DocumentCode :
1667838
Title :
Supporting Data Driven Access through Automatic Keyword Extraction and Summarization
Author :
Weijia Xu ; Wei Luo ; Woodward, Nicholas ; Yan Zhang
Author_Institution :
Univ. of Texas at Austin, Austin, TX, USA
fYear :
2015
Firstpage :
704
Lastpage :
707
Abstract :
The ever-increasing user generated digital data available through the Internet has become an important source of information for individuals, organizations and government agencies. And yet, for users to fully discover and utilize those information remains a complex tasks. Existing popular information access models based on keyword and/or facet searches become less effective in providing access to specific sets of user generated data. To address their limitation, we propose an approach where keywords and summarization of subset of document could be automatically generated during an interactive user session to facilitate user´s information seeking process. In this paper, we present our preliminary development including a new algorithm for keyword extraction and summarization generation simultaneously over a subset of documents and visual representations of those results to assist user explorations.
Keywords :
Internet; information retrieval; text analysis; Internet; automatic keyword extraction; data driven access; facet searches; government agencies; information access models; information seeking process; interactive user session; organizations; summarization generation; user explorations; user generated digital data; visual representations; Clustering algorithms; Data mining; Data visualization; Internet; Tag clouds; Visual analytics; Web archive; keyword extraction; visual exploration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data (BigData Congress), 2015 IEEE International Congress on
Conference_Location :
New York, NY
Print_ISBN :
978-1-4673-7277-0
Type :
conf
DOI :
10.1109/BigDataCongress.2015.113
Filename :
7207297
Link To Document :
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