ACM Home Page
Please provide us with feedback. Feedback
sMash: semantic-based mashup navigation for data API network
Full text PdfPdf (1.90 MB)
Source
International World Wide Web Conference archive
Proceedings of the 18th international conference on World wide web table of contents
Madrid, Spain
POSTER SESSION: Thursday, April 23, 2009 table of contents
Pages 1133-1134  
Year of Publication: 2009
ISBN:978-1-60558-487-4
Authors
Bin Lu  College of Computer Science, Zhejiang University, Hangzhou, China
Zhaohui Wu  College of Computer Science, Zhejiang University, Hangzhou, China
Yuan Ni  IBM China Research Lab, Beijing, China
Guotong Xie  IBM China Research Lab, Beijing, China
Chunying Zhou  College of Computer Science, Zhejiang University, Hangzhou, China
Huajun Chen  College of Computer Science, Zhejiang University, Hangzhou, China
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 22,   Downloads (12 Months): 126,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1526709.1526893
What is a DOI?

ABSTRACT

With the proliferation of data APIs, it is not uncommon that users who have no clear ideas about data APIs will encounter difficulties to build Mashups to satisfy their requirements. In this paper, we present a semantic-based mashup navigation system, sMash that makes mashup building easy by constructing and visualizing a real-life data API network. We build a sample network by gathering more than 300 popular APIs and find that the relationships between them are so complex that our system will play an important role in navigating users and give them inspiration to build interesting mashups easily. The system is accessible at: http://www.dart.zju.edu.cn/mashup.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
D. Butler. Mashups mix data into global service. Nature, 439(5):6--7, 2006.
 
2
 
3
Microsoft Popfly: http://www.popfly.com/
 
4
QEDWiki: http://www.alphaworks.ibm.com/tech/qedwiki
 
5
Yahoo! Pipes: http://pipes.yahoo.com

Collaborative Colleagues:
Bin Lu: colleagues
Zhaohui Wu: colleagues
Yuan Ni: colleagues
Guotong Xie: colleagues
Chunying Zhou: colleagues
Huajun Chen: colleagues