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The needs and benefits of Text Mining applications on Post-Project Reviews
Post Project Reviews (PPRs) are a rich source of knowledge and data for organisations - if organisations have the time and resources to analyse them. Too often these reports are stored, unread by many who could benefit from them. PPR reports attempt to document the project experience – both good and...
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| Main Authors: | , , , |
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| Format: | Default Article |
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2009
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| Online Access: | https://hdl.handle.net/2134/5521 |
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| _version_ | 1818175471538405376 |
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| author | Alok Choudhary Paul Oluikpe Jennifer Harding Patricia Carrillo |
| author_facet | Alok Choudhary Paul Oluikpe Jennifer Harding Patricia Carrillo |
| author_sort | Alok Choudhary (1251471) |
| collection | Figshare |
| description | Post Project Reviews (PPRs) are a rich source of knowledge and data for organisations - if organisations have the time and resources to analyse them. Too often these reports are stored, unread by many who could benefit from them. PPR reports attempt to document the project experience – both good and bad. If these reports were analysed collectively, they may expose important detail, e.g. recurring problems or examples of good practice, perhaps repeated across a number of projects. However, because most companies do not have the resources to thoroughly examine PPR reports, either individually or collectively, important insights and opportunities to learn from previous projects, are missed. This research explores the application of knowledge discovery techniques and text mining to uncover patterns, associations, and trends from PPR reports. The results might then be used to address problem areas, enhance processes, and improve customer relationships. A case study related to two construction companies is presented in this paper and knowledge discovery techniques are used to analyze 50 PPR reports collected during the last three years. The case study has been examined in six contexts and the results show that Text Mining has a good potential to improve overall knowledge reuse and exploitation. |
| format | Default Article |
| id | rr-article-9451508 |
| institution | Loughborough University |
| publishDate | 2009 |
| record_format | Figshare |
| spelling | rr-article-94515082009-01-01T00:00:00Z The needs and benefits of Text Mining applications on Post-Project Reviews Alok Choudhary (1251471) Paul Oluikpe (7175675) Jennifer Harding (1258389) Patricia Carrillo (1248684) Mechanical engineering not elsewhere classified Distributed computing and systems software not elsewhere classified Software engineering not elsewhere classified Text mining Knowledge discovery Post Project Reviews (PPRs) Manufacturing and construction Mechanical Engineering not elsewhere classified Computer Software Distributed Computing Post Project Reviews (PPRs) are a rich source of knowledge and data for organisations - if organisations have the time and resources to analyse them. Too often these reports are stored, unread by many who could benefit from them. PPR reports attempt to document the project experience – both good and bad. If these reports were analysed collectively, they may expose important detail, e.g. recurring problems or examples of good practice, perhaps repeated across a number of projects. However, because most companies do not have the resources to thoroughly examine PPR reports, either individually or collectively, important insights and opportunities to learn from previous projects, are missed. This research explores the application of knowledge discovery techniques and text mining to uncover patterns, associations, and trends from PPR reports. The results might then be used to address problem areas, enhance processes, and improve customer relationships. A case study related to two construction companies is presented in this paper and knowledge discovery techniques are used to analyze 50 PPR reports collected during the last three years. The case study has been examined in six contexts and the results show that Text Mining has a good potential to improve overall knowledge reuse and exploitation. 2009-01-01T00:00:00Z Text Journal contribution 2134/5521 https://figshare.com/articles/journal_contribution/The_needs_and_benefits_of_Text_Mining_applications_on_Post-Project_Reviews/9451508 CC BY-NC-ND 4.0 |
| spellingShingle | Mechanical engineering not elsewhere classified Distributed computing and systems software not elsewhere classified Software engineering not elsewhere classified Text mining Knowledge discovery Post Project Reviews (PPRs) Manufacturing and construction Mechanical Engineering not elsewhere classified Computer Software Distributed Computing Alok Choudhary Paul Oluikpe Jennifer Harding Patricia Carrillo The needs and benefits of Text Mining applications on Post-Project Reviews |
| title | The needs and benefits of Text Mining applications on Post-Project Reviews |
| title_full | The needs and benefits of Text Mining applications on Post-Project Reviews |
| title_fullStr | The needs and benefits of Text Mining applications on Post-Project Reviews |
| title_full_unstemmed | The needs and benefits of Text Mining applications on Post-Project Reviews |
| title_short | The needs and benefits of Text Mining applications on Post-Project Reviews |
| title_sort | needs and benefits of text mining applications on post-project reviews |
| topic | Mechanical engineering not elsewhere classified Distributed computing and systems software not elsewhere classified Software engineering not elsewhere classified Text mining Knowledge discovery Post Project Reviews (PPRs) Manufacturing and construction Mechanical Engineering not elsewhere classified Computer Software Distributed Computing |
| url | https://hdl.handle.net/2134/5521 |