Top-K Entity Units Retrieval Over Big Data

被引:2
作者
Zhang, Da [1 ]
Kabuka, Mansur R. [1 ]
机构
[1] Univ Miami, Coral Gables, FL 33146 USA
来源
WWW'17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB | 2017年
关键词
Big Data; Information Retrieval; Keyword Searching;
D O I
10.1145/3041021.3053063
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
During the past several years, data size has increased explosively. This data explosion tendency has impacted various fields ranging from biomedical engineering, business consulting to social media and mobile application. Big Data is a two sided sword. While it provides incredibly treasured insights in commercial scope and innovative discovery in the scientific field, Big Data also has many challenges, such as complication in data storage, data processing, data analysis and data visualization. Among all these challenges, keyword searching over a large volume of data prevails as one of the four tasks defined by Bizer et al. at the year of 2012. Keyword searching refers to retrieving the objects relevant to the entities of concern using scientific computational methods. Consequently, efficiently solving the problem of keyword searching can contribute as a foundation to diverse Big Data applications.
引用
收藏
页码:1269 / 1272
页数:4
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