Predicting the relevance of search results for e-commerce systems
Search engines (e.g. Google.com, Yahoo.com, and Bing.com) have become the dominant model of online search. Large and small e-commerce provide built-in search capability to their visitors to examine the products they have. While most large business are able to hire the necessary skills to build advan...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
International Center for Scientific Research and Studies (ICSRS)
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/54984/ |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | Search engines (e.g. Google.com, Yahoo.com, and Bing.com) have become the dominant model of online search. Large and small e-commerce provide built-in search capability to their visitors to examine the products they have. While most large business are able to hire the necessary skills to build advanced search engines, small online business still lack the ability to evaluate the results of their search engines, which means losing the opportunity to compete with larger business. The purpose of this paper is to build an open-source model that can measure the relevance of search results for online businesses as well as the accuracy of their underlined algorithms. We used data from a Kaggle.com competition in order to show our model running on real data. |
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