Monthly Archives: November 2016

Phil 11.8.16

7:00 – 6:30 ASRC

Phil 11.7.16

6:30 – 3:00 ASRC

  • Notes from Aaron to discuss today:
    • Great article on RNN. Sample code available too.

    • Slider based decisions for clustering topic models where we weight similarity contributions individually, including entities (who the document is about via NLP extraction), BOW comparison, TF-IDF LS comparison, etc. The clusters change based off the combined contribution of each vector of attractors.
  • Starting review of Novelty Learning via Collaborative Proximity Filtering
  • LingPipe is tool kit for processing text using computational linguistics. LingPipe is used to do tasks like:
    • Find the names of people, organizations or locations in news
    • Automatically classify Twitter search results into categories
    • Suggest correct spellings of queries
  • GATE is open source software capable of solving almost any text processing problem
  • Semantic Vectors creates semantic WordSpace models from free natural language text. Such models are designed to represent words and documents in terms of underlying concepts. They can be used for many semantic (concept-aware) matching tasks such as automatic thesaurus generation, knowledge representation, and concept matching.
  • LSA-based essay grading – could be good for document classification/spam detection

Phil 11.4.16

6:45 – 3:00 ASRC

  • Nervous enough about the election to move 1/3 of my retirement into long term treasuries.
  • Writing up review of Topic-Relevance Map – Visualization for Improving Search Result Comprehension for IUI 2017. Done!
  • Got similarity distance working on retrieved documents using a config file


Phil 11.3.16

7:00 – 3:00 ASRC

Phil 11.1.16

7:00 – 5:00 ASRC

  • Playing around with using dissertation to search from. Interesting and different results for non–and-equalized docs and single counts.
    • baseline: information model behavior agent result pattern search system between
    • equalized docs: information search behavior design system result source document provide
    • single counts: information result provide system between search process example behavior
    • equalized + single: information result provide between search system process approach design
  • Finishing survey and sending out – done!
  • Tested the new CSE
  • Back to Vector space models of semantics
  • Worked on proposal with Aaron.