Key Research Interests and Scientific Questions (with selected writings):

• What is information?
  • Information From Processes: About the Nature of Information Creation, Use, and Representation, Springer, 2012 ( http://dx.doi.org/10.1007/978-3-642-31190-1 ). Book's web site.
  • A Discipline Independent Definition of Information, Journal of the American Society for Information Science, 48 (3), pp. 254-269, 1997. (published article)
• How can one predict information retrieval performance using a formula, instead of running an IR experiment?
  • Measuring Search Engine Quality and Query Difficulty, Journal of the American Society for Information Science, 50 (10), pp. 882-889, 1999. (Losee & Paris) (published article.)
  • When Information Retrieval Measures Agree about the Relative Quality of Document Rankings, Journal of the American Society for Information Science, 51 (9), pp. 834-840, 2000. (published article.) (Won JASIS Best Paper of the Year Award, 2000.)
  • Text Retrieval and Filtering: Analytic Models of Performance (Information Retrieval Series), Kluwer, 1998.
  • Information Retrieval with Distributed Databases: Analytic Models of Performance, IEEE Transactions on Parallel and Distributed Systems. 15, 2004, 18-27. (Losee & Church)
• What does a single term do? How does adding or deleting a single metadata or indexing term or tag from a document affect the performance of the system?
  The Effect of Assigning a Metadata or Indexing Term on Document Ordering, Journal of the American Society for Information Science and Technology. 2013, In Press.
• How does one use a thesaurus and what are its characteristics?
  • A Random Walk on an Ontology: Using Thesaurus Structure for Automatic Indexing, Journal of the American Society for Information Science and Technology. 2013, In Press. Willis and Losee.
  • Decisions in Thesaurus Construction and Use, Information Processing & Management. 43 (4), 2007, 958-968. (published article).
  • "Vocabulary Conversion: Performance with Controlled and Uncontrolled Terms and Tags" UNC-CH SILS Technical Report TR-2008-02.
  • A Performance Model of the Length and Number of Subject Headings and Index Phrases, Knowledge Organization. 31 (4) (2004), 245-251.
• How should items be arranged on a computer display or on a book shelf so that the arrangement is optimal?
  • A Gray Code Based Ordering for Documents on Shelves: Classification for Browsing and Retrieval, Journal of the American Society for Information Science 43(4), 312-322, 1992. (published article)
  • Browsing Mixed Structured and Unstructured Data, Information Processing & Management. 42 (2) 2006, 440-452. (published article)
• How do aspects of natural language contribute to retrieval performance?
  • Is 1 Noun Worth 2 Adjectives? Measuring the Relative Feature Utility, Information Processing & Management. 42 (5) 2006, 1248-1259. (published article)
  • Natural Language Processing In Support of Decision-Making: Phrases and Part-of-Speech Tagging, Information Processing & Management, 37 (6), pp. 769-787, 2001. (published article.)
  • Text Windows and Phrases Differing by Discipline, Location in Document, and Syntactic Structure, Information Processing & Management, 32 (6), pp. 747-767, 1996.
  • Term Dependence: A Basis for Luhn and Zipf Models, Journal of the American Society for Information Science and Technology, 52 (12), pp. 1019-1025, 2001. (published article.)
  • Learning Syntactic Rules and Tags with Genetic Algorithms for Information Retrieval and Filtering: An Empirical Basis for Grammatical Rules, Information Processing & Management, 32(2), pp. 185-197, 1996. (published article)
  • Term Dependence: Truncating the Bahadur Lazarsfeld Expansion, Information Processing & Management, 30(2), pp. 293-303, 1994. (published article)
• How should retrieval systems "learn" from users and what kind of information does a query provide? (Also see the earlier question about ways to predict retrieval performance.)
  • Parameter Estimation for Probabilistic Document Retrieval Models, Journal of the American Society for Information Science, 39(1), pp. 8-16, 1988. (Performance with different Bayesian Relevance Feedback techniques.)
  • Integrating Boolean Queries in Conjunctive Normal Form with Probabilistic Retrieval Models, Information Processing & Management, 24(3), pp. 315-321, 1988. (Losee & Bookstein)