A data mining application on predicting relevance of search results from E-commerce platforms
Search engines like google.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 o...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/10356/70196 |
| _version_ | 1826130230988767232 |
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| author | Li, Yuanrui |
| author2 | Xiao Xiaokui |
| author_facet | Xiao Xiaokui Li, Yuanrui |
| author_sort | Li, Yuanrui |
| collection | NTU |
| description | Search engines like google.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 capability to evaluate the results of their search engines, which means losing the opportunity to compete with larger business. The purpose of this project is to build an open-source solution that could measure the relevance of search results for online business as well as the accuracy of their underlined algorithms.
The data set is taken from ‘CrowdFlower Search Result Relevance’ competition from Kaggle.com. A data mining application is implemented using Python and R language, with design for automating the process of feature engineering and model parameter tuning. As a result, the application helps to reduce the time for searching out the best optimal model and at the same time, maintain a good quality of prediction accuracy rate. |
| first_indexed | 2024-10-01T07:53:05Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/70196 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:53:05Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | ntu-10356/701962023-03-03T20:40:16Z A data mining application on predicting relevance of search results from E-commerce platforms Li, Yuanrui Xiao Xiaokui School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering Search engines like google.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 capability to evaluate the results of their search engines, which means losing the opportunity to compete with larger business. The purpose of this project is to build an open-source solution that could measure the relevance of search results for online business as well as the accuracy of their underlined algorithms. The data set is taken from ‘CrowdFlower Search Result Relevance’ competition from Kaggle.com. A data mining application is implemented using Python and R language, with design for automating the process of feature engineering and model parameter tuning. As a result, the application helps to reduce the time for searching out the best optimal model and at the same time, maintain a good quality of prediction accuracy rate. Bachelor of Engineering (Computer Science) 2017-04-15T07:02:49Z 2017-04-15T07:02:49Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70196 en Nanyang Technological University 51 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Li, Yuanrui A data mining application on predicting relevance of search results from E-commerce platforms |
| title | A data mining application on predicting relevance of search results from E-commerce platforms |
| title_full | A data mining application on predicting relevance of search results from E-commerce platforms |
| title_fullStr | A data mining application on predicting relevance of search results from E-commerce platforms |
| title_full_unstemmed | A data mining application on predicting relevance of search results from E-commerce platforms |
| title_short | A data mining application on predicting relevance of search results from E-commerce platforms |
| title_sort | data mining application on predicting relevance of search results from e commerce platforms |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | http://hdl.handle.net/10356/70196 |
| work_keys_str_mv | AT liyuanrui adataminingapplicationonpredictingrelevanceofsearchresultsfromecommerceplatforms AT liyuanrui dataminingapplicationonpredictingrelevanceofsearchresultsfromecommerceplatforms |