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Data extraction is the act or process of retrieving data out of data sources for further data processing or data storage. The import into the intermediate extracting system is thus usually followed by data transformation and possibly the addition of metadata prior to export to another stage in the data workflow. Usually, the term data extraction is applied when (experimental) data is first imported into a computer from primary sources, like measuring or recording devices. Today's electronic devices will usually present an electrical connector (e.g. USB) through which 'raw data' can be streamed into a personal computer. Typical unstructured data sources include web pages, emails, documents, PDFs, scanned text, mainframe reports, spool files etc. Extracting data from these unstructured sources has grown into a considerable technical challenge where as historically data extraction has had to deal with changes in physical hardware formats, the majority of current data extraction deals with extracting data from these unstructured data sources, and from different software formats. This growing process of data extraction from the web is referred to as Web scraping. The act of adding structure to unstructured data takes a number of forms
• Using text pattern matching such as regular expressions to identify small or large-scale structure e.g. records in a report and their associated data from headers and footers; • Using a table-based approach to identify common sections within a limited domain e.g. in emailed resumes, identifying skills, previous work experience, qualifications etc. using a standard set of commonly used headings (these would differ from language to language), e.g. Education might be found under Education/Qualification/Courses; • Using text analytics to attempt to understand the text and link it to other information OMICS Group International provides an opportunistic environment and vibrant podium through these auspicious events to amplify these steps and meet the highest demand ever, by reflexive and cerebrative connections. Established in the year 2007, OMICS Group International has been progressively organizing scientific conferences across the globe, rendezvous which consist of various streams of scientific study to improve and accelerate discovery for a better tomorrow. The non-profit firm boasts about organizing an average of 300 international conferences per year which is supported by 400 open access journals and 30,000 Editorial Board Members. The number of reader views of the website has clocked 3.5 million and still counting. Lately around more than 1000 scientific associations of various fields from all over the world have shown interest in association with OMICS Group International to promote their research work. International conferences on Data extraction and related fields: 1. The Fourth International Conference on Advances in Information Mining and Management 2. The Sixth International Conference on Advances in Databases, Knowledge, and Data Applications, April 20 - 24, 2014 - Chamonix, France 3. KDIR-2014, Rome, Italy 4. LD4IE 2014 : FP: LD4IE2014 Linked Data for Information Extraction - ISWC2014 5. Society for Industrial and Applied Mathematics-2015 6. 16th International Conference on Data Warehousing and Knowledge Discovery - DaWaK 2014 7. PAKDD-2014, Taiwan 8. 11th ESWC2014 9. ICMETM 2014 - International Conference on Modern Economic Technology and Management 10. SDM 2015: The Fifteenth Siam International Conference On Data Mining 11. EGC 2015: 15th Conference on Knowledge Extraction and Management, Jan 27, 2015 - Jan 30, 2015 12. SIGMOD 2015: International Conference on Management of Data, May 31, 2015 - Jun 4, 2015, Melbourne, VIC, Australia International societies and companies related to Data extraction and related fields: 1. International Society for Computational Biology 2. Society of Petroleum Engineers 3. Association for Computational Machinery 4. International Educational Data Mining Society 5. IAENG Society of Data Mining 6. INFORMS, USA 7. AMAZON 8. Society of Data Miners 9. Evolutionary Agent Societies(EAS) Companies: 1. IBM 2. Microsoft 3. Angoss 4. Amazon 5. Viscovery 6. Think Analytics 7. Stat Soft 8. QI Ware 9. Oracle 10. SAS Data Mining
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