Conference proceeding
ExSearch: a novel vertical search engine for online barter business
Proceedings of the 18th ACM conference on information and knowledge management, pp.1357-1366
CIKM '09
11/02/2009
DOI: 10.1145/1645953.1646125
Abstract
E-Commerce has shown its exponentially-growing business value in the past decade. However, in contrast to the successful examples in online sales, such as Amazon 1 and eBay 2 , the online barter business is still underexplored due to the lack of corresponding information aggregation service. In this paper, we design and implement a novel vertical search engine, called ExSearch, to aggregate online barter information for developing the barter market. Different from classical general purpose Web search engines, ExSearch adopts a focused crawler to gather related information from various websites. We propose to automatically extract the barter information from free-text Web pages such that the unstructured information is represented in structured databases. In addition, we utilize the data mining techniques such as regression to fulfill the missing information, which cannot be extracted from the Web pages. Finally, we validate and rank the search results according to user queries. Experimental results show that each component module in our proposed ExSearch system is efficient and effective. The volunteer users are satisfied by and interested in this novel vertical search engine.
Details
- Title: Subtitle
- ExSearch: a novel vertical search engine for online barter business
- Creators
- Lei Ji - Microsoft Research AsiaJun Yan - Microsoft Research AsiaNing Liu - Microsoft Research AsiaWen Zhang - University of Science and Technology of ChinaWeiguo Fan - Virginia TechZheng Chen - Microsoft Research Asia
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the 18th ACM conference on information and knowledge management, pp.1357-1366
- Publisher
- ACM
- Series
- CIKM '09
- DOI
- 10.1145/1645953.1646125
- Language
- English
- Date published
- 11/02/2009
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380377202771
Metrics
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