Pingar Researchers to Speak at Text Analytics World Boston

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Predictive Analytics Event focuses on business value gained from text analytics.

Pingar unstructured data management solutions

The selection of two members of Pingar Research team to speak separately about gaining business intelligence from data is a significant validation of the quality of the team.

Pingar, a leading provider of unstructured data management solutions, today announced two Pingar researchers are presenting separately at Text Analytics World Boston #TAWCon 3-4 October, 2012. Chief research officer Alyona Medelyan and senior software researcher Anna Divoli were selected to present among a competitive field of leaders in text analytics.

Pingar CEO Peter Wren-Hilton says text analytics, the core of the Pingar API, is an emerging technology that provides new opportunities for enterprises to analyse and extract valuable insight from unstructured data. The ability to automatically assign metadata values to documents as well as populate back-end databases with extracted entities for front-end analytics are just two examples of how Pingar’s API technology can be deployed to create structure from unstructured data.

“Text Analytics World is one of the premier conferences focused on text analytics. The selection of two members of Pingar Research team to speak separately about gaining business intelligence from data is a significant validation of the quality of the team,” Mr. Wren-Hilton continues.

Dr. Alyona Medelyan will present “Text Analytics on Two Million Documents: A Case Study” on Wednesday, October 3, 2012 from 3:15-4 p.m. in Track 1: Big Data and Text Analytics.
Presentation description:

“To make sense of big data, we must know what each document is about and what terms and entities they contain. Natural Language Processing (NLP) techniques are processing-intensive, so correct set-up is key when working with big unstructured data.

We will describe an experiment in which nearly two million publications from CiteSeer were loaded onto an Amazon Elastic Compute Cloud and each publication was processed using a keyword extraction API. We cover lessons learned in setting up a cloud environment for such a large dataset, provide an overview of keyword extraction techniques and explain which ones can scale to handle the Big Data.”

Dr. Anna Divoli will present “How taxonomies and facets bring end-users closer to big data” on Thursday, October 4, 4:15-5 p.m. in Track 2: Text Analytics and Taxonomy.
Presentation description:

“Taxonomies are effective when they are tailored for the particular data-set, are up to date, and make sense to users. As data grows big and evolves fast we need to explore new sustainable ways for generating and maintaining taxonomies, and we need to understand how to do this well. In this talk I will give an overview of traditional, manual, expert-defined taxonomies, user generated taxonomies (or folksonomies), and automatically generated taxonomies. I will then present applications of taxonomies that work and do not work based on a number of user studies.”

About Pingar Research
Pingar is committed to the development of innovative text management solutions and undertakes advanced research both in-house and in collaboration with leading academic institutions. Recently Pingar and the University of Waikato in New Zealand, a recognised centre of excellence in Natural Language Processing, Machine Learning and Data Mining have undertaken research to automate the extraction of taxonomies from unstructured enterprise data.

In addition to the partnerships with PolyU and the University of Waikato, Pingar has important research relationships with institutions including the University of Swansea in Wales and Shanghai’s East China Normal University.
The Pingar Research team consists of in-house researchers and world-renowned collaborators.

Pingar’s background and research areas cover a wide range of expertise necessary for the intelligent handling of unstructured text data. The company has ongoing projects in Natural Language Processing, Machine Learning, Information Retrieval, Semantic Web, and User Interfaces across a number of languages and verticals.

About Pingar
Pingar’s mission is to transform unstructured data in the enterprise into business intelligence by developing technology that harnesses the power of text mining, natural language processing and machine learning. This mission came from years of ground-breaking research at some of the most respected universities in these fields and increases the power and usefulness of your enterprise information. Pingar’s process is intuitive, its API works seamlessly with existing enterprise content management systems and yields more contextually relevant results and tools to extract information and transform that information into intelligence.

Pingar is headquartered in New Zealand with offices in the United States, the United Kingdom, India and Hong Kong. For more information, please see Follow Pingar on Twitter (at) PingarHQ.

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