Jeff Kagan: How IBM Watson and AI is Changing Our Lives

#artificialintelligence

Last week I attended IBM (IBM) World of Watson as both a speaker and an attendee, and today as I sit in my neighborhood Starbucks (SBUX) thinking about everything, all I can say is WOW! This was one of the most interesting, inspiring and amazing events I have ever attended. And we are still in the very early stages of Watson, Cognitive and AI. I invite you to follow me as I learn more and write more about the wonderful world of Watson, all the companies that work with it and how it will change our industries, our businesses and our lives. As a wireless analyst and columnist, I come at this world of Watson from the wireless, telecom, internet and television angle.


How IBM Watson and AI is Changing Our Lives - The MSP Hub

#artificialintelligence

Last week I attended IBM (IBM) World of Watson as both a speaker and an attendee, and today as I sit in my neighborhood Starbucks (SBUX) thinking about everything, all I can say is WOW! This was one of the most interesting, inspiring and amazing events I have ever attended. And we are still in the very early stages of Watson, Cognitive and AI. I invite you to follow me as I learn more and write more about the wonderful world of Watson, all the companies that work with it and how it will change our industries, our businesses and our lives. As a wireless analyst and columnist, I come at this world of Watson from the wireless, telecom, internet and television angle.


Enhancing Event Descriptions through Twitter Mining

AAAI Conferences

We describe a simple IR approach for linking news about events, detected by an event extraction system, to messages from Twitter (tweets). In particular, we explore several methods for creating event-specific queries for Twitter and provide a quantitative and qualitative evaluation of the relevance and usefulness of the information obtained from the tweets. We showed that methods based on utilization of word co-occurrence clustering, domain-specific keywords and named entity recognition improve the performance with respect to a basic approach.


You Too?! Mixed-Initiative LDA Story Matching to Help Teens in Distress

AAAI Conferences

Adolescent cyber-bullying on social networks is a phenomenon that has received widespread attention. Recent work by sociologists has examined this phenomenon under the larger context of teenage drama and it's manifestations on social networks. Tackling cyber-bullying involves two key components – automatic detection of possible cases, and interaction strategies that encourage reflection and emotional support. Key is showing distressed teenagers that they are not alone in their plight. Conventional topic spotting and document classification into labels like "dating" or "sports" are not enough to effectively match stories for this task. In this work, we examine a corpus of 5500 stories from distressed teenagers from a major youth social network. We combine Latent Dirichlet Allocation and human interpretation of its output using principles from sociolinguistics to extract high-level themes in the stories and use them to match new stories to similar ones. A user evaluation of the story matching shows that theme-based retrieval does a better job of finding relevant and effective stories for this application than conventional approaches.


BAFI 2018 : Business Analytics in Finance and Industry

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Conference Topics Topics at this conference include, but are not limited to: Business Analytics - Methods: Dimensionality Reduction, Feature Extraction, and Feature Selection Supervised, Semi-Supervised, and Unsupervised Methods Statistical Learning Theory Online Learning, Data Stream Mining, and Dynamic Data Mining Graph Mining and Semi-Structured Data patial and Temporal Data Mining Deep Learning and Neural Network Research Large Scale Data Mining Uncertainty Modeling in Data Mining Business Analytics - Applications: Credit Scoring and Financial Modeling Forecasting Fraud Detection Web Intelligence and Information Retrieval Marketing, Business Intelligence, and e-Commerce Decision Analysis and Decision Support Systems Social Network Analysis Privacy-preserving Data Mining and Privacy-related Issue Text Mining, Sentiment Analysis, and Opinion Mining Important Dates July 31, 2017: Deadline for submission of extended abstracts August 15, 2017: Accept/reject decision November 15, 2017: Deadline for early registration January 17-19, 2018: BAFI 2018 *Only one contributed abstract is accepted from the same presenting author. Submission Guidelines Authors are requested to submit a 600 word abstract in English using the platform available at the EasyChair system. Please do not attach any additional files at this time.