Towards a Plug-and-Play B2B Marketing Tool Based on Time-Sensitive Information Extraction

Author(s):  
Matt Callery ◽  
Fenno Heath ◽  
Richard Hull ◽  
Mark Linehan ◽  
Piwadee Sukaviriya ◽  
...  
Author(s):  
Andreea Diosteanu ◽  
Armando Stellato ◽  
Andrea Turbati

In this chapter, the authors present Service Oriented Data Acquisition (SODA), a service-deployable open-source platform for retrieving and dynamically aggregating information extraction and knowledge acquisition software components. The motivation in creating such a system came from the observed gap between the large availability of Information Analysis components for different frameworks (such as UIMA [Ferrucci & Lally, 2004] and GATE [Cunningham, Maynard, Bontcheva, & Tablan, 2002]) and the difficulties in discovering, retrieving, integrating these components, and embedding them into software systems for knowledge feeding. By analyzing the research area, the authors noticed that there are a few solutions for this problem, though they all lack in assuring a great level of platform independence, collaboration, flexibility, and most of all, openness. The solution that they propose is targeted to different kinds of users, from application developers, benefiting from a semantic repository of inter-connectable information extraction and ontology feeding components, to final users, who can plug and play these components through SODA compliant clients.


2020 ◽  
Vol 57 (12) ◽  
pp. 120003
Author(s):  
维 Mu Haiwei ◽  
王妙妙 Wang Miaomiao ◽  
韩建 Han Jian ◽  
曹志民 Cao Zhimin

2018 ◽  
Vol 2018 ◽  
pp. 441-442
Author(s):  
Rosy Boardman ◽  
◽  
Marta Blazquez Cano ◽  
Shaoqianqian Deng
Keyword(s):  

2013 ◽  
Vol 7 (2) ◽  
pp. 574-579 ◽  
Author(s):  
Dr Sunitha Abburu ◽  
G. Suresh Babu

Day by day the volume of information availability in the web is growing significantly. There are several data structures for information available in the web such as structured, semi-structured and unstructured. Majority of information in the web is presented in web pages. The information presented in web pages is semi-structured.  But the information required for a context are scattered in different web documents. It is difficult to analyze the large volumes of semi-structured information presented in the web pages and to make decisions based on the analysis. The current research work proposed a frame work for a system that extracts information from various sources and prepares reports based on the knowledge built from the analysis. This simplifies  data extraction, data consolidation, data analysis and decision making based on the information presented in the web pages.The proposed frame work integrates web crawling, information extraction and data mining technologies for better information analysis that helps in effective decision making.   It enables people and organizations to extract information from various sourses of web and to make an effective analysis on the extracted data for effective decision making.  The proposed frame work is applicable for any application domain. Manufacturing,sales,tourisum,e-learning are various application to menction few.The frame work is implemetnted and tested for the effectiveness of the proposed system and the results are promising.


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