Editing Final Report/Thesis 2015 (section)

===Budget===
The project budget for this honours group was set at 500 dollars at the commencement of the project.  It was initially proposed for the budget to depend on the n-gram database chosen to be used for the search engine in Task 2.  As discussed in the Method section of Task 2: N-Gram Search, a variety of options were considered and the main two largest databases were found to be Microsoft Web N-Gram Services<ref>C. X. Zhai et al. (2010, July 19-23). Web N-gram Workshop [online]. Available: http://research.microsoft.com/en-us/events/webngram/sigir2010web_ngram_workshop_proceedings.pdf</ref>, and Google N-Gram <ref>Google Books. (2012 July). Ngram Viewer [Online]. Available: http://storage.googleapis.com/books/ngrams/books/datasetsv2.html</ref>.  

The Microsoft alternative was found to be free to use for academic purposes after applying for a user token, and is stored for free on Microsoft’s web server, hence there was no need to purchase storage upon which to store the database<ref>C. X. Zhai et al. (2010, July 19-23). Web N-gram Workshop [online]. Available: http://research.microsoft.com/en-us/events/webngram/sigir2010web_ngram_workshop_proceedings.pdf</ref>.

The Google alternative was available for free when obtaining the raw dataset, or at a cost of 150 dollars for a student license when purchased from the University of Pennsylvania Linguistic Data Consortium <ref>T.Brants and A.Franz. (2006). Web 1T 5-gram Version 1 [online]. Available: https://catalog.ldc.upenn.edu/LDC2006T13</ref>.  Unlike the Microsoft alternative, if the Google N-Gram option was chosen, a portion of the budget would have had to be dedicated to storing the database.  It was initially proposed to store the database on a hard drive at a cost of approximately 100 dollars. 

The proposed budget can be seen in the tables highlighting the key costs of each option in Figure 45.    
[[File:Proposed_Budget.png|thumb|500px|centre|'''Fig. 45:''' Proposed Budgeting Table]]

For reasons discussed in the Method section of Task 2: N-Gram Search, upon deciding to use the Google N-Gram database, a decision was to be made whether to purchase the University of Pennsylvania's Linguistic Data Consortium version or to obtain it for free directly from Google.  A decision was made to utilise the free database provided by Google as it was not deemed justifiable to spend $150 on the processed data from the Linguistic Data Consortium since it was proposed that the raw dataset could be cleaned up through writing software.

The initial budget was based on the assumption that the Google N-Gram database could be stored locally, although this was feasibly possible in its compressed form, the local computing power available would have been insufficient to run the search engine code through the database within a the time frame of the project.  As discussed in the Method section of Task 2: N-Gram Search, a cloud based computing service called ‘Amazon Elastic Compute Cloud’ was utilised to store and process the database.  The free tier was considered but did not provide the specifications required to meet the needs of our task, and so instances on Amazon EC2 were hired at a rate of 0.853 dollars per hour <ref>Amazon Web Services. (2015). Amazon EC2 Pricing [Online]. Available: https://aws.amazon.com/ec2/pricing/</ref>.  Upon storing the initial full database, running our search code, and downloading our results generated from the outputs of the code, the total cost of utilising the service came to 576 dollars.   This caused our project to exceed the initially proposed budget.  The reason for the additional project expenditure was that despite our efforts, it was difficult to predict the precise time that it would take to upload, store and process the database on the cloud service.  The initially proposed budget did not include the need or costing for the Amazon server since this was not something that could be reasonably foreseen at the start of the project since it was initially thought that the Microsoft N-Gram Service would be suitable for the needs of the project, and if this was not suitable, that the Google N-gram alternative would be able to be stored locally.  

The final revised budget including total project expenditure can be seen in Figure 46. 
[[File:Final_Budget.png|thumb|500px|centre|'''Fig. 46:''' Final Budgeting Table]]

In conclusion, despite going over budget, the additional funds were kindly provided by the school of Electrical and Electronic engineering upon sending an application for funding including justification of our purchases.  The project work has benefited through the purchase of the Amazon service since we were able to complete a search of specific n-gram combinations of the code on the full Google N-Gram database.  It has provided us with results to present as part of our thesis and allowed us to meet the requirements set out in the aim of Task 2.