01389nas a2200157   4500008004100000245006400041210006200105260000900167520087100176653001501047653000801062100002001070700002201090700002101112856009801133       2016                        eng d00aUnraveling K-12 Standard Alignment; Report on a New Attempt0 aUnraveling K12 Standard Alignment Report on a New Attempt  c20163 aWe present the results of an experiment which indicates that automated alignment of electronic learning objects to educational standards may be more feasible than previously implied. We highlight some important deficiencies in existing alignment systems and formulate suggestions for improved future ones. We consider how the changing substance of newer educational standards, a multi-faceted view of standard alignment, and a more nuanced view of the ‘alignment’ concept may bring the long-sought goal of automated standard alignment closer. We explore how lexical similarity of documents, a World+Method representation of semantics, and network-based analysis can yield promising results. We furthermore investigate the nature of false positives to better understand how validity of match is evaluated so as to better focus future alignment system development.10aAccounting10aBIS1 aMarshall, Byron1 aReitsma, Reindert1 aSamson, Carleigh  uhttps://business.oregonstate.edu/biblio/unraveling-k-12-standard-alignment-report-new-attempt02064nas a2200181   4500008004100000245008400041210006900125260000900194300001400203490000700217520147700224653001501701653000801716100002001724700001901744700002001763856009901783       2008                        eng d00aUsing Importance Flooding to Identify Interesting Networks of Criminal Activity0 aUsing Importance Flooding to Identify Interesting Networks of Cr  c2008  a2099-21140 v593 aCross-jurisdictional law enforcement data sharing and analysis is of vital importance because law breakers regularly operate in multiple jurisdictions. Agencies continue to invest massive resources in various sharing initiatives despite several high-profile failures. Key difficulties include: privacy concerns, administrative issues, differences in data representation, and a need for better analysis tools. This work presents a methodology for sharing and analyzing investigation-relevant data and is potentially useful across large cross-jurisdictional data sets. The approach promises to allow crime analysts to use their time more effectively when creating link charts and performing similar analysis tasks. Many potential privacy and security pitfalls are avoided by reducing shared data requirements to labeled relationships between entities. Our importance flooding algorithm helps extract interesting networks of relationships from existing law enforcement records using user-controlled investigation heuristics, spreading activation, and path-based interestingness rules. In our experiments, several variations of the importance flooding approach outperformed relationship-weight-only methods in matching expert-selected associations. We find that accuracy in not substantially affected by reasonable variations in algorithm parameters and demonstrate that user feedback and additional, case-specific information can be usefully added to the computational model.10aAccounting10aBIS1 aMarshall, Byron1 aChen, Hsinchun1 aKaza, Siddharth  uhttp://people.oregonstate.edu/~marshaby/Papers/Marshall_JASIST_ImportanceFlooding_PrePrint.pdf02033nas a2200205   4500008004100000245011700041210006900158260000900227300001200236490000700248520135500255653001501610653000801625100002501633700001201658700002001670700001901690700001901709856009901728       2007                        eng d00aUser-Centered Evaluation of Arizona BioPathway: An Information Extraction, Integration, and Visualization System0 aUserCentered Evaluation of Arizona BioPathway An Information Ext  c2007  a527-5360 v113 aExplosive growth in biomedical research has made automated information extraction, knowledge integration, and visualization increasingly important and critically needed. The Arizona BioPathway (ABP) system extracts and displays biological regulatory pathway information from the abstracts of journal articles. This study uses relations extracted from more than 200 PubMed abstracts presented in a tabular and graphical user interface with built-in search and aggregation functionality. This article presents a task-centered assessment of the usefulness and usability of the ABP system focusing on its relation aggregation and visualization functionalities. Results suggest that our graph-based visualization is more efficient in supporting pathway analysis tasks and is perceived as more useful and easier to use as compared to a text-based literature viewing method. Relation aggregation significantly contributes to knowledge acquisition efficiency. Together, the graphic and tabular views in the ABP Visualizer provide a flexible and effective interface for pathway relation browsing and analysis. Our study contributes to pathway-related research and biological information extraction by assessing the value of a multi-view, relation-based interface which supports user-controlled exploration of pathway information across multiple granularities.10aAccounting10aBIS1 aQuiñones, Karin, D.1 aSu, Hua1 aMarshall, Byron1 aEggers, Shauna1 aChen, Hsinchun  uhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=4300830&arnumber=4300844&count=17&index=500487nas a2200133   4500008004100000245008400041210006900125260002400194653001500218653000800233100002000241700001900261856007300280       2006                        eng d00aUsing Importance Flooding to Identify Interesting Networks of Criminal Activity0 aUsing Importance Flooding to Identify Interesting Networks of Cr  aSan Diego, CAc200610aAccounting10aBIS1 aMarshall, Byron1 aChen, Hsinchun  uhttp://people.oregonstate.edu/~marshaby/Papers/Marshall_ISI_2006.pdf