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AllInOneNews: development and evaluation of a large-scale news metasearch engine
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International Conference on Management of Data archive
Proceedings of the 2007 ACM SIGMOD international conference on Management of data table of contents
Beijing, China
SESSION: Data processing in the large table of contents
Pages: 1017 - 1028  
Year of Publication: 2007
ISBN:978-1-59593-686-8
Authors
King-Lup Liu  Webscalers, LLC, Lafayette, LA
Weiyi Meng  Webscalers, LLC, Lafayette, LA
Jing Qiu  Webscalers, LLC, Lafayette, LA
Clement Yu  Webscalers, LLC, Lafayette, LA
Vijay Raghavan  Webscalers, LLC, Lafayette, LA
Zonghuan Wu  Webscalers, LLC, Lafayette, LA
Yiyao Lu  Webscalers, LLC, Lafayette, LA
Hai He  Webscalers, LLC, Lafayette, LA
Hongkun Zhao  Webscalers, LLC, Lafayette, LA
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

AllInOneNews is the largest news metasearch engine in the world, connecting to over 1,000 news sites over 150 countries. Implementing a large-scale metasearch engine like AllInOneNews needs to overcome unique challenges not faced by building small metasearch engines such as developing highly scalable search engine selection techniques. In this paper, we discuss these unique challenges and our solutions to these challenges. We also discuss some novel features of AllInOneNews such as highly automated solution and semantic query match. This paper also reports the results of a comparative evaluation of three commercial news search systems, one search engine - Google News and two metasearch engines - Mamma News and AllInOneNews. Several measures such as effectiveness, diversity and time-sensitivity are used to perform the comparison. Another contribution of this paper is that we introduce a novel scheme to compare multiple news search systems in a combined measure that takes both relevance and time-sensitivity of retrieved information into consideration.


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.

 
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Collaborative Colleagues:
King-Lup Liu: colleagues
Weiyi Meng: colleagues
Jing Qiu: colleagues
Clement Yu: colleagues
Vijay Raghavan: colleagues
Zonghuan Wu: colleagues
Yiyao Lu: colleagues
Hai He: colleagues
Hongkun Zhao: colleagues