However, UBIC has engineered Self-adaptive Data Landscaping to enhance the knowledge base of KIBIT and ultimately its overall intelligence by analyzing human decision making. The implementation of Self-adaptive Data Landscaping not only improves KIBIT's performance, but also its adaptability to the environment in which it is put to use.The innovative technology covered by this patent has been implemented in several of the newly released products in the Lit i View ® series, UBIC's platform for big data analysis. The Lit i View ® products have been designed not only to process vast amounts of e-discovery data automatically, but also to meet a wider range of new industry demands arising in the age of big data. For example, UBIC's innovative technology also provides state-of-the-art fraud investigation features and an automated email auditing system."We believe that this patent is a testament to the superior innovation that underlies the highly accurate document analysis provided by UBIC," stated UBIC Chairman and Chief Executive Officer Masahiro Morimoto. "In this advanced digital age, when the processing of vast volumes of data is necessary, our cutting-edge technology will open up new business frontiers, such as corporate fraud investigation and email auditing. UBIC aims to provide data analysis solutions in a broad range of new fields, including health care, intellectual property evaluation support and national security. By further honing our AI-based technologies and expanding our portfolio of intellectual properties, UBIC will continue to provide additional value-added eDiscovery services to customers worldwide." About UBIC, Inc. UBIC, Inc. (Nasdaq:UBIC) (TSE:2158) supports the analysis of big data based on behavior informatics by utilizing its technology, KIBIT. UBIC's KIBIT technology is driven by UBIC's AI based on knowledge acquired through its litigation support services. The KIBIT incorporates experts' tacit knowledge, including their experiences and intuitions, and utilizes that knowledge for big data analysis. UBIC continues to expand its business operations by applying KIBIT to new fields such as healthcare and marketing.UBIC was founded in 2003 as a provider of e-discovery and international litigation support services. These services include the preservation, investigation and analysis of evidence materials contained in electronic data, and computer forensic investigation. UBIC provides e-discovery and litigation support by making full use of its data analysis platform, "Lit i View®", and its Predictive Coding technology adapted to Asian languages.For more information about UBIC, contact email@example.com or visit http://www.ubic-global.com. Safe Harbor Statement This announcement contains forward-looking statements. These forward-looking statements are made under the "safe harbor" provisions of the U.S. Private Securities Litigation Reform Act of 1995. These statements can be identified by terminology such as "will," "expects," "anticipates," "future," "intends," "plans," "believes," "estimates" and similar statements. Among other things, the amount of data that UBIC expects to manage this year and the potential uses for UBIC's new service in intellectual property-related litigation, contain forward-looking statements. UBIC may also make written or oral forward-looking statements in its reports filed with, or furnished to, the U.S. Securities and Exchange Commission, in its annual reports to shareholders, in press releases and other written materials and in oral statements made by its officers, directors or employees to third parties. Statements that are not historical facts, including statements about UBIC's beliefs and expectations, are forward-looking statements. Forward-looking statements involve inherent risks and uncertainties. A number of factors could cause actual results to differ materially from those contained in any forward-looking statement, including but not limited to the following: UBIC's goals and strategies; UBIC's expansion plans; the expected growth of the data center services market; expectations regarding demand for, and market acceptance of, UBIC's services; UBIC's expectations regarding keeping and strengthening its relationships with customers; UBIC's plans to invest in research and development to enhance its solution and service offerings; and general economic and business conditions in the regions where UBIC provides solutions and services. Further information regarding these and other risks is included in UBIC's reports filed with, or furnished to the Securities and Exchange Commission. UBIC does not undertake any obligation to update any forward-looking statement, except as required under applicable law. All information provided in this press release and in the attachments is as of the date of this press release, and UBIC undertakes no duty to update such information, except as required under applicable law.
TOKYO, Jan. 21, 2016 (GLOBE NEWSWIRE) -- UBIC, Inc. (Nasdaq:UBIC) (TSE:2158) ("UBIC" or "the Company"), a leading provider of international litigation support and big-data analysis services, today announced that it received a formal notice on January 12, 2016, that the Japan Patent Office approved the Company's patent application related to Self-adaptive Data Landscaping. The technology underlying this self-adaptive system enables users to enhance and customize their system performance through the customized relearning capabilities provided by KIBIT, UBIC's AI technology. The necessary procedures for patent registration have already been executed, and the patent is currently pending issuance. Patent application number: 2014-511634Patent application filing date: March 7, 2014 Just as people struggle to estimate how much they need to study in order to pass an exam, it is similarly hard to know how much 'learning' AI systems require before they can operate effectively. In fact, the amount of learning varies considerably depending on a range of complex factors, including the system's goals, the quality of the data used and its expected performance. With KIBIT, UBIC brings something different to the table. KIBIT can achieve high levels of performance with minimal learning, because its performance improves through relearning processes, even when the volume of training data would be considered too low in other situations. In eDiscovery document review, the training data used for machine learning represents only a small portion of a client's data that has been manually reviewed by an attorney. The training data is the input for KIBIT, from which KIBIT acquires the ability and know-how required to automatically categorize the rest of the client's data. If the training data provided to KIBIT is insufficient for KIBIT to build a proper base of knowledge to conduct accurate document review, bias could occur and certain information could be missed by KIBIT during a search.