By B. C. Craft
This can be one of many conventional textbooks of reservoir engineering that has survived the cross of time as a result of its undoubtful caliber. The e-book has a lot of solved and proposed routines and the themes are provided in a fashion really easy to appreciate. It was once initially written on the time during which fabric stability calculations have been the elemental algoritm utilized by reservoir engineers to signify hidrocarbon reservoirs. As such, this booklet is equipped by way of the fabric stability equation: it is going from fabric stability utilized to dry fuel, the subsequent bankruptcy is set fabric stability utilized to gas-condensate, then undersaturated etc, till all diferent fluids are lined. quite a few techniques to do the fabric stability calculations are provided, lots of them of very little usefulness this present day and positively no longer even pointed out in smooth reservoir engineering classes. very important themes resembling PVT are dispersed in all of the chapters. different akin to strain checking out and inmiscible displacement are lined with no enough intensity. Numerical simulation isn't really even an access within the topic index. In precis, in the event that your curiosity is to examine fabric stability equipment in reservoir engineering, this can be the e-book to select. while you're looking a basic view of the topic then there are greater suggestions.
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In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1195–1204. ACM (2009) 5. : Comparison of Model-Based Learning Methods for Feature-Level Opinion Mining. In: Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, WI-IAT 2011, vol. 01, pp. 265–273 (2011) 6. : Advances in Machine Learning Based Text Categorization. Journal of Software, 1848–1859 (2006) (in Chinese) 7. : Multi-facet Rating of Product Reviews.
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts. In: Proc. ACL (2004) 19. : Opinion mining and sentiment analysis. Found. Trends Inf. Retr. 2(1-2), 1–135 (2008) 20. : An algorithm for suffix stripping. Program: Electronic Library and Information Systems 14(3) (1980) 21. : Reputation Systems: Facilitating Trust in Internet Interactions. Communications of the ACM 43, 45–48 (2000) 22. : Sentiment strength detection in short informal text. Journal of the American Society for information Science 61(12), 2544–2558 (2010) 23.
Log2 N + dfi− dfi+ N − N+ dfi+ − tfi,j . log2 N− dfi− (2) Generating Domain-Specific Sentiment Lexicons for Opinion Mining 19 where: (i) N + is the number of positive texts in the input document collection D (labelled “aye” with respect to our political opinion mining application), (ii) N − is the number of negative texts (labelled “nay”), (iii) tfij is the term frequency for term ti in text j, (iv) dfi+ is the document frequency for term ti with respect to positive texts in the input document collect D and (v) dfi− is the document frequency for term ti with respect to negative texts.