Color and Pattern analysis using Flags of the world

@machinelearnbot

Ever wondered why certain countries have certain colors in their flags, why it has certain symbols and what are the different patterns? We started digging through, checking a Wikipedia article on this topic. This was a good start but we wanted to go deeper so we manually started eye balling each flag to understand the patterns and symbols. We needed to figure out what we can extract from the flags and there were three prominent elements. Our task was then to go through each flag and note down all the distinct colors, prominent patterns and symbols.


Twitter's live NFL news and analysis show premieres tonight

Engadget

Last year, Twitter held the rights for the NFL's Thursday night games, but Amazon snagged those streaming rights this season in a deal believed to have rung in around $50 million. Instead, the platform is getting a 30-minute long news and analysis show that will air Monday to Thursday every week through to the Super Bowl. And for prime time games and particularly important match-ups, #NFLBlitz will also air pregame dispatches via Periscope. For those who enjoyed watching NFL games on Twitter last year, fret not because the platform still has something to offer when it comes to live games. Stadium's 24/7 sports livestream launched on Twitter last week and the site is also working in a weekly WNBA stream, an MLB analysis show, PGA Tour coverage as well as a pro athlete-fan interaction show called #Verified.


Yang

AAAI Conferences

Inspired by recent works in Aspect-Based Sentiment Analysis (ABSA) on product reviews and faced with more complex posts on social media platforms mentioning multiple entities as well as multiple aspects, we define a novel task called Multi-Entity Aspect-Based Sentiment Analysis (ME-ABSA). This task aims at fine-grained sentiment analysis of (entity, aspect) combinations, making the well-studied ABSA task a special case of it. To address the task, we propose an innovative method that models Context memory, Entity memory and Aspect memory, called CEA method. Our experimental results show that our CEA method achieves a significant gain over several baselines, including the state-of-the-art method for the ABSA task, and their enhanced versions, on datasets for ME-ABSA and ABSA tasks. The in-depth analysis illustrates the significant advantage of the CEA method over baseline methods for several hard-to-predict post types. Furthermore, we show that the CEA method is capable of generalizing to new (entity, aspect) combinations with little loss of accuracy. This observation indicates that data annotation in real applications can be largely simplified.


Complex Network Analysis in Python

#artificialintelligence

The Pragmatic Programmers just published my book Complex Network Analysis in Python. The book covers both elements of complex network analysis (CNA), including social network analysis, and the use of networkx for CNA. It covers not only social networks, but also product, semantic, event, interaction, and other types of networks. The book has five complete case studies based on real-world data (including the "Panama papers") and numerous code examples. This book is currently in beta, so the contents and extracts will change as the book is developed.


Top 30 Social Network Analysis and Visualization Tools

@machinelearnbot

Cytoscape is an open source software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.Although Cytoscape was originally designed for biological research, now it is a general platform for complex network analysis and visualization. Cytoscape core distribution provides a basic set of features for data integration, analysis, and visualization. Additional features are available as Apps (formerly called Plugins). Apps are available for network and molecular profiling analyses, new layouts, additional file format support, scripting, and connection with databases.