Monthly Archives: June 2016

Phil 6.6.16

6:30 – 1:00 Writing

  • Realized that I had forgotten to go into how information seeking behavior of the IR users can potentially be used to vet the quality of the information they are looking at.
  • Working my way through the lit review.

Phil 6.5.16

8:00 – 2:00 – Writing

Phil 6.4.16

7:30 – 1:30 Writing

  • More on libraries and serendipity. Found lots, and then went on to look for metions in electronic retrieval. Found Foster’s A Nonlinear Model of Information-Seeking Behavior, which also has some spiffy citations. Going to take a break from writing and actually read this one. Because, I just realized that interdisciplinary researchers are the rough academic equivalent of the explorer pattern.
  • Investigating Information Seeking BehaviorUsing the Concept of Information Horizons
    • Page 3 – To design and develop a new research method we used Sonnenwald’s (1999) framework for human information behavior as a theoretical foundation. This theoretical framework suggests that within a context and situation is an ‘information horizon’ in which we can act. For a particular individual, a variety of information resources may be encompassed within his/her information horizon. They may include social networks, documents, information retrieval tools, and experimentation and observation in the world. Information horizons, and the resources they encompass, are determined socially and individually. In other words, the opinions that one’s peers hold concerning the value of a particular resource will influence one’s own opinions about the value of that resource and, thus, its position within one’s information horizon. 

Phil 6.2.16

7:00 – 5:00 VTX

  • Writing
  • Write up sprint story – done

    • Develop a ‘training’ corpus known bad actors (KBA) for each domain.

      • KBAs will be pulled from http://w3.nyhealth.gov/opmc/factions.nsf, which provides a large list.
      • List of KBAs will be added to the content rating DB for human curation
      • HTML and PDF data will be used to populate a list of documents that will then be scanned and analyzed to prepare TF-IDF and LSI term-document tables.
      • The resulting table will in turn be analyzed using term centrality, with the output being an ordered list of terms to be evaluated for each domain.

  • Building view to get person, rating and link from the db – done, or at least V1 
    CREATE VIEW view_ratings AS
  select io.link, qo.search_type, po.first_name, po.last_name, po.pp_state, ro.person_characterization from item_object io
    INNER JOIN query_object qo ON io.query_id = qo.id
    INNER JOIN rating_object ro on io.id = ro.result_id
    INNER JOIN poi_object po on qo.provider_id = po.id;
  • Took results from w3.nyhealth.gov and ran them through the whole system. The full results are in the Corpus file under w3.nyhealth.gov-PDF-centrality_06_02_16-13_12_09.xlsx and w3.nyhealth.gov-WEB-centrality_06_02_16-13_12_09.xlsx. The results seem to make incredibly specific searches. Here are the two first examples. Note that there are very few .com sites.:

Phil 6.1.16

7:00 – 2:00VTX