edu Institute AIFB Karlsruhe Institute of Technology KIT detlefseesekitedu Institute IISM Karlsruhe Institute of Technology KIT weinhardtkitedu Abstract Financepractitionersandresearchersrelyheavilyonaccurateandacces sible historical data Practitione ID: 1507 Download Pdf
Middleware. The IGUANA Integration Engine. Introduction. Eliot . Muir, CEO. My . role is . 75% . development. Based in Toronto, Canada. The IGUANA Integration Engine. About . iNTERFACEWARE. Iguana – integration in healthcare. .
Adding even more demand to rapidly integrate new data sources and applications are growing trends such as cloud and big data enabling the business to create differentiating services access new data for advanced analytics or change internal processes
Integrating Procurement Systems & Creating the P-RAMS Dashboard. Marcelo Donolo. Procurement Specialist, OPCPR. Fiduciary Forum, March 2010. Why integrate?. All procurement applications that needed to be developed are now (or soon will be) online.
Background and Rationale. The process of integration within the region is increasingly deepening;. financial integration. movement of people (tourism or mode IV). increased trade.. The intervention of the CBTT and Gov’t of Trinidad and Tobago into the operations of CL Financial revealed the inadequacy of data on regional linkages.
Computation of transversal B-field on primary beam. CLIC main parameters. 9/25/2009. Detlef Swoboda. 2. Center of mass energy. 3 TeV. Peak Luminosity. 2. . 10. 34. cm. -2. s. -1. Repetition rate.
Presenters:. Rishi Grover. President, Vena Solutions. 10 Easy tips to make your account reconciliations more efficient. Yanky Li. Financial Close Solutions Lead, Vena Solutions. Rishi . grover. As President, Rishi is responsible for the day-to-day operations and continued success of client implementations at Vena..
Integrating P-RAMS and other Procurement Applications in Operations Portal & Client Connection. Marcelo Donolo. Procurement Specialist, OPCPR. Fiduciary Forum, March 2010. Objectives. Procurement applications in Ops Portal.
Xin. Luna Dong (Google Inc.). Divesh. . Srivastava. (AT&T Labs-Research). http://www.research.att.com/~divesh/papers/bdi-icde2013.pptx. What is “Big Data Integration?”. Big data integration = Big data data integration.
May 2018. BUILDER Overview. 2. BUILDER SMS. 3. A part of a web-based software application Sustainment Management System (SMS). Developed by Construction Engineering Research Laboratory (CERL), Engineer Research and Development Center, US Army Corps of Engineers.
Stijn Claessens . based on:. Geneva Report on the World Economy 12. . Stijn Claessens (IMF), Richard J. Herring (Wharton School. ),. . Dirk Schoenmaker (Duisenberg school of finance). Conference: “.
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edu Institute AIFB Karlsruhe Institute of Technology KIT detlefseesekitedu Institute IISM Karlsruhe Institute of Technology KIT weinhardtkitedu Abstract Financepractitionersandresearchersrelyheavilyonaccurateandacces sible historical data Practitione
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www.kit.edu07.10 GfKl Symposium, Karlsruhe, July 22nd, 2010Applied Informatics and Formal Description Methods (AIFB)Information Management and Market Engineering(IME)Karlsruhe Institute of Technology (KIT), GermanyCaslav Bozic (bozic@kit.edu), Detlef Seese, Christof Weinhardt (i)Motivation(ii)Data Integration(iii)Data Processing(iv)Examples(v)Summary(vi)ReferencesBozic, Seese, Weinhardt -Data integration: Financial Domain-Driven Approach FINDS Text Classification Systems Tokenizer Stemmer Classification Reuters TakesNews Stories Full Text of News Stories 3 classifiers Bayes Fisher SVM Neural NetworkBozic, Seese, Weinhardt -Data integration: Financial Domain-Driven Approach (i)Motivation(ii)Data Integration(iii)Data Processing(iv)Examples(v)Summary(vi)ReferencesBozic, Seese, Weinhardt -Data integration: Financial Domain-Driven Approach Data Integration Data integration includes the task of combiningdata residing at different sources and providing the user with the unified view of this data (Lenzerini 2002) data integration system : triple (G, S, M) G: global schema : source schema M: mapping : final benchmarking dataset S = S: source databases : Thomson Reuters TickHistory : S&P Compustat : target mappings (global-as-view)Bozic, Seese, Weinhardt -Data integration: Financial Domain-Driven Approach (i)Motivation(ii)Data Integration(iii)Data Processing(iv)Examples(v)Summary(vi)ReferencesBozic, Seese, Weinhardt -Data integration: Financial Domain-Driven Approach (i)Motivation(ii)Data Integration(iii)Data Processing(iv)Examples(v)Summary(vi)ReferencesBozic, Seese, Weinhardt -Data integration: Financial Domain-Driven Approach Sentiment Data 6 Mio records about 10,000 different companies 2.5 times increase in yearly volume in period 2003 2008 2 biggest US markets (NYSE & NASDAQ) 40% in 2003 60% in 200813 2000004000006000008000001000000120000014000001600000200320042005200620072008 rest Number of records per yearBozic, Seese, Weinhardt -Data integration: Financial Domain-Driven Approach Summary FINDS Project Variety of financial text mining approaches creates the need for benchmarking method Proposed framework and implemented system for Flexible integration of new data sources Formal definition of calculated fields and aggregationsBozic, Seese, Weinhardt -Data integration: Financial Domain-Driven Approach Applied Informatics and Formal Description Methods (AIFB)Information Management and Market Engineering(IME)Karlsruhe Institute of Technology (KIT), GermanyCaslav Bozic (bozic@kit.edu), Detlef Seese, Christof WeinhardtGfKl Symposium, Karlsruhe, July 22nd, 2010 References [10] Das, S. & Chen, M., Yahoo! for Amazon: Sentiment extraction from small talk on the web, Management Science, INFORMS, 2007, Vol. 53(9), pp. 1375-1388 [11] Tetlock, P., Giving Content to Investor Sentiment: The Role of Media in the Stock Market, THE JOURNAL OF FINANCE, 2007, Vol. 62(3) [12] Tetlock, P., Saar-Tsechansky, M. & Macskassy, S., More Than Words: Quantifying Language to Measure Firms' Fundamentals, Journal of Finance, American Finance Association, 2008, Vol. 63(3), pp. 1437-1467 [13] Pfrommer, J., Hubschneider, C. & Wenzel, S., Sentiment Analysis on Stock News using Historical Data and Machine Learning Algorithms, Term Paper, 2010 [14] Mittermayer, M. & Knolmayer, G., Text mining systems for market response to news: A survey [15] Wthrich, B., Permunetilleke, D., Leung, S., Cho, V., Zhang, J. & Lam, W., Daily prediction of major stock indices from textual www data, 1998 [16] LENZERINI, M., Data integration: a theoretical perspective,Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems.,ACM, New York, 233246. 2002Bozic, Seese, Weinhardt -Data integration: Financial Domain-Driven Approach
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