We provide a hands-on workshop demonstrating the discovery of valuable customer insights through text mining on repair notes. The workshop presents a real world analysis project based on anonymized data from a large manufacturing company. We illustrate the methodology, typical analysis steps, challenges, and potential pitfalls of a repair notes analysis project.
Megaputer Intelligence is exhibiting at the 6th annual NACCM conference
June 10th, 2008. Sergei Ananyan of Megaputer Intelligence presents at the 4th Annual National Workers’ Compensation Subrogation Strategies Executive Summit. Synopsis Insurance companies have to timely process overwhelming volumes of claims, frequently quite complex and lengthy. In this challenging environment, they can easily miss valid subrogation opportunities and thus not recover the money they are entitled to. Subrogations help recover substantial funds, but only a small percentage of cases represent valid subrogation opportunities. Currently, insurance companies task either individual adjusters or special recovery teams with determining the subrogation potential of handled claims. However, there is a general agreement in the industry that manual analysis of subrogation potential is rather inaccurate and time consuming, and a better solution is being sought. Intelligent automated systems combining text mining and data modeling techniques proved to be efficient in identifying valid subrogation opportunities. Such systems exploit the joint use of linguistic and semantic text…
May 13th-14th, 2008. Sergei Ananyan of Megaputer Intelligence makes a joint presentation with two Merck researchers on a PolyAnalyst text mining project at the Merck Technology Symposium 2008. Megaputer exhibits at IDEA (Booth EX21, Tuesday-Wednesday):http://merck.planetconnect.com/exhibits.html#75 Paul Kallukaran, Ph.D., Merck Razek Karnoub, Ph.D., Merck Sergei Ananyan, Ph.D., Megaputer Intelligence Abstract In predicting the evolution of product sales volumes, one would benefit from knowing to what extent different clinical studies affect products and market performance. The potential impact of a clinical study can be determined through the analysis of research articles and other information discussing the study. However, direct manual analysis of large volumes of related literature requires major time and effort investments from a highly trained professional. Thorough analysis of all historical literature related to a particular issue might take several months of the analyst’s work. We incorporated advanced text mining techniques to automate the initial screening of literature related to a…
February 12, 2008. The National Center for Patient Safety (NCPS) of the Department of Veterans Affairs (VA) implements text mining technologies to enhance the analysis of patient safety reports. The VA NCPS analysts are utilizing the PolyAnalyst™ data and text mining system from Megaputer Intelligence to detect common patterns, identify emerging trends, and determine root causes of issues in patient safety reports received from the 153 hospitals operated by the VA. The goal of the VA NCPS is the reduction and prevention of inadvertent harm to patients as a result of care. To accomplish this goal, the VA analysts strive to learn from safety reports representing close calls, also known as «near misses,» which occur at a much higher frequency than actual adverse events. This approach focuses efforts on continually identifying potential problems and proactively fixing them to improve patient safety and quality of care. The most informative part of…