Towards a Technology Platform for Building Corporate Radar Applications that Mine the Web for Business Insight

In this paper, we give a progress report on an ongoing effort at Accenture to develop a technology platform for building a wide range of corporate radar applications,which can turn the Web into a systematic source of business insight. Our goal is to share the platform we have developed and the lessons we have learned, so others can leverage this knowledge when building similar applications. We give an overview of this platform, which integrates a combination of established AI technologies -- i.e. semantic models, natural language processing, and inference engines -- in a novel way. We then illustrate the kinds of corporate radars that can be built with our platform through two applications we developed at Accenture: the Technology Lifecycle Tracker, which assesses the maturity of technologies from the wireless industry, and the Technology Trend Tracker, which measures hype versus reality for emerging technology trends such as cloud computing, software-as-a-service, and more. Finally, we discuss our experiences in using this platform to build these applications and the lessons learned.

[1]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[2]  John F. Sowa,et al.  Conceptual Structures: Information Processing in Mind and Machine , 1983 .

[3]  Stan Szpakowicz,et al.  Semiautomatic recognition of semantic relationships in english technical texts , 1998 .

[4]  Peter Z. Yeh,et al.  Matching utterances to rich knowledge structures to acquire a model of the speaker's goal , 2005, K-CAP '05.

[5]  Yarden Katz,et al.  Pellet: A practical OWL-DL reasoner , 2007, J. Web Semant..

[6]  Peter Z. Yeh,et al.  Capturing the Semantics of Online News Sources for Business Intelligence Applications , 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.

[7]  Rada Mihalcea,et al.  An Iterative Approach to Word Sense Disambiguation , 2000, FLAIRS.

[8]  Philipp Cimiano,et al.  Ontology Learning from Text: Methods, Evaluation and Applications , 2005 .

[9]  Peter Clark,et al.  A library of generic concepts for composing knowledge bases , 2001, K-CAP '01.

[10]  Ramanathan V. Guha,et al.  Building large knowledge-based systems , 1989 .

[11]  Brian McBride,et al.  Jena: Implementing the RDF Model and Syntax Specification , 2001, SemWeb.

[12]  Peter Z. Yeh,et al.  Using transformations to improve semantic matching , 2003, K-CAP '03.

[13]  Gary W. King,et al.  A Knowledge Acquisition Tool for Course of Action Analysis , 2003, IAAI.

[14]  Elizabeth C. Wilson,et al.  The Knowledge Machine , 1968, Teachers College Record.

[15]  Dan Brickley,et al.  Resource Description Framework (RDF) Model and Syntax Specification , 2002 .

[16]  Peter Z. Yeh,et al.  Technology Investment Radar: A Tool to Automatically Track Technology Maturation , 2008, 2008 IEEE International Conference on Semantic Computing.

[17]  Peter Z. Yeh,et al.  A Tool for Measuring the Reality of Technology Trends of Interest , 2009, IAAI.

[18]  Peter Z. Yeh,et al.  A Unified Knowledge Based Approach for Sense Disambiguation and Semantic Role Labeling , 2006, AAAI.