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Human Language Technology and Knowledge Management

AI Magazine

This article summarizes the results of the 6-7 July Workshop on Human Language Technology and Knowledge Management held in Toulouse, France. It describes invited keynotes, presentations, and results of brainstorming sessions to create a technology road map for this important area. The group also articulated grand challenges in human language technology and solutions to these challenges that could benefit facilities for knowledge discovery, access, and exploitation.


Council Post: Three Ways AI Can Assist ESG Investment Decisions

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Dr. Steven Gustafson is Noonum's CTO and an AI scientist, passionate about solving hard problems while having fun and building great teams. It is becoming increasingly important to understand how companies contribute to society, from preventing negative behaviors to identifying positive impacts that others can learn from. A recent book by Rebecca M. Henderson, Reimagining Capitalism in a World on Fire, makes the case for initiatives that encourage the reporting and standardization of metrics such as environmental, social and governance (ESG) reporting and the United Nations Sustainable Development Goals. Until agreed-upon frameworks like the Sustainability Accounting Standards Board become standard and comprehensive, most organizations will report their policies in text reports, and most analysts and watchdogs will also report their analyses and research in text reports. Therefore, companies like JUST Capital are crucial in spending many research hours reading reports, contacting companies and managing a complex rubric of analysis to create rankings and metrics.


Configuration

AI Magazine

The American Association for Artificial Intelligence (AAAI) held its 1996 Fall Symposia Series on 9 to 11 November in Cambridge, Massachusetts. This article contains summaries of the seven symposia that were conducted: (1) Configuration; (2) Developing Assistive Technology for People with Disabilities; (3) Embodied Cognition and Action; (4) Flexible Computation: Results, Issues, and Opportunities; (5) Knowledge Representation Systems Based on Natural Language; (6) Learning Complex Behaviors in Adaptive Intelligent Systems; and (7) Plan Execution: Problems and Issues. This article contains summaries of the seven symposia that were conducted: (1) Configuration; (2) Developing Assistive Technology for People with Disabilities; (3) Embodied Cognition and Action; (4) Flexible Computation: Results, Issues, and Opportunities; (5) Knowledge Representation Systems Based on Natural Language; (6) Learning Complex Behaviors in Adaptive Intelligent Systems; and (7) Plan Execution: Problems and ...


Watson & Cybersecurity: Bringing AI to the Battle

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"To function effectively in this knowledge economy, you need to read through trillions of data points. You basically need to go back to school every day to answer the questions that hit your desk. That is the challenge of the knowledge economy. And that is where I believe we can do something different in security with AI and cognitive." At IBM InterConnect 2017, Marc van Zadelhoff, general manager of IBM Security, delivered a thought-provoking keynote titled "Watson & Cybersecurity: Bringing AI to the Battle."


Challenges Of Implementing Natural Language Processing

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The process includes several activities such as pre-processing, tokenisation, normalisation, correction of typographical errors, Named Entity Reorganization (NER), and dependency parsing. To attain high-quality models, NLP performs an in-depth analysis of user inputs like lexical analysis, syntactic analysis, semantic analysis, discourse integration, and pragmatic analysis, etc. The main challenge is information overload, which poses a big problem to access a specific, important piece of information from vast datasets. Semantic and context understanding is essential as well as challenging for summarisation systems due to quality and usability issues. Also, identifying the context of interaction among entities and objects is a crucial task, especially with high dimensional, heterogeneous, complex and poor-quality data.