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- also see "Tag Based Model for Knowledge Sharing in Agent Society"
- comparative analysis of clickstream from Twitter
- At the core of We Feel Fine is a data collection engine that automatically scours the Internet every ten minutes, harvesting human feelings from a large nu...At the core of We Feel Fine is a data collection engine that automatically scours the Internet every ten minutes, harvesting human feelings from a large number of blogs. Blog data comes from a variety of online sources, including LiveJournal, MSN Spaces, MySpace, Blogger, Flickr, Technorati, Feedster, Ice Rocket, and Google. We Feel Fine scans blog posts for occurrences of the phrases "I feel" and "I am feeling". This is an approach that was inspired by techniques used in Listening Post, a wonderful project by Ben Rubin and Mark Hansen. Once a sentence containing "I feel" or "I am feeling" is found, the system looks backward to the beginning of the sentence, and forward to the end of the sentence, and then saves the full sentence in a database. Once saved, the sentence is scanned to see if it includes one of about 5,000 pre-identified "feelings". This list of valid feelings was constructed by hand, but basically consists of adjectives and some adverbs. The full list of valid feelings, along with the total count of each feeling, and the color assigned to each feeling, is here.
- by Ron Kohavi
- Modeling Web Searching Behaviors and Designing New Effective Interactions for Digital Libraries
- on n-mode network analysis
- A project seemingly similiar ConceptNet, Lucy Vanderwende (Microsoft Research)
- An article on the Top 10 Algorithms in Data Mining
- a theory by M. Minsky
- presented at IUI by Jeffrey Bigham, Anna Cavender, Ryan Kaminsky (University of Washington, USA)
- book draft, logic
- PPrett: The major clou is that the topical clusters (e.g. Information Retrieval, Machine Learning) can be sorted according to their HITS scores (Hub, Autho...PPrett: The major clou is that the topical clusters (e.g. Information Retrieval, Machine Learning) can be sorted according to their HITS scores (Hub, Authority).
- recommended by SEAOSS
publications
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- V. Choi Presented at the SIAM Conference on Discrete Mathematics, (2006)
- B. Di Eugenio and M. Glass Computational Linguistics30(1):95--101(2004)
- A.J. Smith Computer23(4):65--71(1990)
- J. Espinosa MIT Media Laboratory, Massachusetts Institute of Technology, Cambridge, MA, (2005)
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- J. Teevan Massachusetts Institute of Technology, (2006)
- J.M. McPherson Social Networks(1982)
- D.A. Smith Massachusetts Institute of Technology, (2007)
- M. Pasca CIKM '07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, page 683--690. New York, NY, USA, ACM, (2007)
- S.M. Beitzel Illinois Institute of Technology, (2006)
- MEJ Newman Proceedings of the National Academy of Sciences103(23):8577--8582(2006)
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- Sensemaking tools for understanding research literatures: design, implementation and user evaluation
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