Session 5Y, 2.30 PM-4.00 PM: " A Pattern Recognition Approach to Automated XBRL Extraction" (www.ieee-cifer.org)
Cross-Disciplined Research
BCL has been a leader in performing research that combines the fields of Natural Language Processing (NLP) and Document Analysis and Recognition (DAR).
NLP and DAR have a history of close cooperation in developing products that span this divide. Exciting developmental research has been conducted toward natural-language-based search engines for web-based repositories, document summarization, email summarization, document classification, and web page classification.
Natural Language Processing
BCL Technologies offers various ways to communicate with desktop computers and handheld devices using linguistic interfaces for multiple languages, including English, Arabic, Urdu-Hindi, and Korean. The majority of traditional natural-language-based systems cannot handle slight deviations from pre-defined sets of constructs, and therefore do not allow humans to communicate with machines intuitively. BCL's Natural Language (NL) capabilities offer freedom for users to communicate with voice-enabled handheld devices and desktop computers using natural languages with any number of variations in which a specific command or query may be stated. The applications BCL has developed and is currently developing entail semantic annotation, word sense disambiguation, lexical summarization, text simplification, categorization, word sense disambiguation, and speech-based language learning tools.
BCL holds several patents pending in this area. Its research is published widely in refereed journals and peer-reviewed conferences. BCL has been granted a number of multilingual federally funded projects in Natural Language Processing and text processing in the last ten years.
Document Analysis and Recognition
BCL carries out research in all areas of document recognition and analysis. BCL's widely published research on document layout analysis has been incorporated in its award winning document conversion products. BCL is the world leader in providing PDF conversion tools. This product suite includes tools for converting PDF files to Word, PDF files to HTML, PDF files to RTF, and PDF files to ASCII text. Research in DAR has resulted in two product suites. One comes in the form of Adobe Acrobat plugins, meaning the users need to have a copy of full Adobe Acrobat running in their machines. The other is independent of Adobe Acrobat, but offers similar features.
BCL has been granted federally funded projects in the area of document analysis and recognition in the last ten years. It also has several patents in this area, either granted or pending.
Air Force Research Laboratories (AFRL-RH-BR-TR-2009) Phase II Final Report.Friday, May 8, 2009. BCL Technologies successfully completed AFRL Phase II deliverables toward title - Linguist Ambiguity, Training, and Rehearsal System.
In its Phase II SBIR efforts BCL Technologies developed a ...
Posted Jan 9, 2012, 10:39 AM by BCL Technologies
Authorship Analysis for Cognitive Information Operations (2012)
The Small Business Innovation Research (SBIR) program is a United States Government program, coordinated by the Small Business Administration and the Department of Defense (DoD). This US Navy funded award focuses on developing methods to determine document author signatures from features derived from text using Natural Language Processing methods.
Best XBRL tool Award at XBRL
Japan's 2nd Academic Competition (March 2012)
BCL Technologies' XBRL tool, SmartXBRL, was selected as the winner at the 2nd Academic Competition (2012) organized by XBRL Japan Educational Working Group, XBRL Japan. The competition celebrates the invaluable contribution of researchers, students, software developers, and anyone who is interested in XBRL development, by providing implementations of software tools for XBRL documents, definitions of taxonomies, and other useful and effective applications of XBRL. http://www.xbrl.or.jp/
Best Paper Award!
International Conference on Computing, Communication and Control Technologies
Best Paper Award!