Cornell Chronicle: New technique boosts online medical search results. “A Cornell-led group of researchers has developed a search method that employs natural language processing and network analysis to identify terms that are semantically similar to those for cancer screening tests, but in colloquial language.”
Please, please, someone make the tool proposed in this research paper, Real Time Filtering of Tweets Using Wikipedia Concepts and Google Tri-gram Semantic Relatedness . Here’s the abstract: “Interest profiles contain the description of a topic that the user is interested in receiving relevant posts in real-time. Our proposed approach extracts Wikipedia concepts for profiles and tweets and applies a corpus-based word semantic relatedness method to assign tweets to their relevant profiles. This approach is also used to determine whether two tweets are semantically similar which in turn prevents the retrieval of redundant tweets.” And if someone already made this tool, tell me about it!
Want to explore video games? Two UCSC students made some cool tools. “In a UC-Santa Cruz research lab dedicated to the interdisciplinary study of computer games, two graduate students have combined linguistics and computational theory to create a new multidimensional library of 12,000 computer games. The web-based tools, GameNet and GameSage, offer novel ways to discover similar types of games.” And different types of games; if you use GameNet you can enter the name of a computer game and get the 50 most related games and the 50 most unrelated games. The 1991 game Bill & Ted’s Excellent Adventure is apparently completely unrelated to Dance Dance Revolution. And then there’s GameSage. “GameSage is a tool that takes free-text input describing an idea for a videogame and lists the existing games that are most related to that idea. This tool utilizes the notion in LSA of folding in, whereby a new […]
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