Basic Java Amazon ISBN to BibTeX Application

I require a java GUI application that allows me to enter a list of ISBN (one ISBN number per line); query the Amazon API; and then have the associated BibTeX references printed out in a text box (so they can be copied and pasted elsewhere). The GUI Application should consist of the following: • Window Title: “Amazon ISBN to BibTeX” • TextBox labled “ISBN:” • Button labeled: “Process” (centered) • TextBox labled “BiBTeX:” • Button labeled: “Copy to Clipbpard” (centered) Note: Both of the Text Boxes should have a vertical scroll bar. (The BibTeX textbox should have a horizontal scrollable as well). An example of this kind of application (webpage) can be found at: [login to view URL] The BibTeX output should be formatted similar to the following (note: a) The BibTex must include the Abstract; b) send me the available fields from Amazon): @BOOK{HastieTibshiraniFriedman201112, title={The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)}, author={Trevor Hastie, Robert Tibshirani, Jerome Friedman}, publisher={Springer}, year={2011}, month={12}, edition={2nd ed. 2009. Corr. 7th printing 2013}, isbn={9780387848570}, url={[login to view URL]}, price={$89.95}, totalpages={745}, timestamp={2014.07.10}, abstract={During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates. }, } Some sample ISBN numbers: 13:9780387848570 13:9781461461135 0387479414 13:9780387881454 13:9780275964283 Some additional notes: • The BibTeX must include the abstract. • The ISBN number may contain dashes or spaces (the application must account for this). • The Amazon API should use the [login to view URL] website • The application should handle both ASIN (0387848576) and ISBN (13:9780387848570) numbers • You will need to watch out for wrong characters being included in the BibTex – i.e. if the Amazon abstract includes } that might ruin the format. • It would be good to have the Authors/Editors separated by a comma instead of the word “and”. The deliverable(s) for this project are: • Source code (documented) • Jar file