank approach to rank heterogeneous entities. Experimental results on a large scale real data set show that our proposed ranking model achieves high efficiency and outperforms all compared baselines. Item withdrawn by Alexis Thompson (athmpsn1@illinois.edu) on 2014-04-25T16:25:57Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 LEI_KINHOU.pdf: 3940319 bytes, checksum: 7b7fb7e0da7544d8aacc013b2e47876e (MD5) Made available in DSpace on 2014-05-30T16:39:26Z (GMT). No. of bitstreams: 2 Kin Hou_Lei.pdf: 3940319 bytes, checksum: 7b7fb7e0da7544d8aacc013b2e47876e (MD5) license.txt: 4058 bytes, checksum: 7e862d25a43fe9d5707cc95892da8cb1 (MD5) http://hdl.handle.net/2142/49348 en Copyright 2014 Kin Hou Lei Heterogeneous Information Network Online Analytical Processing ONet: Search, explore, and visualize hierarchical topic summarization on Twitter using network-OLAP text Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Thesis M.S. MS:Computer Science -UIUC 10KS0112MS